Int. J . Plant Sci. 168(9):1293-1309. 2007. Copyright is not claimed for this article. DOl: 10.1086/521692
GENETIC STRUCTURE AND GENE FLOW AMONG SOUTH FLORIDA POPULATIONS OF IRIS HEXAGONA WALT. (IRIDACEAE) ASSESSED WITH 19 MICROSATEILITE DNA LOCI Alan W. Meerow , )* Michael Gideon,t David N. Kohn , * Juan Carlos Motamayor,4 and Kyoko Nakamura* USDA-ARS, Subtropical Horticulture Research Station (SFIRS), National Germplasm Repository, 1 3601 Old Cutler Road, Miami, USA; and iMastertoods Florida 311 313, U.S.A.; tGideons Iris, 15455 Southwest 232nd Street, Homestead, Florida 33030, U.S.A. 33158, Old Cutler Road, Miami, Florida 1.3601 USDA-ARS-SI IRS, USA Mars, Inc.), c/o We investigated genetic variation within and among 11 populations of Iris hexagona at its southern limits in the Florida peninsula by using 19 microsatcllite loci. All of the populations contain var y ing numbers of identical multilocus genotypes, indicative of clonal reproduction. Two population samples consist largely of one clonal lineage and two clonal lineages: the first from the Caloosahatchee drainage west of Lake Okeechobee and the other from the Big Cypress Swamp. The populations are predominantly outcrossing, with high levels of heterozygosity, and show a highly significant pattern of isolation by distance that fits a modified stepping-stone model. This pattern breaks down at the local level, however, where metapopulation dynamics or asymmetrical gene flow may exert a stronger effect on patterns of genetic diversity. Though the majority of genetic variation is within populations, 20% occurs between populations. Genetic distance resolves five clusters: four in the Caloosahatchee Valley and one in the Big Cypress Swamp. However, the populations are differentiated strongly enough that frequency-based genetic structure analysis resolves seven effective populations. Assignment tests identify the northernmost population as a likely ancestral point of origin for the others. All of the populations exhibit evidence of a recent bottleneck, which we attribute to founder effects, given the low migration rate of the species and the high degree of population differentiation, as well as the Holocene geological history of the Florida peninsula. We hypothesize that the two predominantly clonal populations may he artifacts of deliberate cultivation by humans. Keywords: population genetics, population biology, SSR, heterozygosity excess, bottleneck, isolation by distance, stepping-stone model, founder effects, Florida, phytogeography.
Iris hexagona Walter is the most southerly occurring iris species in the United States and achieves its broadest geographic range in Florida, occurring throughout the peninsula to the Big Cypress Swamp in Monroe County. In the eastern half of the southern peninsula, the species does not occur south of Lake Okeechobee (Hume 1933). It is a member of the subsection or series Hexagonae, a small complex of three species and associated hybrid populations (Randolph 1966; Arnold et al. 1990a, 1990b; Arnold 1993a, 1993b), popularly known as the "Louisiana irises." Iris hexagona occurs mostly in open freshwater swamps in Louisiana, Mississippi, Alabama, Georgia, South Carolina, and Florida (Viosca 1935; Bennett 1989) and frequently forms large populations, though this broad range assumes only a single species. In the Flora of North America treatment of the genus, Henderson (2002) recognized two segregates as distinct species: Iris gzganticaerulea Small (coastal Alabama to Louisiana) and Iris savannarum Small (Alabama, Georgia, Florida). Henderson (2002) assigned the name I. hexagona only to populations from South Carolina and a few disjuncts in northern Florida. Author for correspondence; telephone 305-254-3635; fax 305969-6410; e-mail
[email protected] . Manuscript received April 2007; revised manuscript received June 2007.
