Caryologia. International Journal of Cytology, Cytosystematics and Cytogenetics 77(2): 3-18, 2024 Firenze University Press www.fupress.com/caryologia ISSN 0008-7114 (print) | ISSN 2165-5391 (online) | DOI: 10.36253/caryologia-2672 Caryologia International Journal of Cytology, Cytosystematics and Cytogenetics Citation: Fouroutan, P., Sheidai, M., & Koohdar, F. (2024). The role of chro- mosomal rearrangements, polyploidy, and genome size variation in the diversity and ecological distribution of Asparagus L. species: a landscape cytogenetics meta-analysis approach. Caryologia 77(2): 3-18. doi: 10.36253/ caryologia-2672 Received: April 04, 2024 Accepted: September 21, 2024 Published: November 10, 2024 © 2024 Author(s). This is an open access, peer-reviewed article pub- lished by Firenze University Press (https://www.fupress.com) and distrib- uted, except where otherwise noted, under the terms of the CC BY 4.0 License for content and CC0 1.0 Uni- versal for metadata. Data Availability Statement: All rel- evant data are within the paper and its Supporting Information files. Competing Interests: The Author(s) declare(s) no conflict of interest. The role of chromosomal rearrangements, polyploidy, and genome size variation in the diversity and ecological distribution of Asparagus L. species: a landscape cytogenetics meta-analysis approach Paris Fouroutan1, Masoud Sheidai2,*, Fahimeh Koohdar3 1 Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran 2 Faculty of Life Sciences & Biotechnology, Shahid Beheshti University, Tehran, Iran *Corresponding author. E-mail: msheidai@sbu.ac.ir Abstract. The Asparagus genus includes a group of plants with economic and medici- nal importance. Although numerous cytogenetic and genetic studies have been con- ducted on Asparagus species, there are no reports on landscape genetics, landscape cytogenetics, or Asparagus cultivation in response to climate change. Therefore, we designed this study to answer the above-mentioned objectives. We performed a meta-analysis involving landscape genetic studies based on available cytogenetic data and reported DNA C-values for several Asparagus species from different countries. Additionally, species distribution modeling (SDM) was performed on some selected Asparagus species. This combined study not only identifies the genetic fragmentation and genetic clines within plant species but also predicts their growth and distribu- tion across different regions and in response to climate change. We used discriminant analysis of principal components (DAPC) to group Asparagus taxa based on karyo- type and chromosome pairing data. We also performed random forest (RF) analysis to determine the contribution of cytogenetic traits to Asparagus speciation based on the Gini index. An association study was performed using redundancy analysis (RDA) of cytogenetic data with geographic variables (longitude and latitude). We used spa- tial principal component analysis (sPCA) to analyze the contribution of spatial vari- ables to the cytogenetic structure of the studied Asparagus species. We used Bioclim and Maxent species distribution models (SDMs) to predict and identify areas suitable for selected Asparagus species in response to climate change by 2050. Results indicated that ploidy and chromosome size, the occurrence of heterozygote translocation, fre- quency and distribution of chiasmata, and genome size play role in Asparagus species diversification and adaptation. These cytogenetic characters are significantly associated with spatial variables and Asparagus species formed cytogenetic clines in response to local environmental conditions. SDM analyses showed that a combination of tempera- ture and precipitation factors affect Asparagus species distribution and that in the com- ing future, some of these species may have a reduced cultivation area due to climate change which must be tackled by planning a proper conservation program worldwide. Keywords: Asparagus, cytogenetic clines, genome size, Maxent, RDA. http://www.fupress.com/caryologia https://doi.org/10.36253/caryologia-2672 https://doi.org/10.36253/caryologia-2672 