Variation of the interphase heterochromatin in Artemia (Crustacea, Anostraca) of the Americas is related to changes in nuclear size and ionic composition of hipersaline habitats/ Variacao da heterocromatina interfasica em Artemia (Crustacea, Anostraca) das Americas esta relacionada a mudancas no tamanho nuclear e composicao ionica em habitats hipersalinos.
1. IntroductionHeterochromatin is a characteristic component of the eukaryotic nucleus which, as opposed to euchromatin, is highly compacted, non-coding and contains highly repetitive DNA sequences (Swanson et al., 1981; Brutlag, 1980). The heterochromatin in the interphase nucleus can be visualized as easily discernible heteropycnotic bodies, called chromocenters, which can vary in number and size. In the brine shrimp Artemia, a conspicuous inhabitant of hypersaline lakes and lagoons, the chromocenter number may have a diagnostic value as an indicator of species or populations (Badaracco et al., 1987; Abreu-Grobois and Beardmore, 1989; Colihueque and Gajardo, 1996; Papeschi et al., 2000; Gajardo et al., 2001; Torrentera and Abreu-Grobois, 2002; Papeschi et al., 2008). Previous studies indicate that the heterochromatin in Artemia varies in quantity and quality both within and among species (Gajardo et al., 2002). For instance, the New World Artemia species, A. franciscana and A. persimilis, have a significantly different chromocenter number (Badaracco et al., 1987; Abreu-Grobois and Beardmore, 1989; Colihueque and Gajardo, 1996; Papeschi et al., 2000; Gajardo et al., 2001; Torrentera and Abreu-Grobois, 2002; Lipko et al., 2004). While the former exhibits a high number of these structures (5-18 chromocenters) the latter has lower numbers (<5 chromocenters). Such variation in the amount of heterochromatin is also associated with the presence of repetitive AM sequences in the genome, with around a tenth less of these sequences being observed in A. persimilis in comparison with A. franciscana (Barigozzi et al., 1984; Badaracco et al., 1987). In addition, chromosome studies of these species have revealed an interspecific variation in the diploid chromosome number, consisting of 42 in A. franciscana and 44 in the case of A. persimilis.
The evidence available on plants and animals indicates that variation in the DNA content per genome, usually positively associated with the increase in the amount of heterochromatin (Rayburn et al., 1985; Kao et al., 2001; Bosco et al., 2007), may produce changes at the cellular (termed nucleotypic effect), or organismal level (Gregory and Hebert, 1999). In other words, the phenotype expression would not just depend on the interaction between genotype and environment, but also on the expression of the DNA quantity, irrespective of its informational content (Swanson et al., 1981; Hartl, 2000). For instance, at the cellular level, this modification may affect either the cell or nucleus size, or the duration of the cell cycle. These changes in DNA quantity have been related to variations in the biomass content, breeding season and even the physiological responses of organisms (Swanson et al., 1981; Hartl, 2000).
Artemia is a crustacean that can deploy numerous physiological adaptations; these enable it to tolerate abrupt abiotic changes in the brines inhabited by different species or populations that involve mainly changes in temperature, salinity, ionic concentration and dissolved oxygen. Such changes are driven by the high evaporation rate or the rain regime (Gajardo and Beardmore, 2012). Among the adaptations developed by Artemia to tolerate abiotic changes are a high osmoregulatory capacity, the efficient utilization of dissolved oxygen and the conditional switch in offspring quality between cyst (oviparous reproduction) and nauplii (viviparous reproduction) depending on unfavorable and favorable environmental conditions, respectively. Although most of these adaptive traits have a relatively well-known physiological and molecular basis (Gajardo and Beardmore, 2012), changes in heterochromatin could be another factor in the Artemia repertory adopted to withstand extreme conditions. This has been mentioned in other animal and plant studies, where some of their ecological features are associated with variation in the heterochromatin content (Walker et al., 1991; Ceccarelli et al., 1992, 2002).
In this study the interphase heterochromatin content in different American Artemia populations belonging to the A. franciscana and A. persimilis species were determined through the analysis of interphase nuclei from nauplii cells. This parameter was related to variations in nucleus size in order to explore the existence of nucleotypic changes. We also investigated the relationship of these heterochromatic changes with the ionic composition of the brines inhabited by these populations as a proxy of their adaptive nature.
2. Material and Methods
2.1. Populations studied
Twelve populations of Artemia from different locations in America were analysed: Salina la Colorada Chica (SCC, Argentina), Laguna Amarga-Torres del Paine (TPA, Chile), Laguna de Los Cisnes (CIS, Chile), San Francisco Bay-1258 (SFB, USA), Great Salt Lake (GSL, USA), Salar de Llamara (LLA, Chile), Chaxas (CHX, Chile), La Rinconada (RIN, Chile), Palo Colorado-Los Vilos (LVI, Chile), Salinas de Pichilemu (PCH, Chile), Rio Grande (RGB, Brazil), and Macao (MAC, Brazil) (as shown in Table 1). The populations from the United States (SFB and GSL) and Argentina (SCC), A. franciscana and A. persimilis, respectively, were used as reference species (Gajardo et al., 2001). According to previous studies (Colihueque and Gajardo, 1996; Papeschi et al., 2000; Gajardo et al., 2001), the chromocenter numbers of the remaining populations from Chile (n = 7) and Brazil (n = 2), are known to vary. The Chilean populations were obtained from laboratory cultures originating from live, wild animals.