The Hexagonae group of Iris has been recognized as a textbook case of introgressive hybridization since the classic work of Anderson (1949) summarized the findings of Viosca (1935), Foster (1937), and Riley (1938, 1939), which overturned Small and Alexander's (1931) unprecedented recognition of more than 80 species in the Louisiana iris group. Arnold and his students and colleagues (Arnold et al. 1990a, 1990b, 1991, 1993; Arnold 1992, 1993a, 1993b; Arnold and Bennett 1993; Cruzan and Arnold 1994; Cruzan et al. 1994; Emms and Arnold 1997; Burke et al. 1998, 2000a, 2000h; Burke and Arnold 2001) have broadened this investigation on vanoils fronts with molecular data and both in situ and ex situ experiments, not only confirming hypotheses concerning introgressive hybridization among Louisiana iris species but also using the group as a model of the processes involved in natural hybridization and evolution (Arnold 2000; Arnold et al. 2003). What hasnot been available for any of the three Louisiana Iris species is a multilocus, multipopulation study of genetic structure and gene flow outside of the context of natural hybridization. In this article, we investigate the population genetics of ii populations of 1. hexagona (=1. savannarum sensu Henderson 2002) by using 19 microsatellite (simple sequence repeat [SSR]) DNA loci. These 11 populations constitute ca. 25% of the populations of I. hexagona that we are in the 1291
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process of studying and represent the southernmos t distribution of the genus in the United States. Moreover, these 11 populations consistently form a cluster supported by >50% bootstrap support in all distance phenograms generated by various genetic distance coefficients across all of our sampled populations (A. W. Meerow, unpublished data); thus, we feel confident that they share a genealogical history. SSRs provide an ideal tool for assessing the genetic diversity of plants (Chase et al. 1996; Powell et al. 1996a; Zhang and Hewitt 2003) because of their high information content, ease of genotyping, codominant and multiallelic nature, high discriminatory power, and reproducibility (Morgante and Olivieri 1993; Powell et al. 1996a, I 996b; Jones et al. 1997; Russell et al. 1997). For a wetland species such as 1. hexagona, population structure and gene flow might he expected to reflect the Paleocene and Holocene history of Florida during glacial and interglacial periods, when sea level fluctuated extensively. For the past 5000-8000 yr, rising sea level accompanied by a rising water table expanded swamp vegetation in the southern peninsula suitable for I. hexagona establishment (Watts and Hansen 1994). We hypothesize that populations should show the genetic consequences of founder effects as new habitats were colonized since the last glaciation. Previous studies of iris have reported low dispersal and migration potential (Arnold 1993h; Arnold et al. 1993; Arafeh et al. 2002); thus, we hypothesized that if this were true of I. hexagona as well, a stepping-stone pattern of differentiation with significant isolation by distance should he detectable. Louisiana irises are capable of both clonal and sexual reproduction (Burke et al. 2000a). We wished to assess the significance of clonal reproduction among these populations and the degree to which it varied. Finally, we sought to estimate the significance of migration among the populations as a factor contributing to the patterns of genetic variation observed.
Material and Methods Sampling Twenty-four to 38 samples were collected from each of 11 discrete (separated by an intervening area without iris) populations (for all population abbreviations, see table 1; fig. 1), except FEC (n = 11) and TG (n = 14). None of the populations was accessible by road, and collections required travel by foot, thereby avoiding recent anthropogenic influences on population structure. All of the populations were large, containing many thousands to more than a million ramcts, with the exception of AM, which contained ca. 10,000. Samples were collected randomly but from the geographic breadth of the population, maintaining a minimum distance of 10 111 between samples in order to lower the likelihood of sampling clones. Leaf material was collected in bags of silica gel before extraction. Though there are some extant populations of Iris hexagona in the intervening area between the eight sampled in the Caloosahatchee drainage and the three in the Big Cypress Swamp, we were not able to obtain permission to access these sites. AM was sampled more heavily because we suspected a high incidence of clones in that population at the outset on the basis of observations of high uniformity (M. Gideon, personal observation). FEC and TG were more lightly sampled as a result of the difficulty of access.