https://doi.org/10.36253/caryologia-2672 https://www.fupress.com https://creativecommons.org/licenses/by/4.0/legalcode https://creativecommons.org/publicdomain/zero/1.0/legalcode mailto:msheidai@sbu.ac.ir 4 Parisa Fouroutan, Masoud Sheidai, Fahimeh Koohdar INTRODUCTION The genus Asparagus contains about 240 species, with Asparagus officinalis L., commonly known as the garden Asparagus as the most famous and economi- cally important species. This edible vegetable crop is cultivated, grown, and used all over the world for its edible spear (Kanno et al. 2011). However, along with garden Asparagus, other species are also cultivated such as Asparagus maritimus L., or have been proposed as a genetic source for breeding programs like Asparagus acutifolius L. Moreover, the young shoots of some wild Asparagus spp. namely, A. acutifolius L., A. aphyllus L., A. acerosus Thunb. ex Schult. & Schult. f., and A. laricinus Burch., are consumed fresh. Similarly, A. verticillatus L. is used for medicinal purposes and A. densiflorus (Kunth) Jes- sop as well as A. plumosus Baker have been grown as ornamental plants (Kubitzki et al. 1998). Polyploidy has been reported in both the garden Asparagus (4x, and 8X), as well as in several species related to garden Asparagus, for example in Asparagus falcatus (2x, and 4x), Asparagus racemosus var. javinica (2x, and 4x), Asparagus maritimus (4x, and 6x) (see for example, Sheidai and Inamdar 2017; Mousavizadeh et al. 2021; Sala et al. 2023). Although numerous cytogenetic and genetic studies have been conducted on Asparagus species, there are no reports on landscape genetics, landscape cytogenetics, or Asparagus cultivation in response to climate change. Therefore, we designed this study to answer the above- mentioned objectives. We used our own cytogenetic data (Sheidai and Inadar 1997) and publicly available cytoge- netic and nuclear DNA quantity data reports (C-value data) (Pires et al. 2006; Bouberta et al. 2017; Suma et al. 2017; Mousavizadeh et al.2021; Plath et al.2022), and performed a meta-analysis in a landscape genetic con- text. Additionally, species distribution modeling (SDM) was performed on some selected Asparagus species. This combined study not only identifies the genetic fragmen- tation and genetic clines within plant species but also predicts their growth and distribution across different regions and in response to climate change. Cytogenetic studies, including chromosome mor- phology and chromosome pairing analysis, are essen- tial for plant breeding, QTL hybridization and molecu- lar mapping, and genetic transfer of beneficial genes between different species and cultivars. Moreover, the frequency and location of recombination through chi- asmata formation can promote adaptation in a spe- cies by creating new genetic combinations (Rice 2002). Recombination can vary within chromosomes, between chromosomes, and between individuals, sexes, popula- tions and species and its proportions can be influenced by environmental and demographic factors (Charles- worth 1976; Rice 2002), but are inherited, maintained, and selected for at specific genetic loci (Chinnici 1971). Moreover, studies across different taxonomic scales have shown that recombination frequency and occupy- ing a particular landscape may be controlled by differ- ent mechanisms in different taxa (Ortiz-Barrientos et al. 2015; Johnston et al. 2016). Landscape genetics considers the genetic basis of diversity in response to spatial variables such as geo- graphic distance, altitude, and latitude (Provost et al. 2022). The frequency and distribution of chiasmata (cross-over) which are genetically controlled, as well as the occurrence of heterozygote translocations, result in genetic variation through chromosome genetic rear- rangement. It is also known that polyploidy is one of the main genetic mechanisms in Asparagus genus speciation (Sheidai and Inamdar 2017). Therefore, landscape genet- ics and species distributions allow for determining the role of global and regional spatial variables as well as climatic variables in the genetic makeup of Asparagus species and potentially suitable growing