2.2. Obtaining interphase nuclei
The interphase nuclei were obtained from nauplii by the squash method following the Colihueque and Gajardo (1996) protocol. Larvae were collected either from newly hatched cysts incubated in artificial seawater or from offspring of natural crosses of adults reared in the laboratory under standardised conditions of salinity (35%), temperature (~22 [degrees]C) and light (~1000 lux). The chromocenters of the nuclei were stained using a fluorescent dye (Hoechst 33258) which displays a high affinity for interphase heterochromatic regions (Latt and Wohlled, 1975). The nuclei were photographed at 1000x using a 7 mpx digital camera mounted on an epifluorescence Nikon Labophot microscope. Before taking the photographs, excitation of the fluorochrome was undertaken with UV light through an appropriate filter (UV-2A, 330-380 nm). Five nuclei of each nauplii were photographed at random, totaling from 20 to 58 nuclei per population.
2.3. Heterochromatin quantification in the interphase nuclei
We use a computer-based image analysis to accurately determine the amount of interphase heterochromatin. This method permits increased objectivity, since it can register the totality of the heterochromatin distributed in the nucleus, regardless of its number, size, shape and associations. In this context, the interphase heterochromatin content was estimated using the IMAGEJ version 1.38 software (National Institute of Health, Bethesda, USA). The "count particles" function of the program was used to determine the following parameters: 1) chromocenter number per nucleus (N-CHR) and 2) relative area, as a percentage of the chromocenters per nucleus (R-CHR), representing a relative assessment of interphase heterochromatin. All the analyses were undertaken in grayscale, that fluctuates between 0 and 255 (where 0 = black and 255 = white), whereby a chromocenter was defined as any nuclear structure below the 150 threshold of the grayscale (intense black) and a size above 50 pixels. The relative area (RA) filled by chromocenters in the nucleus was calculated using the formula: RA = (AC/TA) x 100, where AC corresponds to the area covered by the chromocenters in pixels, and TA was the total area of the nucleus in pixels. The nucleus size (S-NUC) was established using the formula for the area of a circumference A = [pi] [r.sup.2], where A is the final area in [micro][m.sup.2] and r is the radius of the nucleus. The absolute diameter of the nucleus was determined using a reference scale incorporated into a micrometer ocular with 0.5 pm sensitivity. The scale bar was subsequently used to calibrate the actual diameter of each nucleus with the SIGMASCAN PRO 5.0 program (Systat software Inc., Chicago, USA), using the image size calibration function.
2.4. Ionic composition of brines
The ionic concentration of brines for SCC, TPA, CIS, SFB, GSL, LLA, RIN, LVI, and PCH populations (as shown in Table 2) was obtained from previous studies (Clarke, 1924; Adams, 1964; Stube et al., 1976; Post, 1980; Gomez-Silva et al., 1990; Amat et al., 1994; Schalamuk et al., 1999; Zuniga et al.,1999; Campos et al., 1996; Lopez et al., 1996; Ruiz et al., 2007; Jones et al., 2009; de Los Rios and Soto, 2009; de Los Rios and Salgado, 2012). Although such conditions are obviously particular to the year and season, it is assumed they represent the water composition of that particular site, depending on their marine (Athalassohaline) or inland (Thalasohaline) characteristics. In order to compare all sites, the values were represented in a Piper's diagram (Piper, 1944), using the DIAGRAMMES program, version 6.1 (Laboratoire d'Hydrogeologie, University of Avignon, Avignon, France). This method displays specific cations ([Ca.sup.2+], [Mg.sup.2+], [Na.sup.+], [K.sup.+]) and anions (HC[O.sub.3.sub.-], C[O.sub.3.sub.2-], [Cl.sup.-], S[O.sub.4.sub.2-]) as a percentage of the total cations and anions, respectively, in a trilinear diagram. Thus, chemically similar waters are grouped in the same position, as follows: a) waters containing sulphate and/or chloride, rich in calcium or magnesium; b) waters containing bicarbonate, rich in calcium or magnesium; c) waters containing chloride and/or sulphate, rich in sodium; and d) waters containing bicarbonated sodium. The percentage of each ion (as shown in Table 2) was calculated based on its value in meq/L, using the following formula: percentage of the ion X = (([SIGMA] meq/L of total ions in water/meq/L ion X) x 100.
2.5. Statistical analyses
The data obtained from the different populations was subject to a two-way analysis of variance (ANOVA), followed by a Tukey's multiple comparison test to carry out a post hoc pairwise comparison of means. Pearson's product-moment correlation analysis was applied to establish the following associations: 1) N-CHR vs. R-CHR; and 2) R-CHR vs. S-NUC. The correlations between R-CHR and percentage of a particular ion were established for the following ions: [Cl.sup.-], S[O.sub.4.sub.2-], [Na.sup.+], [K.sup.+], [Ca.sup.2+] y [Mg.sup.2+]. The significance of correlations was calculated through a Student's t-test. The same statistical test was used to calculate differences between means. The STATISTICA program, version 5.1 (Statsoft, Inc., Tulsa, USA) was used to undertake these analyses.
