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Average frequency of band-present allele across the five populations relative to fragment size (bp) for (a) C. virginica and (b) O. equestris based on the matrixB (open triangles) and 0 error (filled squares) data sets. The 0 error data are a subset of the matrixB data after culling high-error loci. Allele frequencies were estimated from all individuals using AFLPsurv with Bayesian non-uniform priors.
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Phylogeographic inferences about gene flow are strengthened through comparison of co-distributed taxa, but also depend on adequate genomic sampling. Amplified fragment length polymorphisms (AFLPs) provide a rapid and inexpensive source of multilocus allele frequency data for making genomically robust inferences. Every AFLP study initially generates...
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... each species, five nested (that is, non-independent) data sets were created from matrixB with incrementally less average mismatch error based on duplicates (Table 1). For C. viginica, some AFLP data from the CAT-selective primer showed plate effects (Supplementary Figure 2) as described below and was repeated from the archived pre- selective reaction (15 individuals). The matrixB mismatch error rate was 4.7% in C. virginica and 5.7% in O. equestris. The number of loci in the six data sets (0-4% error plus matrixB) ranged from 28 to 206 for C. virginica, and 26 to 167 for O. ...
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... was evident from a negative correlation between frag- ment size and band-present frequency, which was significant when based on band phenotypes (r¼À0.49 to À0.87; Po0.01) and on Bayesian band-present allele frequencies (r¼À0.41 to À0.87; Po0.01; Figure 2). Decomposing the patterns that produced this correlation, both species had roughly J-shaped frequency distributions of band- present phenotype frequencies, with the 0-0.1 class (fixed or nearly fixed for band-absent allele) and the 0.9-1.0 class (fixed or nearly fixed for band-present allele) being the second and first most abundant classes, respectively, in every data set (Supplementary Figure 3). However, whether examining band phenotype frequency or Bayesian-estimated allele frequencies, the frequency distribution was distinct for fragment lengths below and above 300 bp (Figure 2). As expected from homoplasy (comigrating fragments) in smaller fragments, band-present allele frequencies were skewed-high for frag- ments o300 bp whereas frequencies were skewed-low, with many fewer moderate frequency loci, for fragments 4300 bp (Figure 2). Furthermore, in both species, as higher error loci were discarded to produce smaller data sets with lower average error, the loci with moderate band-present frequencies were disproportionately elimi- nated (Figure 2; Supplementary Figure 3), strengthening the disparity in allele frequency spectrum for fragments o300 and 4300 bp in length. Homoplasy was not restricted to small fragments; even fragments 4300 bp showed a significant negative correlation between fragment size and band-present frequency for C. virginica in matrixB (r¼À0.60, Po0.01) and for O. equestris in the three largest data sets ...
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... was evident from a negative correlation between frag- ment size and band-present frequency, which was significant when based on band phenotypes (r¼À0.49 to À0.87; Po0.01) and on Bayesian band-present allele frequencies (r¼À0.41 to À0.87; Po0.01; Figure 2). Decomposing the patterns that produced this correlation, both species had roughly J-shaped frequency distributions of band- present phenotype frequencies, with the 0-0.1 class (fixed or nearly fixed for band-absent allele) and the 0.9-1.0 class (fixed or nearly fixed for band-present allele) being the second and first most abundant classes, respectively, in every data set (Supplementary Figure 3). However, whether examining band phenotype frequency or Bayesian-estimated allele frequencies, the frequency distribution was distinct for fragment lengths below and above 300 bp (Figure 2). As expected from homoplasy (comigrating fragments) in smaller fragments, band-present allele frequencies were skewed-high for frag- ments o300 bp whereas frequencies were skewed-low, with many fewer moderate frequency loci, for fragments 4300 bp (Figure 2). Furthermore, in both species, as higher error loci were discarded to produce smaller data sets with lower average error, the loci with moderate band-present frequencies were disproportionately elimi- nated (Figure 2; Supplementary Figure 3), strengthening the disparity in allele frequency spectrum for fragments o300 and 4300 bp in length. Homoplasy was not restricted to small fragments; even fragments 4300 bp showed a significant negative correlation between fragment size and band-present frequency for C. virginica in matrixB (r¼À0.60, Po0.01) and for O. equestris in the three largest data sets ...