Microsate/lite Isolation and DNA Extraction, Amplification, and Visualization SSRs were isolated and primers designed as described by Meerow et al. (2005), using a method modified from that of Edwards et al. (1996), with streptavidin-coated beads (Dvnal, Oslo) in conjunction with a Dynal magnetic particle concentrator. DNA was extracted and amplified with SSR primer pairs (the forward primer fluorescently labeled) as described
Table 1 South Florida Populations of Iris hexagona Used in the Study of Genetic Variation with 19 Simple Sequence Repeat Loci
Name
Abbreviation
County
Altman
Latitude (°N)
Longitude (°W)
AM
Charlotte
26.833
Bee Branch
BE
Glades
Fishcating Creek Gannett Strand
FEC GS
Glades Collier
Jacks Branch
0
Voucher
81.600
38
Meerow 3035
26.825
81.492
24 Meerow 3003
25.867
26.933
81.267 81.058
11 Meerow 3008 24 Meerow3OJO
Glades
26.833
81.567
24 Meerow 3015
Monument Lake
ML
Collier
25.883
81.150
24 Mcerow 3019
Pollywog PollywogX Sweetwater Turkey Creek Thigpen
P PX SW iC TG
Glades Glades Monroe Glades Glades
26.816 26.800 25.783 26.800 26.783
81.467 81.450 81.092 81.300 81.450
24 24 24 24 14
Note.
it
= number of collected samples. All vouchers are deposited at FIG.
Meerow 3023 Meerow 3025 Meerow 3028 Meerow 3029 Meerow 3033
Population characteristics Small depression (0.1 ha), ca. 3 rn below sea level amid high and dry pine and oak woods Broad swampy headlands for Bee Branch slough, cypress and wet prairie Riverine, cypress strand Old-growth cypress, deep water, no evidence of fire events Long, broad slough punctuated by sandy, dry uplands Very open shallow water, evidence of past fire events Old river bottom, cypress Old river bottom, cypress Young cypress, evidence of past fire events Broad slough, cypress and wet prairie Old river bottom, cypress, some wet prairie
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MEEROW ET AL—IRIS SIMPLE SEQUENCE REPEATS 81.8333W
26.9167 N-
26,8333 N-.'
bA,
'JAM
26.7500 N-
-25,8333 N
37-km
Fig. 1
Map of southern peninsular Florida showing distribution of the
by Meerow et al. (2005). Differences in allele size were detected on an ABI 3100 genetic analyzer (Applied Biosystems, Foster City, CA) using capillary gel electrophoresis as described by Meerow et al. (2005). Preliminary analysis of raw microsatellite data was performed using Genemapper 3.5 (Applied Biosystems).
Data Analysis Clonality. The number of multilocus genotypes (MLGs) was computed for each population with GENALEX (Peakall and Smouse 2006). Populations containing individuals with identical genotypes were further analyzed with the program
II Iris hexagona
populations sampled.
GenClone (Arnaud-Haond and Belkhir 2007) to generate various statistics of genotypic diversity: number of distinct MLGs, modified index of genotypic richness (Dorken and Eckert 2001), Shannon-Weiner diversity (Shannon and Weaver 1963; Washington 1984), Shannon evenness (Hill 1973), and Hill's Simpson reciprocal (Hurlbert 1971; Hill 1973). The latter is essentially a measure that combines diversity and evenness and corresponds to the "apparent number of genotypes" in the population (Arnaud-Haond and Belkhir 2007). Several probability tests for inferring clonality (Tibayrenc et al. 1990; Parks and Werth 1993; Sydes and Peakall 1998; Stenberg et al. 2003; Arnaud-Haond et al. 2005; Gregorius 2005)
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were also calculated. The data set was first reduced by indiMutation model. The allele size permutation test of viduals and/or loci in order to eliminate missing data. Three Hardy et al. (2003) was used to assess whether a stepwise thousand permutations on both loci and individuals were first mutation process (SMM; Kimura and Ohta 1978) should be run to test how well the sampling density could estimate the reflected in the choice of distance measures used for analysis actual number of MLGs in the population (Arnaud-Haond of the populations. SMM assumes that alleles mutate by sinet al. 2005). Tests for clonal propagation in GenClone are gle repeat changes in a stepwise manner, compared with the based on the round-robin method proposed by Parks and infinite allele model (LAM; Kimura and Crow 1964), in which Werth (1993), which allows for each MLG an estimate of the multiple repeat unit changes may take place in a single mutaprobability of identical genotypes arising under sexual reprotion event. The analysis was conducted with the program SPAduction under random mating (P 6 ) and the probability of GeDi, version 1.2. (1-lardy and Vekemans 2002), with the obtaining the observed number of repeated MLGs in the sammaximum allowable number of permutations (20,000), on the ple by sexual reproduction under random mating The matrix transformed from fragment size in base pairs to numcalculation for is (flp,)2", where p, is the frequency of ber of repeat units. The test allows the comparison of observed each allele (two per locus) observed in the MLG and h is the (i.e., nonpermutated) R 5 -r, an analog of Wright's (1965) coannumber of loci that are heterozygous. The calculation for cestry coefficient j'si that incorporates allele size and thus asis N!