3. Results
The interphase nuclei from nauplii cells, which display the chromocenters observed in the 12 populations studied, are shown in Figure 1. Quantification of these heterochromatic areas per nucleus indicated that the mean N-CHR values varied widely and significantly among populations (ANOVA, [F.sub.[11,440]] = 31.08, p<0.001), from 0.81 [+ or -] 1.17 to 12.58 [+ or -] 3.78 (as shown in Table 3), with a variation index of 15.5 fold. Thus, there were populations whose means were low (SCC), medium (CHX, LLA, LVI, PCH) or high (RIN, CIS, RGB, MAC, SFB, GSL, TPA). In 30 out of 66 pairwise comparisons, differences in means were statistically significant (Tukey's test, p<0.05). The analysis of this parameter at species level also indicated significant variation among populations for A. franciscana (ANOVA, [F.sub.[8,304] = 10.94, p<0.001) and A. persimilis (ANOVA, [F.sub.[2,136]] = 152.52, p<0.001). With regard to the reference populations, the mean N-CHR in the SFB population (A. franciscana) was significantly higher than in the SCC population (A. persimilis) (10.54 [+ or -] 3.55 vs. 0.81 [+ or -] 1.17, Student's t-test, p<0.05). The mean N-CHR obtained in previous studies (as shown in Table 1) revealed less chromocenters (two to seven) in some populations, in contrast to the result found in this study, such as the LLA and LVI populations.
The mean R-CHR values also varied significantly among populations (ANOVA, [F.sub.[11,440]] = 115.05, p<0.001), from 0.19 [+ or -] 0.34% to 11.78 [+ or -] 3.71%, but with a higher level of variation (62 fold) than the N-CHR parameter. Within this distribution, populations presented mean values that were grouped into low (SCC), medium (CHX, LLA, LVI, RGB, PCH), or high (RIN, MAC, SFB, CIS, GSL, TPA) categories (as shown in Table 3). The pairwise comparison of means for the R-CHR parameter indicated that 50 out of 66 had significant differences (Tukey's test, p<0.001). The result of this parameter at species level also indicated significant variation among populations for A. franciscana (ANOVA, [F.sub.[8,304] = 49.74, p<0.001) and A. persimilis (ANOVA, [F.sub.[2,136]] = 297.07, p<0.001). In the case of the reference populations, mean R-CHR in the SFB population was significantly higher than in the SCC population (8.34 [+ or -] 3.32% vs. 0.19 [+ or -] 0.34%, Student's t-test, p<0.05). The mean N-CHR among A. franciscana and A. persimilis did not differ significantly (9.19 [+ or -] 4.03 vs. 8.95 [+ or -] 5.55, Student's t-test, p>0.05). However, the mean R-CHR was significantly lower in A. franciscana than in A. persimilis (4.59 [+ or -] 3.21 vs. 8.31 [+ or -] 5.76, Student's t-test, p<0.05).
The mean S-NUC values ranged from 155.43 [+ or -] 88.32 [micro][m.sup.2] to 372.32 [+ or -] 160.03 [micro][m.sup.2]. The mean differences among populations were statistically significant (ANOVA, [F.sub.[11,440]] = 19 67, p<0.001), but only 23 out of 66 pairwise comparisons were significant (Tukey's test, p<0.05). At species level, this parameter also indicated significant variation among populations for A. franciscana (ANOVA, [F.sub.[8,304]] = 21.26, p<0.001) and A. persimilis (ANOVA, F[[.sub.2,136]] = 5.53, p<0.01). In addition, the S-NUC parameter, showed much less variation than the R-CHR parameter according to the variation index (2.39 vs. 62 fold). The mean S-NUC was significantly higher in A. franciscana than in A. persimilis (253.94 [+ or -] 125.10 [micro][m.sup.2] vs. 205.76 [+ or -] 90.48 [micro][m.sup.2], Student's t-test, p<0.05).
According to the regression analysis (as shown in Table 4), there was a positive and significant relationship between N-CHR and R-CHR in eight out of 12 populations (r = 0.297-0.792, Student's t-test, p<0.05,). All populations pooled exhibited a significant correlation between both parameters (r = 0.641, Student's t-test, p<0.05). This pattern was also observed for populations of A. franciscana (r = 0.525, Student's t-test, p<0.05) and A. persimilis (r = 0.807, Student's t-test, p<0.05). The coefficient of determination ([r.sup.2] = 0.41) in the relationship of pooled data revealed that only 41% of R-CHR was determined by N-CHR, reflecting a low level of determination between both parameters. Likewise, there was a significant association between R-CHR and S-NUC in five out of 12 populations (Student's t-test, p<0.05), either negative, in four populations (CHX, r = -0.643; RIN, r = -0.464; RGB, r = -0.443; PCH, r = -0.540), or positive, in one population (CIS, r = 0.367). All populations pooled showed a negative and not statistically significant association (r = -0.032, Student's t-test, p>0.05) between both parameters. A similar pattern was observed for populations of A. franciscana (r = -0.009, Student's t-test, p>0.05) and A. persimilis (r = -0.005, Student's t-test, p>0.05).
Piper's diagram (see Figure 2) grouped populations studied into two classes according to the predominant ions in each location: 1) waters containing sodium and/or chloride such as SCC, LLA, RIN, LVI, PCH, SFB and GSL populations; and 2) water with irregular ionic composition, represented by TPA and CIS populations, where the maximum percentage of S[O.sub.4.sub.2-] was relatively high (23-67%). With regard to the correlation between the ion concentration of each location and R-CHR (as shown in Table 5), the pooled data indicated a positive and significant association (Student's t-test, p<0.05) for the [Mg.sup.2+] ion and negative and significant association (Student's t-test, p<0.05) for the [Cl.sup.-], Na+ and [Ca.sup.2+] ions. At species level, this analysis indicated that there were different associations for some ions, particularly, the S[O.sub.4.sub.2-] and [Ca.sup.2+] ions displayed negative and significant correlations in A. franciscana, in contrast to A. persimilis.