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... was evident from a negative correlation between frag- ment size and band-present frequency, which was significant when based on band phenotypes (r¼À0.49 to À0.87; Po0.01) and on Bayesian band-present allele frequencies (r¼À0.41 to À0.87; Po0.01; Figure 2). Decomposing the patterns that produced this correlation, both species had roughly J-shaped frequency distributions of band- present phenotype frequencies, with the 0-0.1 class (fixed or nearly fixed for band-absent allele) and the 0.9-1.0 class (fixed or nearly fixed for band-present allele) being the second and first most abundant classes, respectively, in every data set (Supplementary Figure 3). However, whether examining band phenotype frequency or Bayesian-estimated allele frequencies, the frequency distribution was distinct for fragment lengths below and above 300 bp (Figure 2). As expected from homoplasy (comigrating fragments) in smaller fragments, band-present allele frequencies were skewed-high for frag- ments o300 bp whereas frequencies were skewed-low, with many fewer moderate frequency loci, for fragments 4300 bp (Figure 2). Furthermore, in both species, as higher error loci were discarded to produce smaller data sets with lower average error, the loci with moderate band-present frequencies were disproportionately elimi- nated (Figure 2; Supplementary Figure 3), strengthening the disparity in allele frequency spectrum for fragments o300 and 4300 bp in length. Homoplasy was not restricted to small fragments; even fragments 4300 bp showed a significant negative correlation between fragment size and band-present frequency for C. virginica in matrixB (r¼À0.60, Po0.01) and for O. equestris in the three largest data sets ...
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... was evident from a negative correlation between frag- ment size and band-present frequency, which was significant when based on band phenotypes (r¼À0.49 to À0.87; Po0.01) and on Bayesian band-present allele frequencies (r¼À0.41 to À0.87; Po0.01; Figure 2). Decomposing the patterns that produced this correlation, both species had roughly J-shaped frequency distributions of band- present phenotype frequencies, with the 0-0.1 class (fixed or nearly fixed for band-absent allele) and the 0.9-1.0 class (fixed or nearly fixed for band-present allele) being the second and first most abundant classes, respectively, in every data set (Supplementary Figure 3). However, whether examining band phenotype frequency or Bayesian-estimated allele frequencies, the frequency distribution was distinct for fragment lengths below and above 300 bp (Figure 2). As expected from homoplasy (comigrating fragments) in smaller fragments, band-present allele frequencies were skewed-high for frag- ments o300 bp whereas frequencies were skewed-low, with many fewer moderate frequency loci, for fragments 4300 bp (Figure 2). Furthermore, in both species, as higher error loci were discarded to produce smaller data sets with lower average error, the loci with moderate band-present frequencies were disproportionately elimi- nated (Figure 2; Supplementary Figure 3), strengthening the disparity in allele frequency spectrum for fragments o300 and 4300 bp in length. Homoplasy was not restricted to small fragments; even fragments 4300 bp showed a significant negative correlation between fragment size and band-present frequency for C. virginica in matrixB (r¼À0.60, Po0.01) and for O. equestris in the three largest data sets ...