regions. Species distribution models (SDMs) are methods that study the current geographic distribution of plant species and pre- dict future events in the face of climate change. Through this, suitable habitats for the cultivation of the plant spe- cies of interest can be identified, and conservation meas- ures can be proposed if there is a possibility that the cultivation area of the target plant species will decrease (Elite and Litwick 2009; Lee-Yaw et al. 2021). MATERIAL AND METHODS For landscape cytogenetic studies we used both kar- yotype and chromosome pairing data of 18 Asparagus taxon (Table 1). For genome size analysis we used the freely available published data of Plath et al (2022). For the species distribution modeling (SDM), we used the occurrence data points for the selected Asparagus species from GBIF (the Global Biodiversity Information Facil- ity), as well as the published materials. DATA ANALYSES Cytogenetic grouping We used discriminant analysis of principal compo- nents (DAPC), for grouping of Asparagus taxa for both karyotype and chromosome pairing data. An analysis of 5Chromosomal rearrangements and diversity in Asparagus: a cytogenetics meta-analysis variance (ANOVA) test was performed on the cytogenet- ic data to reveal a significant difference between Aspara- gus species in different countries. We also performed random forest (RF) analysis to reveal the contribution of cytogenetic characters in Asparagus species differentia- tion based on the Gini index. These were performed in the adegenet package of R. 4. 2. Redundancy analysis (RDA) Association studies were performed using redundan- cy analysis (RDA) of cytogenetic data with geographic variables (longitude and latitude). RDA which is a con- strained ordination method models the linear relation- ships between environmental predictors and genetic vari- ation (Capblancq and Forester, 2021). This analysis was performed through 999 permutations in PAST ver. 4. Spatial principal components analysis (sPCA) We used the Spatial principal components analysis (sPCA), to analyse the spatial variables’ contribution to the studied Asparagus species cytogenetic structuring. The sPCA is a multivariate method that is independent of Hardy Weinberg expectations and produces estimates summarizing both genetic variation and spatial structure between individuals (or populations) (Jombart et al.2008). Global structures (patches, wedges, and intermediate junctions) are statistically comparable to local structures (strong genetic differences between neighbors) and ran- dom noise. The sPCA also performs Moran’s I test and IBD (isolation by distance). The sPCA analyses were per- formed with the adegenet package version R. 4. 2. Species Distribution Modeling (SDM) We used species distribution modeling (SDM) to predict and identify suitable regions for selected Aspar- agus species in response to climate change by 2050. In species distribution modeling, we used layers of forecast climate data for the current period (~1950-2000) and 2050 (2050-2061 average) based on 19 bioclimatic vari- ables at a 5-minute resolution. Data was loaded from the WorldClim database. To represent the impact of climate change, future climate variables in 2050 were projected Table 1. Karyotype data of Asparagus species used in present study. Species Country Locality Longitude Latitude 2n Ploidy Total chromatin length Mean chromatin length Shortest chromosome Longest chromosome Ratio A. racemosus var. Javanica-1 India Orissa 84.27 20.23 40 4 66.5 3.325 1.00 2.60 2.60 A. racemosus var. Javanica-2 India Pune-University 73.82 18.55 20 2 38.52 3.852 1.13 2.93 2.59 A. densiflorus cv. Myers India private nursery Pune 73.88 18.51 40 4 78.58 3.929 1.30 2.82 2.16 A. laevissimus India J.N.H-Pune 73.87 18.53 40 4 66.12 3.30 0.91 2.91 3.20 A. myriocladus India Pune-University botanical garden 73.05 18.03 40 4 92.2 4.61 1.00 3.66 3.66 A. racemusus subacerosa India Pune-law college hills 73.82 18.51 40 4 65.2 3.26 1.06 2.26 2.13 A. sprengeri India Agharkar Research Institute 73.50 18.31 40 4 58.82 2.94 1.06 2.47 0.78 A. virgatus India Fergussen college 73.50 18.31 40 4 67.26 