/[n!(N - n)!(l'gn)'( 1 -- Pgc,j ) ", where N is the sumes the SMM (Slatkin 1995), with the value of Rr after total number of samples, regardless of the number of differpermutation (PR ST ). A nonsignificant probability that PR ST is ent genotypes, and n and z are the number of times the MLG higher than R 51- supports the null hypothesis that the stepwise is repeated. We did not report the more conservative test of mutation model is not applicable and thus that Fç1- is a better the same probabilities that takes into account the estimated measure of population differentiation (I lardy et al. 2003). inbreeding coefficient Fl s in the population (Young et al. Genetic distance and Mantel tests. A Euclidean geographic 2002) because F I s values were significant (p < 0.05, based on distance matrix was generated from latitude/longitude coor20,000 permutations by locus) in only two of the 11 populadinates with the program SPAGeDi, version 1.2 (Hardy and tions. Where possible (two populations, AM and ML), the Vekemans 2002). Genetic distance measures and unrooted significance of P was rested at the 0.01 level with the proneighbor-joining (Sairou and Nei 1994) trees with bootstrapgram MLGsim (Stenberg et al. 2003) running 106 simulaping by locus were generated with the program POPULAtions of the data. For most of the other tests described, an TIONS, version 1.30.2 (Langella 2003). Five genetic distance adjusted data set was used with repeating Ml.Gs reduced to measures that incorporate the LAM were generated: Da (Nei a single representative. et al. 1983), DAS (Jin and Chakrahorry 1993), Dc (CavalliGenetic variation. The program MICRO-CHECKER, verSforza and Edwards (1967), Dr (Rogers 1972), and Cp (l'revosti sion 2.2.3 (van Oosterhout et al. 2004), was used to identify 1974). Trees were visualized with Tree Explorer as implemented putative errors of three types in our data (DeWoody et al. in MEGA3 (Kumar et al. 2004). The distance matrices were 2006): stuttering patterns, large-allele dropout, and null alleles also used for permuted (10,000 iterations) Mantel (1967) tests on the adjusted data set (reduced to unique Ml.Gs). A modiof correlation with geographic distance and pairwise correlation fied data set was created with values set to "missing" for loci between each other, following the methods of Smouse et al. in populations with putative nulls, and descriptive statistics (1986) and Smouse and Long (1992), as implemented in GENwere generated for the adjusted data set for comparative purALEX (Peakall and Smouse 2006). These distance coefficients poses. were also used in principal coordinate analysis (PCA) with Descriptive statistics (number of alleles per locus, A; number GENALEX. ICA plots were generated in MS Excel (Microsoft, of alleles with frequency . = 0.752 (p = 0.006). However, when the same tests were conducted only on a regional cluster of populations (the central Caloosahatchee group of BE, P. PX, and TG), there was no significant correlation with geographic distance by either measure (with Da: R., = -0.280, p = 0.329; with Fs i = -0.306, p = 0,288). Likewise, the Big Cypress group showed a similar lack of cor= relation (with Da: R 5, = - 0.688, p = 0.333; with Fsr 0.021, p = 0.501). Genetic Structure All pairwise F51 values between populations (table 7) were significantly high (>0.100) at the p < 0.001 level, indicating a substantial level of genetic differentiation among the populations. The results of the AMOVA were highly significant as well (p < 0.0001), with 80.5% of the variation within populations (df = 287, sum of squares = 1700.196, variance = 5.924) and 19.6% among populations (df = 10, sum of squares = 444.042, variance = 1.43857). If a regional structure is imposed on the population conforming to the clusters resolved by genetic distance (fig. 3), 78.9% of the variation is within populations (df = 287, sum of squares = 1700.196, variance = 5.92403), 11.5% among populations within groups (df = 7, sum of squares = 197.816, variance = 0.86678), and 9.6% among the four groups (df = 3, sum of squares= 246.227, variance = 0.71799). The highest modal value for Lxk indicated 7 as the true value of k. Ten of the 11 populations have >80% membership in one of the clusters (fig. 4A; table 8); i.e., the cluster is essentially synonymous with that population. The most heavily admixed population is TC, with the highest proportion of
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IN TERNATIONAL JOURNAL OF PLANT SCIENCES
A •AM2O • Ath'9 •AMO3
0
• AMI
•1
I-
0 0
C-)
clonal lineage
•AM25 •AM17 (..00rd.