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... is a well-documented artifact of scoring dense fragment profiles ( Vekemans et al., 2002) with stronger impacts expected on smaller fragments (Althoff et al., 2007;Caballero et al., 2008). Simulated metapopulations with p ¼ 0:1 studied by Caballero et al. (2008) showed homoplasy effects to include a downward bias on F ST and an upward bias on both H e and p, each bias monotonically increasing with shorter fragment size. In this study, a negative correlation between fragment size and band-present phenotype fre- quency indicated some homoplasy effects in all fragment size classes. For unknown reasons band-present frequency distributions transi- tioned abruptly between fragments o300 versus 4300 bp in C. virginica (Figure 2). The Caballero et al. (2008) predictions for homoplasy effects were seen much more strongly in loci o300 versus 4300 bp in 4% error C. virginica data; the loci o300 bp had p five times larger and H S three times larger than loci 4300 bp. In contrast to expectations, however, among-locus average F ST was twice as high for short fragments (0.0409 vs 0.0212, both significantly different than zero at Po0.001). In fact, this F ST discrepancy between short and long fragments was an order of magnitude for 0 error (0.0114 vs 0.002, Po0.006 for both) and 1% error data, and smallest for matrixB (0.0529 vs 0.0424). The differences in average F ST do not appear to be a function of genomic sampling because the number of loci in short (11-131) vs long (17-122) fragment subsets was similar across the data sets. The O. equestris data showed the same differences between short and long fragments and the same bias trends, although in this case the fragments 4300 bp in each data set had F ST that was not statistically different from zero, whereas the shorter fragments had F ST similar to that shown in Figure 3. We do not have an explanation for this disagreement with simulation-based predictions, but note that many of the highest F ST loci among small fragments showed clinal patterns in agreement with previous codominant data (data not shown). These loci clearly have useful information content despite indications of strong homoplasy effects at that fragment size class. In fact, excluding loci o300 bp for fear of homoplasy effects would have removed all but one locus with F ST ...
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Citations
... Though the inferred absence of population structure among sites even >65 km apart may be a true signal, previous work has demonstrated low dispersal rates (Peacock, 1997;Peacock & Smith, 1997) and high genetic differentiation among patches located <5 km from each other (Henry et al., 2012;Robson et al., 2016). Our results may therefore be an artifact of the high genotyping error observed, which is known to bias estimates of population structure towards admixture (Kirk & Cardon, 2002;Zhang & Hare, 2012). ...
Genetic tools for wildlife monitoring can provide valuable information on spatiotemporal population trends and connectivity, particularly in systems experiencing rapid environmental change. Multiplexed targeted amplicon sequencing techniques, such as genotyping‐in‐thousands by sequencing (GT‐seq), can provide cost‐effective approaches for collecting genetic data from low‐quality and quantity DNA samples, making them potentially useful for long‐term wildlife monitoring using non‐invasive and archival samples. Here, we developed a GT‐seq panel as a potential monitoring tool for the American pika (Ochotona princeps) and evaluated its performance when applied to traditional, non‐invasive, and archival samples, respectively. Specifically, we optimized a GT‐seq panel (307 single nucleotide polymorphisms (SNPs)) that included neutral, sex‐associated, and putatively adaptive SNPs using contemporary tissue samples (n = 77) from the Northern Rocky Mountains lineage of American pikas. The panel demonstrated high genotyping success (94.7%), low genotyping error (0.001%), and excellent performance identifying individuals, sex, relatedness, and population structure. We subsequently applied the GT‐seq panel to archival tissue (n = 17) and contemporary fecal pellet samples (n = 129) collected within the Canadian Rocky Mountains to evaluate its effectiveness. Although the panel demonstrated high efficacy with archival tissue samples (90.5% genotyping success, 0.0% genotyping error), this was not the case for the fecal pellet samples (79.7% genotyping success, 28.4% genotyping error) likely due to the exceptionally low quality/quantity of recovered DNA using the approaches implemented. Overall, our study reinforced GT‐seq as an effective tool using contemporary and archival tissue samples, providing future opportunities for temporal applications using historical specimens. Our results further highlight the need for additional optimization of sample and genetic data collection techniques prior to broader‐scale implementation of a non‐invasive genetic monitoring tool for American pikas.
... In this study we used AFLPs as a first approximation to analyze the A. quebracho-blanco intraspecific genetic diversity. Despite some weakness of AFLP data, this molecular technique provides a relatively rapid and inexpensive source of multilocus data for making genomically robust inferences (Zhang and Hare, 2012). The information retrieved using these makers allowed us to identify genetic populations and different levels of intrapopulation genetic variability (see below). ...