3.363 1.12 2.49 2.22 A. gonoclados India Pune 73.05 18.03 60 6 87.38 4.369 1.96 5.30 2.70 A. adsendens India J.N.H-Pune 73.87 18.53 20 2 73.3 7.33 0.99 2.00 2.02 A. falcatus India private nursery Pune 73.88 18.51 20 2 28.48 2.85 1.00 1.99 1.99 A. Officinalis-1 India Fergussen college 73.50 18.31 20 2 85.68 8.57 2.58 5.85 2.27 A. racemosus Bangladesh University of Dhaka 90.39 23.77 20 2 18.18 1.81 0.53 1.23 2.32 A. setaceus Bangladesh Dakha 90.39 23.77 20 2 18.50 1.85 0.48 1.47 3.06 A. albus Algeria Tipaza 2.27 36.25 20 2 44.47 4.44 3.19 6.25 1.95 A. acutifolius Algeria Senalba 3.10 34.38 20 2 52.07 5.2 4.21 6.61 1.57 A. horridus Algeria Emir Khaled 2.12 36.08 20 2 36.04 3.6 2.91 4.46 1.53 A. Officinalis-2 Algeria Tessala El Merdja 2.54 36.37 20 2 51.18 5.11 3.15 6.52 2.06 6 Parisa Fouroutan, Masoud Sheidai, Fahimeh Koohdar according to the “representative concentration trajec- tory” (RCP, 2. 6). We used bioclimatic variables derived from the monthly temperature and rainfall values. These biocli- matic variables are coded as follows: BIO1 = Annual Mean Temperature BIO2 = Mean Diurnal Range (Mean of monthly (max temp - min temp)) BIO3 = Isothermality (BIO2/BIO7) (×100) BIO4 = Temperature Seasonality (standard deviation ×100) BIO5 = Max Temperature of Warmest Month BIO6 = Min Temperature of Coldest Month BIO7 = Temperature Annual Range (BIO5-BIO6) BIO8 = Mean Temperature of Wettest Quarter BIO9 = Mean Temperature of Driest Quarter BIO10 = Mean Temperature of Warmest Quarter BIO11 = Mean Temperature of Coldest Quarter BIO12 = Annual Precipitation BIO13 = Precipitation of Wettest Month BIO14 = Precipitation of Driest Month BIO15 = Precipitation Seasonality (Coefficient of Varia- tion) BIO16 = Precipitation of Wettest Quarter BIO17 = Precipitation of Driest Quarter BIO18 = Precipitation of Warmest Quarter BIO19 = Precipitation of Coldest Quarter To build the SDM model, we used the Bioclim and maximum entropy methods implemented in the Dis- mo package in R 4. 2 and the Maxent program. SDMs require the occurrence data points on which the pseudo- absences (PAs) points are estimated, followed by model prediction. All the models were constructed with 80% training and 20% testing of occurrence data. The model evaluation was performed by both the threshold method and AUC determination (ROC curve). Bioclim models the species distributions in rela- tion to climatic variables and thus assumes that spe- cies occurrence is influenced by climate at the scale of climate variables and that these variables are normally distributed. Similarly, Maxent (Maximum Entropy Mod- eling) predicts the occurrence of a species by finding the one closest to the most common or uniform distri- bution, taking into account the limits of environmental variables in a known location (Phillips et al.2004). I n this method, the fit is measured as gain, which is basi- cally a likelihood statistic that maximizes the probabil- ity of being present for background data adjusted for the case where all pixels have an equal (uniform) probability. The final probability distribution becomes the basis for fitted predictor variable coefficients. (Phillips et al.2004). The importance of bioclimatic variables influencing the distribution of Asparagus species was assessed by the Jackknife incremental method and the AUC value. RESULTS Cytogenetic data based on the country of origin of the Asparagus species used in this study are shown in Tables 2 and 3. An analysis of variance (ANOVA) test performed on the cytogenetic data revealed a significant difference between these countries in karyotype data (p<0.01, Fig. 1). These results demonstrate that genetic variation accompanies Asparagus species diversity in dif- ferent regions of the world. A similar analysis for chiasma frequency and chromosome pairing could be performed on the species studied and not among the countries, but a significant result (p<0.01), indicated the species cytogenet- ic differences even within a particular country i. e. India. Cytogenetic grouping of the studied Asparagus spe- cies based on karyotype data is presented in the DAPC plot (Fig. 2). These species are