1 (77.9% var.)
B ML2 •ML
(5
>
clonal lineage I
(0
0
CM I-
0 0
clonal lineage 2
C)
ML17 L000. 1 (7.6%
var.)
Fig. 2 Principal coordinate analysis (PCA) scattergrams of two extensively clonal iris hexagona populations using Nei et al's (1983) genetic distance. A, Altman (AM) population. B, Monument Lake (ML) population.
membership in any one cluster being 0.560, followed by BE
(0.856). The three Big Cypress populations are placed into a
single cluster, all at >90% membership (yellow in fig. 4A). AM and J are likewise assigned to the same cluster (green in fig. 4A), though J exhibits more admixture. More than a third of the total sample of TC is assigned to the same cluster as the majority of FEC (red in fig. 4A). FEC and TC exhibit the greatest degree of genotypic heterogeneity, showing significant admixture with eight and five population clusters, respectively (table 8). Overall, the larger Okeechobee clusters (BE, FEC, P, PX, TC, and TG) show more evidence of admixture than the secondary Okeechobee cluster represented by AM and J. The single cluster encompassing the Big Cy-
press populations (GS, ML, and SW) shows little significant admixture with any other cluster, though a single individual of CS has a 0.08 probability of membership in the cluster dominated by FEC and TC. Using GENECLASS with the original 11 populations suggests that membership is less discrete and assignments less successful. Six of the populations had individuals that could not be assigned to origin with p ^! 0.5 or to the putative ancestral population at p ^! 0.05, probably because other source populations were not sampled. Nonetheless, many of the same admixture patterns detected by STRUCTURE are resolved (table 9). The clustering of the three Big Cypress populations by STRUCTURE is mirrored in assignment of individuals of
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MEEROW ET AL-IRIS SIMPLE SEQUENCE REPEATS
Table 4 Characteristics and Descriptive Statistics of the 19 Simple Sequence Repeat Loci Used for Genetic Analysis Populations with All Samples Included Reduced to Unique MLGs across 11 Iris hexagona
Locus 11-142 lH56 1H57 IH63 1H73 1H86A ll-186 B 1H122 IH 153 11-1155 11-1183 1H203 11-1204 111211 1H212 11-1214 11-12 22 1H225 1H227 ver
Repeat
(AG) 19 (Cl)'3 (CT)3' )TC)22 )TG)'5•(c;r(;)' )'rc)' 5 ac ) 15
(TC)'6 (GA)2' (GA)19 (TGT)'5 (GA)2' (TC)3('IT)(TC)'7 (Cl') ' (AG ')C(;)(A(-;)'6 (GT)'9 (AC)'5 (CA)'7 (CT)'7
Allele range (hp)
GenBank accession no.