Aspidosperma quebracho-blanco is a key species of the Gran Chaco, one of the most threatened subtropical woodlands in South America. By combining ecological niche modeling (ENM) and population genetic analysis, we explored the impact of land use and climate change on the species distribution with the aim to map the geography of its vulnerability and to propose conservation strategies. Future climate models revealed a generalized reduction in climatic suitability for A. quebracho-blanco, as well as a tendency of suitable areas for the species to shift towards the south-southeast. Land use and land cover (LULC) analysis indicated that more than 50% of A. quebracho-blanco distribution is mainly affected by cultivated lands. The analysis of the genetic population showed that the species has moderate genetic structure and populations are clustered in three genetic groups. The ENM analyses indicated an under-representation of the species’ potential range in protected areas. These results highlight the need to prioritize the conservation and restoration of remnant populations and the expansion of protected natural areas. Therefore, using an integrative approach of the results obtained here, we identified four areas with different levels of vulnerability and proposed specific conservation strategies for each one. This work can be similarly applied in other countries that might establish common criteria in the definition of conservation strategies for tree species.
... A major drawback for the AFLP technique is its dominant nature, although co-dominant AFLP markers have been found in low frequency, which means that it is difficult to use AFLP in identifying allelic variants at a specific locus (Zhang and Hare, 2012). Moreover, due to the high cost and the relatively complicated methodology, AFLPs are not adapted To protect the rights of the author(s) and publisher we inform you that this PDF is an uncorrected proof for internal business use only by the author(s), editor(s), reviewer(s), Elsevier and typesetter SPi. ...
Diagnostic methods are vital for the study of any kind of infection of forest trees caused by biotic agents. Usually, a combination of traditional and modern verification approaches for plant pathogen identification is often deployed. This is necessary as accurate and proper identification of tree pathogens is critical for a better understanding of disease epidemiology and facilitation of better control and management measures. This chapter discusses the different diagnostic methods currently used to study pathogens causing infections in forest trees focusing primarily on microscopy, immunological, microbiological, biochemical, remote sensing, molecular methods, and sequencing.
... One of these was comprised of UK and German individuals, one of only Polish individuals, and one of German, Polish and a UK individual. AFLP analysis can incorporate hundreds of polymorphisms across a whole genome, but it suffers from relatively high genotyping error (Zhang and Hare 2012) that can significantly affect analysis of population structure and make it impossible to determine the 'true' number of populations among a set of individuals. Mensch (2009) reports shifting AFLP peak profiles between individuals included in her study, which may have resulted in incorrect genotyping and thus the greater number of genetic lineages detected (Vašek et al. 2017). ...
Segmentina nitida Müller 1774 is a rare European freshwater snail of drainage ditches and marshland, which has seen a marked decrease in range (~ 80%) over the last 100 years in the UK. This has been attributed to over-dredging of drainage ditches for land management, conversion of grazing marshes to arable farmland, as well as eutrophication. Segmentina nitida is identified as a priority species in the UK Biodiversity Action Plan (UKBAP) that recommends further research to inform reintroduction and translocation for its conservation. We used nuclear markers (microsatellites and ITS2) and a mitochondrial (COI) marker to investigate population structure in S. nitida individuals sampled from Poland, Germany, Sweden, and the UK to identify differences within and between populations. Data based on 2D landmark-based geometric morphometrics of S. nitida shells was used to determine if phenotypic variation followed genetic differentiation. Two distinct genetic lineages of S. nitida were identified in ITS and COI phylogenies as well as cluster analysis of microsatellite markers, one of these lineages was present in eastern Europe (Poland, Sweden- Lineage 2), and one in western Europe (UK, Germany- Lineage 1), with lineages co-occurring in German populations. No genetic admixture was observed in German populations containing both lineages. These two lineages were also distinct in shape, with lineage 2 individuals having significantly wider shells and taller and wider apertures than those in Lineage 1. ~ 85% of shells assigned to the predicted lineage in a discriminant analysis of Procrustes shape coordinates. We infer that S. nitida includes at least one sympatric cryptic species. We discuss the implications of these findings on the conservation status of S. nitida in the UK and Europe.
... Vol. 26 No. 2 May 2021 ISSN: 2509-0119 268 but the main thing is that this signal is not lost for the sake of an "acceptable" level of error, and the researchers propose an empirical approach to achieve the desired compromise [61]. ...