scattered in three distinct groups based on their country of origin. Association analyses performed by CCA and RDA for karyotype data produced significant results (p<0.01, Fig. Table 2. The mean value for chiasma frequency and distribution, and chromosome pairing in Asparagus species studied. Asparagus species Terminal chiasmata Intercalary chiasmata Total chiasmata Ring bivalents Rod bivalents A. racemosus javanica 14.2 1.3 16 7.3 1.37 A. densiflorus cv. Myers 34.3 2.6 37 17.2 2.4 A. laevissimus 15.8 4 20 8.5 1.48 A. racemusus subacerosa 35.62 0.47 36.1 16.78 2.81 A. sprengeri 39 0.347 39.347 19.26 0.74 A. virgatus 36.1 1.3 37.4 18 1.7 A. gonoclados 55.28 5 60.23 26.84 2.46 A. adsendens 16.8 4.425 21.225 9.8 0.325 A. officinalis 13.8 1.36 14.54 5.54 3.36 7Chromosomal rearrangements and diversity in Asparagus: a cytogenetics meta-analysis 3, A). These results showed an association between ploidy level, the ratio of the longest to the shortest chromosome the somatic chromosome number (2n). Moreover, the random forest result (Fig. 3, B) identified the ploidy level and somatic chromosome number as the main karyotype characters that differentiate the studied taxa. A similar analysis performed on chiasma frequency and chromosome pairing of Asparagus species did not produce significant association (p >0.1). This may be due to the fact that we obtained and used only the meiotic data of Asparagus species from India. Spatial principal components analysis (sPCA) The results of sPCA are presented in Fig. 4, A-F. The preliminary analysis of sPCA Eigenvalues showed the presence of strong positive and global spatial constraints over the cytogenetic characteristics of the studied Aspar- agus species (Fig. 4, A). This was supported by a signifi- cant global test obtained (p= 0.01, Fig. 4, B). Similarly, the isolation by distance test (IBD), pro- duced a significant result (p= 0.01, Fig. 4, D), indicating that cytogenetic differences among Asparagus species increased with increasing geographic distance. The connection network (Fig. 4, E), showed a clos- er relationship (common shared cytogenetic features) between species from India and Bangladesh species, and the cytogenetic clines plot (Fig. 4, F), showed that the species studied in all three countries formed cytogenetic clines probably due to their spatial adaptation. Moreo- ver, Moran’s I test was not significant (p> 0.1), indicating that the similar spatial and geographical regions have similar effects on the studied cytogenetic features. Table 3. The genome size (1C-value) of Asparagus species used in the landscape cytogenetic analyses (data obtained from freely available published paper (Plath et al., 2022)). Species Country Country-code Longitude Latitude Ploidy (X) C-value A. acutifolius Italy, Vittoria 1 14.53 36.95 2 1.35 A. aethiopicus Spain, Malaga 2 4.42 36.71 6 0.86 A. albus Portugal 3 8.22 39.39 2 1.23 A. amarus Italy 1 12.56 41.87 6 1.37 A. arborescens Canary 4 16.62 28.29 2 1.32 A. maritimus 1 Italy 1 12.56 41.87 6 1.33 A. maritimus 2 Italy 1 12.56 41.87 6 1.30 A. maritimus 3 Italy 1 12.56 41.87 6 1.28 A. maritimus 4 Italy, Vign 1 13.04 43.37 6 1.29 A. officinalis ‘Darlise’ France 6 2.21 46.22 2 1.47 A. officinalis ‘Ravel’ Germany 7 10.45 51.16 2 1.53 A. officinalis ‘Steiners Violetta’ Germany 7 10.45 51.16 4 1.59 A. pastorianus Macaronesia 8 16.84 28.23 4 1.40 A. plumosus Cuba 9 82.36 23.11 2 0.42 A. plocamoides Canary 4 16.62 28.29 2 0.71 A. prostratus 1 France, Ploemever 6 3.25 47.44 4 1.48 A. prostratus 2 France, Gavres 6 3.35 47.69 4 1.53 A. prostratus 3 France, Damgan 6 2.57 47.51 4 1.52 A. prostratus 4 France, Houat Is. 6 2.95 47.39 4 1.54 A. pseudoscaber Italy 1 12.56 41.87 6 1.28 A. ramosissimus Angola 10 17.87 11.20 2 1.15 A. scoparius Africa, Cape Verde 11 23.04 16.53 2 0.73 A. stipularis 1 Ibiza 2 1.42 38.90 2 0.81 A. stipularis 2 Ibiza 2 1.42 38.90 2 1.13 A. stipularis 3 Ibiza 2 1.42 38.90 2 1.21 A. stipularis 4 Cyprus 12 33.42 35.12 2 1.19 A. albus Portugal 2 8.22 39.39 2 1.23 A. ramosissimus Angola 2 17.87 11.20 2 1.35 A. stipularis 4 Cyprus 2 33.42 35.12 2 0.86 A. scoparius Africa, Cape Verde 12 23.04 16.53 2 