4. Discussion
Analysis of the interphase heterochromatin in Artemia has been based mostly on counting the number of chromocenters using visual methods. Despite the taxonomic value attributed to this cytogenetic trait (Gajardo et al., 2001), some authors have stated that these studies have probably been subject to considerable experimental error (Papeschi et al., 2008). This situation may occur due to following sources of error: 1) the chromocenters tend to merge in the interphase nucleus, and thus the actual chromocenter number counted in different nuclei might differ; 2) the chromocenter counts are often carried out regardless of size, thus small chromocenters may be compared to large ones, despite the fact that the former may have less heterochomatin than the latter; this situation leads to a misinterpretation of the amount of heterochromatin present in the nucleus; and 3) some researchers may exclude the tiny chromocenters on the final count, based on a subjective decision. To address this problem, we included the determination of the relative amount of heterochromatin per nucleus in this study (i.e. R-CHR parameter), to ensure more reliable heterochromatin quantification in the nucleus. Indeed, large interpopulation differences were observed in the mean percentage of heterochromatin per nucleus, compared to the traditional method based on counting the number of chromocenters (62 fold vs. 15.53 fold), which confirms the robustness of this methodology. In other species, such as Arabidopsis (Soppe et al., 2002), a similar strategy has been adopted to improve the quality of this analysis.
The relationship between the percentage of interphase heterochromatin per nucleus and nuclear size showed no significant associations at species level. However, our results indicate that, in some cases, significant associations occur at a population level. For example, CHX, RIN, PCH and RGB populations exhibited a significant reduction in nuclear size associated with an increase in the amount of interphase heterochromatin, while the opposite was observed for the CIS population. This finding suggests the existence of a nucleotypic effect in Artemia from the Americas, mediated by variation in the amount of heterochromatin present in the nucleus. However, the effect would be specific to certain populations. It is important to note that the natural habitats of these population may vary widely throughout the year, for example, in temperature (18-29.8 [degrees]C for RIN) (Gomez-Silva et al., 1990) and salinity (30-120 ppt for PCH) (Gajardo et al., 1998). Therefore, the associations observed between both parameters may reflect their adaptations to particular ecological conditions. On the other hand, the results showing reduction in nucleus size to be negatively correlated with heterochromatin content appears intriguing, although this effect has recently been demonstrated (Wang et al., 2013) in another organism, specifically in the Arabidopsis mutant Crowded Nucleus (CRWN). In the case of increasing nuclear size, the evidence available in animals and plants has revealed a positive correlation, although mainly with nuclear DNA content (Swanson et al., 1981; Jovtchev et al., 2006).
The strong and positive association between the content of interphase heterochromatin and magnesium concentration in the brine sites is a significant result. In other words, heterochromatin variation would induce changes that extend from the cell to the organism level, expressed as the differential ability to survive in brines with different ionic composition. Although this effect must be substantiated in further studies, especially relating the actual ion composition of the brine to the moment when samples of Artemia are obtained, this is a plausible working hypothesis worthy of future study. The two populations (TPA and CIS) considered in this study, located in Chilean Patagonia (below latitude 50[degrees] S) are atypical for Artemia standards (Clegg and Gajardo, 2009). According to data previously collected (Campos et al., 1996; Zuniga et al., 1999; De Los Rios and Soto, 2009), both hypersaline sites would differ from the traditional description of environments classified as Athassalohaline (inland waters) and Thassalohaline (marine waters). For instance, magnesium content (9.85-46.35%) is considerably higher (up to 2.5 times) than that of sea water. Despite the fact that the adaptive role of heterochromatin might still be considered controversial, evidence now available indicates that its role in the cellular function cannot be ignored, for example, this element is involved in the stabilization of the chromosome structure, chromosome segregation and gene silencing (Grewal and Jia, 2007). Furthermore, variation in heterochromatin content has been associated with the particular distribution of the species in response to divergent environments (Walker et al., 1991; Ceccarelli et al., 1992, 2002), or with the biomass level of the organisms (Edelman and Lin, 1996). Previous studies showing a latitudinal variation in chromocenter numbers in A. franciscana would be an indirect indication of such heterochromatin abilities (Gajardo et al., 2001). In fact, the Artemia used in this study, collected from Torres del Paine, present a larger relative heterochromatin content in the nucleus than that of the other populations analysed. Clarification of this paradox requires further analysis, but a preliminary hypothesis would be that particular environmental and water conditions may have effectively selected particular genomic and phenotypic features for this population. For instance, cyst size of this population, larger than that of other Chilean populations, appears to be associated with the particular ionic composition of the water in this site (Castro et al., 2006). In addition, analysis of the association between amount of interphase heterochromatin and the ionic concentration of the brines revealed a species-specific negative association with the sulphate and calcium ions, only in the case of A. franciscana. Given that the brine habitats of populations of this species are mainly Thassalohaline waters, whose ionic composition is characterized as being rich in chloride and sodium and poor in sulphate and calcium ions (a result that was confirmed by the Piper's diagram), this association could be explained by the scarce presence of these ions in their natural habitats.
The result indicating interspecific or interpopulation differences in the relative amount of interphase heterochromatin found in Artemia is significant. The origin of this variation may have other causes, such as difference in genome size, or the particular evolutionary process of the karyotype. In the case of differences in genome size, greater amount of heterochromatin is expected in species with a large genome size than in those with a smaller genome size, a pattern that has been demonstrated in evolutionary closely related organisms (Rayburn et al., 1985; Kao et al., 2001; Bosco et al., 2007). Although this hypothesis is interesting, to date it is not possible to contrast Artemia species, since data is only available for the genome size of A. franciscana, reaching a value of 0.97 pg per haploid genome (De Vos et al., 2013). Differences in the evolutionary process of the karyotype could also be taken into account given that A. franciscana appears to be at more advanced stage of evolution than A. persimilis (Parraguez et al., 2009). Thus, it is expected that the former would accumulate more heterochromatin in the chromosomes than the latter. With the exception of the TPA and CIS populations of A. persimilis, which presented large amounts of interphase heterochromatin, most populations of both species studied followed this pattern. Hence in our case, this hypothesis seems to be consistent.