Genotype error can greatly reduce the power of a genetic study. For family data, genotype error can be assessed by examining marker data for non-Mendelian inconsistencies, closely linked markers for double recombination events, and consistency of duplicate genotypes. Genetic markers are widely used to determine the parentage of individuals in studies of mating systems, reproductive success, dispersals, quantitative genetic parameters and in the management of conservation populations. These markers are, however, imperfect for parentage analyses because of the presence of genotyping errors and undetectable alleles, which may cause incompatible genotypes (mismatches) between parents and offspring and thus result in false exclusions of true parentage. Highly polymorphic markers widely used in parentage analyses, such as microsatellites, are especially prone to genotyping errors. Molecular markers based on a hybridization reaction or PCR stage that detect DNA polymorphism are currently used in various fields of biology, including the study and preservation of genetic diversity, identification of individuals, phylogenetic, mapping of useful traits of quality and resistance to stress factors. , in the breeding process, biotechnology, etc. Before starting the experiment, researchers must determine what type of markers to use based on the following criteria: the variability and number of required markers, the need for their codominance, the corresponding requirements for the extracted DNA; practical-efficiency, reproducibility of analysis, the necessary appropriate technical support and cost. For a correct interpretation of the results of genotyping, one should take into account the fact that the use of any type of molecular markers is associated with a number of genotyping errors, the main ones being the loss of larger alleles, "zero" alleles, "stutter" alleles due to the peculiarities of Tag polymerase, and non-homology of amplified sequences of the same size (homoplasia). Researchers formulate defining conditions to reduce genotyping errors and reduce their impact on the final analysis. These include the quality and quantity of analyzed DNA, the level of technical capabilities and professionalism of the staff, since the human factor is defined as one of the main reasons for incorrect results; conducting pilot experiments for a comparative assessment of the theoretical and real error rate. The minimization of errors is achieved by assessing the capabilities of a particular type and screening markers; optimization of experimental methods, proper use of controls, replicates, and development of statistical approaches to identify errors. The trade-off between culling error-generating loci and increasing the potential of the retained loci to amplify the genetic signal can be different in different studies, but the main thing is that this signal is not lost for the sake of an "acceptable" level of error and the researchers develop empirical approaches to achieve the desired compromise.so that this signal is not lost for the sake of an "acceptable" level of error and researchers develop empirical approaches to achieve the desired compromise.so that this signal is not lost for the sake of an "acceptable" level of error and researchers develop empirical approaches to achieve the desired compromise.
... Amplification fragment length polymorphisms (AFLP) analysis was performed as described previously. [18][19][20] Following amplification, the AFLP fragments were ran by capillary electrophoresis. The capillary electrophoresis 20 µL reaction consisted of a 2 µL (1:10 dilution) of the AFLP product, 0.1 µL of Genescan 600LIZ size marker (Thermo Fisher, Landsmeer, The Netherlands) and 17.9 µL HiDi Formamide (Thermo Fisher). ...
Background
At the dermatology service of the General Hospital of Mexico City, Mexico, two patients, father and son, with black‐grain mycetoma were seen. The grains were isolated and the cultured fungi were identified as Madurella mycetomatis based on morphology. Using the M. mycetomatis specific PCR, amplicons of a different size than that of the M. mycetomatis type strain were obtained.
Objective
To determine the causative agent of the two black‐grain mycetoma cases and develop non‐culture based diagnostic tools to identify them to the species level
Methods
The M. mycetomatis specific, the internal transcribed spacer (ITS) region, β‐tubulin (BT) and ribosomal binding protein 2 (RBP2) PCRs were used to confirm the identity of the isolates. Genetic variation was established by AFLP. To determine the antifungal susceptibility profile, the Sensititre™ YeastOne™ assay was used. To develop a species specific PCR primers were designed on the sequenced PCR amplicon from the M. mycetomatis specific PCR.