1.23 8 Parisa Fouroutan, Masoud Sheidai, Fahimeh Koohdar Heterozygote translocations Some of the studied Asparagus species showed the occurrence of heterozygote translocations in the pachy- tene stage of meiosis (Fig. 5, A). These translocations would result in multivalent formation in the metaphase stage (Fig. 5, B and C), (Sheidai 1985). Genome size (C-value) analysis The 1C value of the Asparagus species obtained from the published freely available work (Plath et al.2022) and their country of origin with spatial variables (longitude and latitude) are presented in Table 3. ANOVA per- formed on the amount of C-value produced significant results among the Asparagus species studied (p< 0.01, Fig. 6). The RDA analysis (Fig. 7) also showed a signifi- Figure 1. Representative box plots of Karyotypic data ANOVA between Asparagus species based on the countries. (Abbreviations for the country are 1= India, 2=Bangladesh, and 3 = Algeria). 9Chromosomal rearrangements and diversity in Asparagus: a cytogenetics meta-analysis cant association (p= 0.01), and spatial variables. There- fore, the longitudinal as well as latitudinal distribution of Asparagus species analyzed affect the ploidy level and their 1C-value genomic content. The longitude and lati- tude data are in degrees, and minutes, respectively. Spatial principal components analysis (sPCA) of 1C-value data The results of sPCA are presented in Fig. 8, A-D. The preliminary analysis of sPCA Eigenvalues showed the presence of strong positive and global spatial variables over the ploidy level, and the genomic 1C-value content of the studied Asparagus species (Fig. 8, A). This was supported by a significant global test obtained (p =0.10). Similarly, the isolation by distance test (IBD), did not produce a significant result (p= 0.01), indicating that the 1C-value content difference among Asparagus species is not increased with increasing geographic distance. The connection network (Fig. 8, B), showed similari- ties (common shared cytogenetic features) between the species studied in different countries, and the genome size clines plot (Fig. 8, C), showed that the species stud- ied in all these countries formed ploidy and 1C-value content clines due to their spatial adaptation. Moreover, Moran’s I test was not significant (p> 0.1), indicating that the similar spatial and geographical regions have similar effects on the studied cytogenetic features. The contribution plot (Fig. 8, D), revealed that the ploidy level plays a more pronounced role compared to that of 1C-value content in the analyzed Asparagus spe- cies in response to spatial variables. Species distribution modeling (SDM) results SDM analysis of selected Asparagus species provides insight into the climatic variables affecting the growth and occurrence of these important species worldwide and can predict their response to climate change in the future. These findings help conservation programs. The results of present-time predicted distribution versus Asparagus species distribution by the year 2050 are presented in Figs. 9 and 10. The probable distribution of these species under the influence of climate change obtained from both BIOCLIM and Maxent models was almost the same. These results revealed that the area under cultivation for the studied species would be much reduced in extent by the year 2050. This statement holds true, particularly for Asparagus verticillatus. The importance of climatic variables based on the Jackknife method and ROC curve (AUC value) are pre- sented in Fig. 10. The AUC values obtained for both pre- sent time prediction and by the year 2050, were all above 0.90 which supports the modeling results. Important and influential bioclimate variables iden- tified by the Jackknife method revealed that BIO3= Isothermality, BIO5= Max Temperature of Warmest Month, BIO13= Precipitation of Wettest Month, BIO14= Precipitation of Driest Month, BIO15= Precipitation Seasonality, BIO17= Precipitation of Driest Quarter and BIO18= Precipitation of Warmest Quarter, are among the most important bioclimate variables affecting the distribution of Asparagus species. DISCUSSION