According to the evidence available in Arabidopsis, nuclear changes induced by heterochromatin cannot be ruled out, given the identification of various genes that specifically control such processes (Fransz et al., 2003; Wang et al., 2013). For example, in the ddml mutant, it is observed that the heterochromatin content is significantly reduced in the nucleus (-30%) in comparison to the wild type. This is reflected at the cytological level in lower chromocenter numbers with small sizes. Likewise, in the CRWN4 mutant the chromocenters are notoriously disorganized or dispersed when compared to those observed in a normal nucleus. Based on these cytological patterns, it is possible to classify the organization of the nucleus in Arabidopsis according to the appearance of chromocenters, either as adispersed phenotype (CRWN4 mutant) or as acompact phenotype (wild type). It is important to note that the arrangement of chromocenters in the nucleus of some Artemia populations analysed in this study may match these phenotypes. For example, LLA, CHX and RGB populations would represent a dispersed chromocenter phenotype, while LVI population would correspond to a compact chromocenter phenotype (see Figure 1). Thus, we cannot discard the possibility that these phenotypes may reflect the existence of a particular organizational process of the heterochromatin in the nucleus, across different Artemia populations, whose control may depend on the action of specific genes. In addition, chemical and physical factors may also be involved in the packing status of the chromocenters in Artemia populations, given that natural populations of this organism may be subject to many abiotic stressors, such as changes in temperature, ionic composition and salinity (Gajardo and Beardmore, 2012). Although the participation of these factors has not generally been demonstrated in Artemia, experimental data collected in other organisms reveals their existence. For instance, in NIH 3T3 mouse cells treated with valproic acid produce decondensation in the chromatin structure of the nucleus, including the heterochromatin areas (Felisbino et al., 2014); while in Malpighian tubule cells of the blood-sucking insect, Triatoma infestans, heterochromatin decondensation occurs either after treatments with heavy metals (copper and mercury) or heat shocks (Mello et al., 1995, 2001). Moreover, heterochromatin decondensation after heat shock treatements in Malpighian tubule cells of a vector of Chagas' disease in Brazil, Panstrongylus megistus, infected and non-infected by Trypanosoma cruzi, has been also reported (Garcia et al., 2011). In our case we believe that such factors would not have affected the results obtained since the samples analysed are from laboratory cultures that were kept under standardised conditions of temperature and salinity. However, the chemical or physical factors that might be affecting the condensation of heterochromatin in the interphase nucleus in natural populations of Artemia emerge as an interesting topic for future studies.
Further studies on heterochromatin in Artemia aimed at providing more in depth information about its organization and structure may help to clarify the biological meaning of variation across populations. This type of analysis may contribute additional insight into the source of variation in the interphase heterochromatin, both at intraspecific and interspecific levels in Artemia.
5. Conclusion
The amount of interphase heterochomatin per nucleus that was estimated based on chromocenter number and relative area of chromocenter, in A. franciscana (n = 9) and A. persimilis (n = 3) populations from different locations of the Americas, varied significantly both within and between species. The relationship between relative area of chromocenter and nuclear size revealed a significant association, either negative or positive, in five out of twelve populations analysed. All populations pooled or categorised by species did not show a statistically significant association between both parameters. There was a significant association between relative chromocenter area and ionic concentrations of natural brines in the populations studied, with a positive correlation for magnesium and negative correlations for chloride, sodium and calcium. When populations were categorised by species, a negative and significant correlation with sulphate and calcium ions was found for A. franciscana. These findings suggest the existence of a nucleotypic effect on nuclear size in some populations of Artemia from the Americas, mediated by the variation in the amount of interphase heterochromatin of the nucleus. Moreover, the association of this parameter with the ionic composition of natural brines suggests that it could be involved in the ability of this organism to survive in these environments, which are habitually subject to strong physicochemical changes.
http://dx.doi.org/10.1590/1519-6984.02516
Acknowledgements
The suggestions and constructive comments of all those who helped to improve the final version of this manuscript, are gratefully acknowledged. Reference samples of A. franciscana and A. persimilis were provided by the Artemia Reference Center, Ghent, Belgium. The English language editing of the manuscript by Susan Angus, is also appreciated. The authors are indebted to Dr P.M. Galetti Jr for kindly reviewing the Resumo in Portuguese. This study was financed by Direccion de Investigacion of the Universidad de Los Lagos, project R03/11.
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M. Parraguez (a), *, G. Gajardo (a)
(a) Laboratorio de Genetica, Acuicultura and Biodiversidad, Departamento de Ciencias Biologicas y Biodiversidad, Universidad de Los Lagos, Av. Alcalde Fuchslocher, 1305, PO Box 933, Osorno, Chile
* e-mail: mparraguez@ulagos.cl
Received: February 26, 2016--Accepted: April 30, 2016--Distributed: August 31, 2017 (With 2 figures)
Caption: Figure 1. The interphase nuclei of nauplii cells, displaying the chromocenters stained by Hoechst 33258 fluorescent dye (bright bodies) observed in the 12 studied population of Artemia. Populations: (a) Salina la Colorada Chica (SCC), (b) Laguna Amarga-Torres del Paine (TPA), (c) Laguna de Los Cisnes (CIS), (d) San Francisco Bay-1258 (SFB), (e) Great Salt Lake (GSL), (f) Salar de Llamara (LLA), (g) Chaxas (CHX), (h) La Rinconada (RIN), (i) Palo Colorado-Los Vilos (LVI), (j) Salinas de Pichilemu (PCH), (k) Rio Grande (RGB) and (l) and Macao (MAC). Bar represent 5 gm.