122-156 245-307 217-263 92-122 157-173 127-153 209-235 76-108 197-203 232-266 139-183 78-98 119-147 167-201 215-283 203-245 121-131 79-119 150-184
AY 8220 16 AY82202 I AY822023 AY822024 AY82201 8 AY 82 2022 AY822022 AY822025 AY822017 AY822020 AY82201 9 DQ650302 DQ650303 1)Q650304 DQ6S 0305 DQ650306 DQ650307 DQ6S 0308 DQ650309
n 148 146 139 147 149 148 148 145 144 135 148 149 144 148 145
136 148 146 148
A
15 21 14 16 9 12 16 18 17 II 10 11 14 19 19 6 15
13
H, .653 .840 .880 .792 .672 .798 .801 .883 .862 .862 .789 .576 .831
.865 .855 .904
H .523 .711 .577
.630 .509 .635
.635 .730 .640 .686 .724 .427 .60.5 .700 .639
H', .559
.724 .628 .722 .551
.762 .762 .809 .689 .716 .768 .462 .631
.591
.754 .859
.621 .643
.776
.557
.756
.732 .419 .674 .485
.652
F's .011 .003 -.059 -.082 -.123 --.055
-.037 -.012' --.0003 -.022 -.013 -.002 - .060 3501.g -.061 2581,g -.117 --.011
1'ST
.186 .137 .260 .191 .191 .188 .176 .144 .251
.175 .209 .227 .239 .170 .219 .240 .160 .252 .249 .204
total expected heterozygosity (all samples pooled, no population subdivision), 11, = Note. n - sample size, A -= number of alleles, H, = F, 5 = inbreeding mean expected heterozygosity (with population subdivision), II, = mean observed heterozygosity (with population subdivision),
coefficient, F,, = coancestry coefficient. a Clonal genotypes reduced to single representative. Significant at p < 0.001 based on 20,000 permutations by locus. Significant departure from Hardy-Weinberg equilibrium (HWE) at p < 0.05. d I-letero7.ygote excess. Significant departure from HWE at p < 0,01. i Heterozygote deficit. S
Significant departure from HWE at p < 0.001.
GS and MI. to SW and of SW to ML. As with STRUCTURE, admixture between J and AM (its nearest geographic neighbor) is captured. GENECLASS also identifies admixture between FEC and GS, though at higher levels than STRUCTURE. The most striking aspect of the GENECLASS analysis is the fact that every population other than SW shows some significant proportion of membership in FEC. Substructure within the Big Cypress cluster was also estimated with STRUCTURE. The most likely value of k = 2 (fig. 4B). While GS and SW resolve with >90% proportionate membership as distinct population clusters, the seven unique genotypes of ML appear heavily admixed, with 29% assigned to GS and 71% to SW. A single individual of GS has a probability of 0.995 of originating in SW; a second is assigned with nearly even probability to both clusters (0.48 [GS] and
0.52 [SW1, respectively). Two individuals of SW are admixed between both clusters, with probabilities of 0.577 (SW) and 0.423 (CS) and 0.687 (SW) and 0.313 (GS), respectively. In ML, two genotypes are assigned to SW with >0.99 probability and the remaining five to GS with >0.99 probability. Both of the putatively clonal genotypes are in this latter group. Similarly, we analyzed substructure within the central Caloosahatchee cluster. The most likely value of k = 2 (fig. 4C). More than 90% of BE, and P resolve within one cluster (northern), and >90% of PX and TG resolve in the second
(southern) cluster. One individual of BE had >90% probability of membership in the second cluster, and another individual had roughly equal probability of originating in either
subgroup. All individuals of P and PX were assigned to the first and second clusters, respectively, while one individual of TG had a 34% probability of membership in the first cluster. Migration Using GENECLASS to identify first-generation migrants suggests that recent migration is relatively rare. Discounting any exchange among the Big Cypress populations (GENECLASS identified one migrant from SW to GS and two from SW to ML), which STRUCTURE suggests are (or were recently) panmictic, we found that only two migrants were identified: BE from PX and J from FEC, both at p < 0.0001. Overall
migration rate among the populations, estimated by the PA method after correction for size, was 0.89. The migration rate estimated from pairwise F ST values is uniformly higher
than that estimated by the PA method, but there is good concordance between the two (Spearman rank correlation r, = There 0.89, p < 0.0001, 95% confidence interval = 0.82-0.94). are some differences, however. Highest Nm (gene flow) estimates by the PA method are between BE and PX, while with FST, the highest Nm is between FEC and J.
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INTERNATIONAL JOURNAL OF PLANT SCIENCES Table 5 Descriptive Statistics and Allele Patterns of 11 Iris hexagona Populations across 19 Simple Sequence Repeat Loci Ak
Population AM BE FEC CS ML P Px SW TC TG
7.7 19.8 8.6 19.8 18.8 6.8 11.8 14.5 17.8 11.8 8.7
A
Af
3.3 6.2 6.4 4.3 6.4 3.7 3.8 5.1 4.0 5.1 4.5
54 92 122 63 100 63 63 76 64 69 86
Private alleles
Frequency