This study showed that global and local spatial pat- terns influence the genetic structure of Asparagus spe- cies through cytogenetic changes like polyploidy, struc- tural changes of chromosomes (heterozygote translo- cations), chromosome size, and the plant genome size. Moreover, bioclimatic variables determine the geograph- ical distribution of these plants worldwide. Chromosomal evolution has played an important role in plant diversification and speciation, especially in the genus Asparagus (Plath et al. 2022). In the Asparagus genus, Plants with different ploidy levels within the same population are very common. For example, triploid, pen- taploid, hexaploid, and octoploid plants were found in Figure 2. DAPC grouping of Asparagus species based on karyotype data. Abbreviations: 1= India, 2= Bangladesh, and 3 = Algeria. 10 Parisa Fouroutan, Masoud Sheidai, Fahimeh Koohdar Figure 3. A= RDA plot of karyotype data in the studied Asparagus species shows a significant association between ploidy level, longest to shortest chromosome ratio, and somatic chromosome number. B = Random Forest plot of the same data showing the importance of karyo- type characters in differentiating the studied taxa. 11Chromosomal rearrangements and diversity in Asparagus: a cytogenetics meta-analysis Figure 4. Representative sPCA plots of cytogenetic data in the studied Asparagus species. A = Plot of Eigenvalues revealed a strong effect of positive (global) spatial features for the studied taxa (the part shown in red), B-D = Global, local, and IBD test results showed significant p-values in the first two tests. E, and F = The connection and cytogenetic clines plots showed closer relationships between species from India and Bangladesh, with cytogenetic clines formed respectively in all three countries. 12 Parisa Fouroutan, Masoud Sheidai, Fahimeh Koohdar the Spanish landrace ‘Morado de Huetor’ (Moreno et al. 2006). Additionally, Ozaki et al. (2014) discovered spon- taneous triploid Asparagus plants from crosses with dip- loid parents. Mousavizadeh et al. (2021), studied the influence of climate on the geographical distribution of diploid and polyploid Asparagus plants of A. officinalis, A. persicus, A. verticillatus, and A. breslerianus growing in Iran and reported changes in the ploidy levels of vegetation across different zones. These changes are related to humidity, average minimum and maximum temperatures, and soil salinity. They observed that the species with 8X and 10X species live at higher altitudes and are able to adapt to drier and more salinity lands than 2X and 4X plants. The number and shape of plant chromosomes, the amount and composition of nuclear DNA, the frequen- Figure 5. A = A heterozygote translocation (arrow) in Asparagus racemosus sub acesora, B, and C = Multivalent formation (arrows) in Asparagus gonoclados, and A. officinalis, respectively. (Figures are from one of the coauthors i.e. Sheidai 1985, Ph.D thesis) 13Chromosomal rearrangements and diversity in Asparagus: a cytogenetics meta-analysis cy of chiasmata, and the chromosomal meiotic behavior of chromosome pairs vary greatly among plant species. In particular, meiotic behavior is genetically regulated, and changes in the frequency and location of crosso- vers within chromosome arms affect the genetic diver- sity of the offspring (Rees and Jones 1977). Therefore, the existence of significant differences in the chiasmata frequency and distribution, and ring and rod bivalents, among Asparagus species growing in different parts of the world may indicate their genomic differences (Sheid- ai et al. 2002) and may act as the genomic adaptation to environmental variables that have been reported in other plant crops (see for example, Sheidai et al. 2012). Genetic variation can be exploited through local environmental and climatic selection to achieve eco- logical diversity even in the absence of physical barri- ers. Because new beneficial mutations or chromosomal rearrangements are unlikely to accumulate rapidly, it has been suggested that rapid adaptation may involve selec- tion based on persistent genetic variation i. e. the genetic