Caption: Figure 2. Piper's diagram displaying ionic concentration (%) of brine waters of nine American Artemia populations studied in this work. The populations were the following: Salina la Colorada Chica (SCC), Laguna Amarga Torres del Paine (TPA), Laguna de Los Cisnes (CIS), San Francisco Bay (SFB), Great Salt Lake (GSL), Salar de Llamara (LLA), Palo Colorado Los Vilos (LVI), La Rinconada (RIN) and Salinas de Pichilemu (PCH). Antofagasta (ANT) sample was included in the analysis as reference of sea water.
Table 1. List of Artemia populations analysed in this study. Location,
geographic coordinates and mean chromocenter number previously
reported is shown.
Population Country Code Species
1. Salina la Colorada Chica Argentina SCC A. persimilis
2. Laguna Amarga-Torres del Paine Chile TPA A. persimilis
3. Laguna de Los Cisnes Chile CIS A. persimilis
4. San Francisco Bay-1258 USA SFB A. franciscana
5. Great Salt Lake USA GSL A. franciscana
6. Salar de Llamara Chile LLA A. franciscana
7. Chaxas Chile CHX A. franciscana
8. La Rinconada Chile RIN A. franciscana
9. Palo Colorado-Los Vilos Chile LVI A. franciscana
10. Salinas de Pichilemu Chile PCH A. franciscana
11. Rio Grande Brasil RGB A. franciscana
12. Macao Brasil MAC A. franciscana
Population Geographic Mean
coordinates chromocenter
number
reported (a)
1. Salina la Colorada Chica 38[degrees]22'46"S 1.0
63[degrees]25'43"W
2. Laguna Amarga-Torres del Paine 50[degrees]58'32"S 17.7
72[degrees]44'57"W
3. Laguna de Los Cisnes 53[degrees]10'35"S 7.0
70[degrees]19'41"W
4. San Francisco Bay-1258 37[degrees]32'53"N 16.8
122[degrees]13'41"W
5. Great Salt Lake 41[degrees]6'56"N 9.0t
112[degrees]28'36"W
6. Salar de Llamara 21[degrees]21'00"S 13.8
69[degrees]35'56"W
7. Chaxas 23[degrees]17'6"S NA
68[degrees]10'37"W
8. La Rinconada 23[degrees]26'21"S 9.5[dagger]
70[degrees]30'20"W
9. Palo Colorado-Los Vilos 32[degrees]4'27"S 9.9
71[degrees]29'38"W
10. Salinas de Pichilemu 34[degrees]30'5"S 6.7
71[degrees]59'4"W
11. Rio Grande 5[degrees]06'00"S 10.1
36[degrees]16'00"W
12. Macao 5[degrees]05'51"S 9.6
36[degrees]38'40"W
(a) According to Gajardo et al. (2001); [dagger] Papeschi et al.
(2008); [double dagger] Unpublished data from Laboratorio de Genetica,
Acuicultura and Biodiversidad, Universidad de Los Lagos.
Table 2. Ionic concentration and the transformation to percentages of
brine waters inhabited by Artemia populations from the Americas
according to previous studies.
Ionic composition
Country Population [Cl.sup.-] S[O.sub.4.
sup.2-]
mg/L % mg/L %
[section]
Argentina see 174,000 94.69 13,020 5.24
Argentina see 173,597 95.27 11,500 4.67
Chile TPA 14,600 46.30 22,900 53.70
Chile TPA 8,960 25.31 26,000 54.32
Chile TPA 9,650 25.78 26,600 52.55
Chile TPA 12,263 55.25 374 1.25
Chile TPA 12,264 57.54 330 1.15
Chile TPA 8,290 51.25 389 1.78
Chile TPA 9,466 46.73 673 2.46
Chile TPA 17,020 25.86 60,380 67.86
Chile CIS 11,700 55.71 6,770 23.84
Chile CIS 12,900 59.06 6,780 22.96
Chile CIS 5,693 74.30 73 0.71
USA SFB 179,200 89.14 29,530 10.86
USA GSL 111,100 90.85 14,850 8.98
USA GSL 177,600 91.49 21,540 8.21
USA GSL 181,000 89.78 27,000 9.90
USA GSL 718,000 92.06 8,000 7.59
Chile LLA 134,722 76.35 56,256 23.58
Chile LLA 37,451 72.40 19,200 27.45
Chile LLA 29,302 74.18 13,632 25.52
Chile LLA 43,600 77.17 17,440 22.83
Chile RIN 152,780 88.49 26,880 11.51
Chile LVI 23,480 89.70 3,550 10.03
Chile LVI 53,300 90.23 7,580 9.49
Chile LVI 53,300 90.10 7,600 9.50
Chile PCH 121,958 96.44 6,091 3.56
Chile PCH 54,780 90.23 7,690 9.37