Results
By analyzing the ITS, BT and RBP2 regions the isolates were identified as Madurella pseudomycetomatis. The isolates from father and son were similar but not identical to M. pseudomycetomatis from Venezuela and one from an unknown origin. Madurella pseudomycetomatis isolates were inhibited by itraconazole, posaconazole and voriconazole but showed increased MIC values for amphotericin B and fluconazole. They were not inhibited by the echinocandins and 5 flucytosine. The two patients were treated with itraconazole resulting in cure for the father while the son was lost to follow up. The species‐specific PCR developed for M. pseudomyceotmatis was discriminative and specific.
Conclusion
M. pseudomycetomatis is genetically diverse with same susceptibility profile as M. mycetomatis and causes eumycetoma in Latin America. The M. pseudomycetomatis specific PCR can be used to identify this causative agent to the species level, however, this needs to be validated in an endemic setting.
... Although there is no direct evidence for the relationship between the number of amplification primer pairs and the level of genetic diversity, higher interlocus variance was found to contribute more to the total variance associated with the (Ribeiro et al., 2002). Moreover, more amplified AFLP loci, though with higher error rate, could be positively correlated with higher level of genetic diversity (Zhang and Hare, 2012). Additionally, higher number of amplification primer pairs used could have amplified fragments spanning more chromosomal loci and contributed to the higher level of genetic diversity. ...
Populations can be genetically isolated by differences in their ecology or environment that hampered efficient migration, or they may be isolated solely by geographic distance. Moreover, mountain ranges across a species’ distribution area might have acted as barriers to gene flow. Genetic variation was quantified using amplified fragment length polymorphism (AFLP) and 13 selective amplification primer combinations used generated a total of 482 fragments. Here, we tested the barrier effects of mountains on gene flow and environmentally dependent local adaptation of Cunninghamia konishii occur in Taiwan. A pattern of genetic isolation by distance was not found and variation partitioning revealed that environment explained a relatively larger proportion of genetic variation than geography. The effect of mountains as barriers to genetic exchange, despite low population differentiation indicating a high rate of gene flow, was found within the distribution range of C. konishii. Twelve AFLP loci were identified as potential selective outliers using genome-scan methods (BAYESCAN and DFDIST) and strongly associated with environmental variables using regression approaches (LFMM, Samβada, and rstanarm) demonstrating adaptive divergence underlying local adaptation. Annual mean temperature, annual precipitation, and slope could be the most important environmental factors causally associated with adaptive genetic variation in C. konishii. The study revealed the existence of physical barriers to current gene flow and environmentally dependent adaptive divergence, and a significant proportion of the rate of gene flow may represent a reflection of demographic history.
... In comparison, many other lepidopteran populations for which genetic diversity at AFLP loci has been characterized, including several threatened species, display PPL above ~ 0.70 (some approaching 1.0) and H e ranging from 0.03 to 0.46 (see Table 5 in Gradish et al. 2015). However, differences in laboratory protocol and the methods used to score AFLP phenotypes can generate datasets that greatly vary in the number of loci retained and the genotyping error rate (Crawford et al. 2012), potentially influencing estimates of genetic diversity and population differentiation (e.g., Herrmann et al. 2010;Zhang and Hare 2012). Thus, direct comparisons among species and studies should be made with caution. ...
Understanding effects of habitat and landscape features on genetic variation is a prerequisite for the development of habitat and landscape management strategies aimed at conserving genetic diversity. While there has been considerable research on the effects of landscape structure on the genetics of populations, a recent review identified key biases in this body of work. The majority of landscape genetic studies investigate the intervening matrix’s influence on differentiation and gene flow among populations. Although characteristics of local habitat patches may be important determinants of genetic diversity, fewer studies have examined these relationships. Here we use node- and neighbourhood-based approaches to analyze correlates of genetic diversity in the bog copper (Lycaena epixanthe), a specialist butterfly endemic to temperate Nearctic peatlands that is threatened in parts of its range. Based on 190 repeatable and polymorphic amplified fragment length polymorphism loci, we found that genetic diversity was higher in habitat patches that were smaller and surrounded by more open water. Our results indicate that valuing small peatlands and preserving the surrounding water table may be important for conservation of genetic diversity in this highly specialized species. Our study highlights the importance of variables affecting habitat quality for conservation genetics.