variation present in ancestral populations before diver- gence occurred (Ortiz-Barrientos et al. 2016). Van Belleghem et al. (2018) presented a scenario for the emergence of persistent genetic variation that describes the demographic history of a population or species. When alleles involved in adaptation arise from independent mutations or chromosomal changes, they occur either at different loci or randomly in lineages from the same locus. Therefore, lineages are not identi- cal because new adaptive mutations may occur in differ- ent haplotypes in different regions. On the other hand, if ecological differentiation is based on alleles or genetic loci that exist as persistent genetic variation in an ances- tral population, derived alleles have the same origin but differ greatly in their evolutionary history. Plath et al. (2022) reported that 2C DNA content can vary not only across accessions within a species but also across Asparagus species growing in different geographical regions of the world. The causes of these changes are thought to be polyploidization and differ- ences in chromosome size. However, other cytogenetic abnormalities and mechanisms, such as aneuploidy (Sheidai and Inamdar 1992; Ozaki et al. 2004), the presence of B-chromosomes (Sheidai and Inamdar 1993), cytomixis (Sheidai et al. 1993), or desynapsis (Sheidai 1992), are the other poten- tially effective cytogenetic changes found in the genus Asparagus. Landscape genetics and population-level cytoge- netic studies can reveal habitat fragmentation and iden- tify the genetic clines within the geographic range of a plant species (Anderson et al. 2011). Studying global cli- mate change also tests the ecological and evolutionary responses of species to predicted conditions. Knowledge and understanding of how habitat fragmentation affects adaptive evolution under projected climate change is very limited (Anderson et al. 2011). The present study found that Asparagus species could see their geographic distribution significantly reduced in the future due to climate change. It has been suggested that environmental stresses (e. g., climate change) may result in inbreeding depres- sion. As a result, inbred, fragmented populations may have a lower ability to adapt to contemporary and changing conditions compared to large, unfragmented Figure 6. Box-plot of 1C-value quantity among the countries of ori- gin of Asparagus species (The country code 1-12, are as in Table 3). Figure 7. RDA plot shows a significant association (p=0.01), between the polyploidy level and 1C-value with spatial variables. 14 Parisa Fouroutan, Masoud Sheidai, Fahimeh Koohdar populations. Fragmented populations with reduced genetic diversity may lack variation in key ecologi- cal traits such as drought tolerance. In such situations, assisted migration to suitable habitats along with the conservation of habitat corridors, may be necessary to prevent dramatic declines in species and genetic diver- sity (Anderson et al. 2011). Polyploidy may play a role in adaptation to new habitats and environmental conditions. This appears to be positively related to latitude, altitude, and recent sea ice (Stebbins, 1984; Brochmann et al. 2004). Higher ploidy rates are generally observed at higher latitudes or altitudes than related diploids, especially in herbaceous perennial grasses (Zhang et al. 2019). Likewise, genome size is correlated with the environment and geographic distribution of species (Bottini et al. 2000; Bennett and Leitch 2011), and changes in DNA C values are correlat- ed with many phenotypic traits of cells and organisms. This can affect important ecological traits of plant spe- cies in natural habitats, such as spring growth timing, cell size and leaf expansion rate early in the growing season, frost tolerance, and dry conditions (Zhang et al. 2019). Therefore, in conclusion, we report that both spa- tial and bioclimatic variables influence the genetic struc- ture and geographical distribution of Asparagus spe- cies worldwide and that general conservation programs against climate change are needed. 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