Sea water ANT 54,840 90.20 7,710 9.38
[dagger]
Ionic composition
Country Population [Na.sup.+] [K.sup.+]
mg/L % mg/L %
Argentina see 108,340 94.32 1,110 0.57
Argentina see 111,600 93.75 4,156 2.06
Chile TPA 27,300 84.01 1,390 2.52
Chile TPA 19,000 81.11 1,868 4.70
Chile TPA 21,900 81.79 1,930 4.25
Chile TPA 580 23.14 95 2.24
Chile TPA 5,330 54.57 35 0.21
Chile TPA 10,240 74.13 109 0.47
Chile TPA 25 0.70 106 1.78
Chile TPA 34,160 82.64 2,250 3.21
Chile CIS 15,500 87.42 430 1.43
Chile CIS 16,300 89.06 324 1.04
Chile CIS 4,119 80.08 129 1.48
USA SFB NA NA NA NA
USA GSL NA NA NA NA
USA GSL 101,450 81.86 4,140 1.97
USA GSL 105,400 80.64 6,700 3.02
USA GSL 41,100 81.80 2,300 2.70
Chile LLA 107,042 95.18 3,094 1.62
Chile LLA 31,013 92.58 914 1.61
Chile LLA 23,513 91.93 737 1.70
Chile LLA 35,810 92.67 2,130 3.25
Chile RIN 75,120 78.65 2,780 1.72
Chile LVI 12,750 75.31 410 1.43
Chile LVI 32,480 77.48 1,320 1.86
Chile LVI 32,500 77.46 1,300 1.83
Chile PCH NA NA NA NA
Chile PCH 31,380 78.29 1,100 1.62
Sea water ANT 29,850 77.38 1,090 1.67
[dagger]
Ionic composition
Country Population [Ca.sup.2+] [Mg.sup.2+]
mg/L % mg/L %
Argentina see 500 0.50 2,800 4.61
Argentina see 857 0.83 2,112 3.36
Chile TPA 20 0.07 2,300 13.40
Chile TPA 6 0.03 1,752 14.16
Chile TPA 6 0.03 1,971 13.93
Chile TPA 2 0.09 987 74.54
Chile TPA 55 0.65 2,300 44.57
Chile TPA 7 0.06 1,850 25.35
Chile TPA 0 0.00 1,816 37.51
Chile TPA 330 0.92 2,089 13.23
Chile CIS 11 0.07 1,038 11.08
Chile CIS 7 0.05 952 9.85
Chile CIS 16 0.37 491 18.07
USA SFB NA NA NA NA
USA GSL NA NA NA NA
USA GSL 300 0.28 10,400 15.89
USA GSL 300 0.26 11,100 16.08
USA GSL 189 0.43 4,000 15.07
Chile LLA 332 0.34 1,700.4 2.86
Chile LLA 441 1.51 759.4 4.29
Chile LLA 836 3.76 352.8 2.61
Chile LLA 450 1.34 560 2.74
Chile RIN 730 0.88 9,460 18.75
Chile LVI 380 2.58 1,860 20.38
Chile LVI 1,260 3.46 3,810 17.21
Chile LVI 1,300 3.56 3,800 17.15
Chile PCH NA NA NA NA
Chile PCH 1,210 3.47 3,520 16.62
Sea water ANT 1,220 3.64 3,530 17.32
[dagger]
Country Population
Argentina see Schalamuk et al. (1999)
Argentina see Ruiz et al. (2007)
Chile TPA Unpublished data [double dagger]
Chile TPA Unpublished data [double dagger]
Chile TPA Unpublished data [double dagger]
Chile TPA Campos et al. (1996)
Chile TPA Campos et al. (1996)
Chile TPA Campos et al. (1996)
Chile TPA Campos et al. (1996)
Chile TPA Zuniga et al. (1999)
Chile CIS Unpublished data [double dagger]
Chile CIS Unpublished data [double dagger]
Chile CIS de Los Rios and Soto (2009)
USA SFB Clarke (1924)
USA GSL Adams (1964)
USA GSL Stube et al. (1976)
USA GSL Post (1980)
USA GSL Jones et al. (2009)
Chile LLA Lopez et al. (1996)
Chile LLA Lopez et al. (1996)
Chile LLA Lopez et al. (1996)
Chile LLA Zuniga et al. (1999)
Chile RIN Gomez-Silva et al. (1990)
Chile LVI Amat et al. (1994)
Chile LVI Zuniga et al. (1999)
Chile LVI de Los Rios and Salgado (2012)
Chile PCH Unpublished data [double dagger]
Chile PCH Zuniga et al. (1999)
Sea water ANT Zuniga et al. (1999)
[dagger]
[section] The percentage of each ion was calculated based on its value
in meq/L, using the following formula: percentage of the ion X =
(([sigma] meq/L of total ions in water/meq/L ion X) x 100; [dagger]
Data from .Antofagasta (northern Chile) was included as reference of
sea water; [double dagger] Data from Laboratorio de Genetica,
Acuicultura and Biodiversidad, Universidad de Los Lagos.
Table 3. Summary of the interphase heterochromatin content and nucleus
size parameters (mean [+ or -] SD) in Artemia populations.