... The reliability of AFLP markers was assessed by the error rate, which is the ratio of the number of mismatched loci to the total number of loci (Bonin et al., 2004;Ley and Hardy, 2013). Mismatches can be calculated within duplicates across all loci or for each locus across all duplicates (Bonin et al., 2004;Bonin et al., 2007;Zhang and Hare, 2012). Replicate error rate due to biological or technical causes was used to calculate the mismatch error rate using the formula stated in (Bonin et al., 2004;Bonin et al., 2007;Holland et al., 2008). ...
Visceral leishmaniasis (VL), the most severe form of leishmaniasis, is caused by Leishmania donovani. In addition to fatal VL, these parasites also cause skin diseases in immune-competent and -suppressed people, post-kala azar dermal leishmaniasis (PKDL) and HIV/VL co-infections, respectively. Genetic polymorphism in 36 Ethiopian and Sudanese L. donovani strains from VL, PKDL and HIV/VL patients was examined using Amplified Fragment Length Polymorphism (AFLP), kDNA minicircle sequencing and Southern blotting. Strains were isolated from different patient tissues: in VL from lymph node, spleen or bone marrow; and in HIV/VL from skin, spleen or bone marrow. When VL and PKDL strains from the same region in Sudan were examined by Southern blotting using a DNA probe to the L. donovani 28S rRNA gene only minor differences were observed. kDNA sequence analysis distributed the strains in no particular order among four clusters (A - D), while AFLP analysis grouped the strains according to geographical origin into two major clades, Southern Ethiopia (SE) and Sudan/Northern Ethiopia (SD/NE). Strains in the latter clade were further divided into subpopulations by zymodeme, geography and year of isolation, but not by clinical symptoms. However, skin isolates showed significantly (p < 0.0001) fewer polymorphic AFLP fragments (average 10 strains = 348.6 ± 8.1) than VL strains (average 26 strains = 383.5 ± 3.8).
... Following other MS-AFLP studies (Alonso, Pérez, Bazaga, Medrano, & Herrera, 2016;Cara, Marfil, & Masuelli, 2013; also see Zhang & Hare, 2012), loci were also discarded if they showed too many mismatches among technical duplicates: We allowed a maximum of three mismatches among the set of 24 pairs of technical duplicates. The averaged mismatch error rate (±standard deviation) across all primer combinations used was before purging for T. alatum 8.46 ± 1.70% (N = 65) and for T. hemicyclum 9.20% ± 1.39% (N = 72). ...
DNA methylation is one of the mechanisms underlying epigenetic modifications. DNA methylations can be environmentally induced and such induced modifications can at times be transmitted to successive generations. However, it remains speculative how common such environmentally induced transgenerational DNA methylation changes are and if they persist for more than one offspring generation. We exposed multiple accessions of two different apomictic dandelion lineages of the Taraxacum officinale group (Taraxacum alatum and T. hemicyclum) to drought and salicylic acid (SA) treatment. Using methylation-sensitive amplified fragment length polymorphism markers (MS-AFLPs) we screened anonymous methylation changes at CCGG restriction sites throughout the genome after stress treatments and assessed the heritability of induced changes for two subsequent unexposed offspring generations. Irrespective of the initial stress treatment, a clear buildup of heritable DNA methylation variation was observed across three generations, indicating a considerable background rate of herit-able epimutations. Less evidence was detected for environmental effects. Drought stress showed some evidence for accession-specific methylation changes, but only in the exposed generation and not in their offspring. By contrast, SA treatment caused an increased rate of methylation change in offspring of treated plants. These changes were seemingly undirected resulting in increased transgenerational epigenetic variation between offspring individuals, but not in predictable epigenetic variants. While the functional consequences of these MS-AFLP-detected DNA methylation changes remain to be demonstrated, our study shows that (1) stress-induced transgenerational DNA methylation modification in dandelions is genotype and context-specific; and (2) inherited environmental DNA methylation effects are mostly undirected and not targeted to specific loci.