Population Species No. of N-CHR (n)
nuclei
analysed
(No. of
nauplii)
SCC A. persimilis 32(6) 0.81 [+ or -] 1.17 (a)
TPA A. persimilis 58(7) 12.58 [+ or -] 3.78 (d)
CIS A. persimilis 49(10) 9.95 [+ or -] 3.06 (cd)
SFB A. franciscana 26(5) 10.54 [+ or -] 3.55 (c,d)
GSL A. franciscana 24(8) 11.71 [+ or -] 3.67 (d)
LLA A. franciscana 38(4) 6.83 [+ or -] 4.47 (b)
CHX A. franciscana 20(5) 5.3 [+ or -] 2.36 (a,b)
RIN A. franciscana 41(8) 11.75 [+ or -] 3.14 (d)
LVI A. franciscana 38(5) 7.89 [+ or -] 3.65 (b,c)
PCH A. franciscana 53(5) 8.35 [+ or -] 2.82 (b,c)
RGB A. franciscana 33(4) 9.84 [+ or -] 3.15 (c,d)
MAC A. franciscana 40(3) 10.12 [+ or -] 4.64 (c,d)
Pooled A. persimilis 139(23) 8.95 [+ or -] 5.55 (x)
Pooled A. franciscana 313(47) 9.19 [+ or -] 4.03 (x)
Pooled Both species 452(70) 9.12 [+ or -] 4.54
Variation Across 15.53
index populations
Population R-CHR (%) S-NUC (um2)
SCC 0.19 [+ or -] 0.34 (a) 212.98 [+ or -] 84.05 (a,b)
TPA 11.78 [+ or -] 3.71 (e) 178.02 [+ or -] 61.55 (a)
CIS 9.49 [+ or -] 4.36 (d,e) 233.87 [+ or -] 112.55 (a,b)
SFB 8.34 [+ or -] 3.32 (c,d) 212.53 [+ or -] 60.58 (a,b)
GSL 8.34 [+ or -] 2.51 (e) 300.18 [+ or -] 57.96 (b,c)
LLA 1.89 [+ or -] 0.91 (b) 207.96 [+ or -] 95.42 (a,b)
CHX 2.09 [+ or -] 1.06 (b) 155.43 [+ or -] 88.32 (a)
RIN 6.94 [+ or -] 2.74 (c) 372.32 [+ or -] 160.03 (e)
LVI 2.11 [+ or -] 1.44 (b) 253.57 [+ or -] 68.20 (b)
PCH 3.93 [+ or -] 2.09 (b) 172.54 [+ or -] 42.07 (a)
RGB 2.87 [+ or -] 1.46 (b) 369.41 [+ or -] 164.51 (c,e)
MAC 5.98 [+ or -] 2.82 (c) 237.62 [+ or -] 191.52 (a,b)
Pooled 8.31 [+ or -] 5.76 (x) 205.76 [+ or -] 90.48 (x)
Pooled 4.59 [+ or -] 3.21 (y) 253.94 [+ or -] 125.10 (y)
Pooled 5.74 [+ or -] 4.50 239.12 [+ or -] 117.58
Variation 62.00 2.39
index
Population means in each column bearing different letters are
significantly different from each other (Tukey's test, p< 0.05).
Species means (pooled data) with different letters indicate
significant differences (Student's t-test, p< 0.05). N-CHR=
chromocenter number per nucleus, R-CHR= relative area in percentage of
chromocenter per nucleus, S-NUC = nuclear size.
Table 4. Correlation values between heterochomatin content (N-CHR and
R-CHR) and nucleus size (S-NUC) in Artemia populations.
Population No. of N-CHR vs. R-CHR R-CHR vs. S-NUC
nuclei
analysed
SCC 32 0.792 (0.000) * 0.126 (0.478)
TPA 58 0.032 (0.757) -0.202 (0.123)
CIS 49 0.465 (0.001) * 0.367 (0.009) *
SFB 26 0.335 (0.094) -0.322 (0.107)
GSL 24 0.313 (0.000) * -0.158 (0.282)
LLA 38 0.406 (0.011) * -0.145 (0.364)
CHX 20 0.071 (0.755) -0.643 (0.002) *
RIN 41 -0.063 (0.669) -0.464 (0.002)
LVI 38 0.639 (0.000) * -0.100 (0.546)
PCH 53 0.609 (0.000) * -0.540 (0.000) *
RGB 33 0.442 (0.009) * -0.443 (0.009) *
MAC 40 0.297 (0.008) * -0.235 (0.331)
A. persimilis 139 0.807 (0.000) * -0.005 (0.947)
A. franciscana 313 0.525 (0.000) * -0.009 (0.897)
Pooled 452 0.641 (0.000) * -0.032 (0.407)
Values in brackets are p-values according to Student's t-test; * p <
0.05.
Table 5. Correlation values between ions concentration and
heterochromatin content (R-CHR) in Artemia populations.
Ions
[Cl.sup.-] S[O.sub. [Na.sup.+] [K.sup.+]
4.sup.2-]
A. persimilis
No. of samples 13 13 13 13
Correlation (r) -0.845 0.350 -0.431 0.289
(0.000) ** (0.241) (0.141) (0.338)
A. franciscana
No. of samples 15 15 12 12
Correlation (r) -0.549 -0.546 -0.341 0.537
(0.034) * (0.035) * (0.278) (0.072)
Pooled
No of samples 28 28 25 25
Correlation (r) -0.705 0.276 -0.478 0.233
(0.000) ** (0.155) (0.016) * (0.263)
Ions
[Ca.sup.2+] [Mg.sup.2+]
A. persimilis
No. of samples 13 13
Correlation (r) -0.476 0.419
(0.101) (0.154)
A. franciscana
No. of samples 12 12
Correlation (r) -0.653 0.443
(0.021) * (0.149)
Pooled
No of samples 25 25
Correlation (r) -0.640 0.496
(0.001) ** (0.012) *
Values in brackets are p-values according to Student's t-test; * p <
0.05; ** p < 0.001.
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| Title Annotation: | Original Article |
|---|---|
| Author: | Parraguez, M.; Gajardo, G. |
| Publication: | Brazilian Journal of Biology |
| Date: | Jul 1, 2017 |
| Words: | 9248 |
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