Gr). Modeling the segregation of genomewide markers with estimated effects may be one method of predicting Gr in a cross, but this approach remains untested. Our objectives were to: (i) use simulations to assess the accuracy of genomewide predictions of Gr and the long-term response to selection when selecting crosses on the basis of such predictions; and (ii) empirically measure the ability to predict genetic correlations using data from a barley (Hordeum vulgare L.) breeding program. Using simulations, we found that the accuracy to predict Gr was generally moderate and influenced by trait heritability, population size, and genetic correlation architecture . Among 26 barley breeding populations, the empirical prediction accuracy of Gr was low (-0.012) to moderate (0.42), depending on trait complexity. Within a simulated plant breeding program employing indirect selection, choosing crosses based on predicted Gr increased multi-trait genetic gain by 11–27% compared to selection on the predicted cross mean. Importantly, when the starting genetic correlation was negative, such cross selection mitigated or prevented an unfavorable response in the trait under indirect selection. Prioritizing crosses based on predicted genetic correlation can be a feasible and effective method of improving unfavorably correlated traits in breeding programs.The many quantitative traits of interest to plant breeders are often genetically correlated, which can complicate progress from selection. Improving multiple traits may be enhanced by identifying parent combinations – an important breeding step – that will deliver more favorable genetic correlations ( Investil model” ]. This sl model” .Triticum aestivum L.; Zea mays L.; Glycine max L.; Plant breeders routinely select on multiple traits, but progress can be complicated by genetic correlations. If two traits are favorably correlated, selection can simultaneously improve both by tandem selection, indirect selection, or a trait index . Unfavori.e., one trait), but multivariate models have recently been explored as a means of borrowing information from genetically correlated traits and improving the prediction accuracy of both traits  breeding program.The objectives of this study were to (i) use simulations to assess the accuracy of genomewide predictions of genetic correlations and the long-term response to selection when selecting crosses on the basis of superior/correlated progeny means; and (ii) empirically measure the ability to predict genetic correlations using data from a barley  population assuming two fully inbred parents, bi-allelic QTL, and no dominance or epistasis. This derivation follows the notation presented in L(k) QTL influence the kth quantitative trait, and in the mth cross mL(k) QTL are segregating for that trait (where mL(k) ≤ L(k)). The expected genetic variance in the cross is the sum of the variance of each locus plus the covariance between pairs of loci. As noted in m isith and jth loci, respectively and ith and jth loci. As expected, loci that are genetically unlinked  were jittered by adding a small value (1 × 10−6 cM). These data were used to define the genetic architecture of the simulated quantitative traits and form the initial pool from which to establish a base training population.We conducted two simulations to assess the utility of predicting the genetic correlation in a breeding cross. Our simulations were based on observed marker genotypes of 1,570 North American two-row spring barley lines genotyped with 3,072 single nucleotide polymorphism (SNP) markers  and genetic correlation, the initial genetic correlation, and the base/training population size . QTL effects were defined by a geometric series, as proposed by kth QTL, the value of the favorable homozygote was In the first simulation experiment, we assessed the conditions influencing prediction accuracy of genetic correlations. We perturbed the heritabilities of two traits, the architecture defining the traits  between QTL influencing the first trait and QTL influencing the second trait. This adjustment resulted in base genetic correlations that approximately matched the target, Genetic correlations were generated according to three different architecture types: pleiotropy, tight linkage, or loose linkage. For simplicity, we assumed that the genetic architecture was governed entirely by one of the types. Under pleiotropy, the sampled QTL effects were first stored in an TPN individuals from the simulation starting material. For each trait, the genotypic value of an individual was calculated as the sum of the QTL allele effects carried by that individual, and the genetic variance was calculated as the variance among genotypic values. Phenotypic values were simulated by adding independent normally distributed deviations to the genotypic values to achieve a starting entry-mean heritability of ith individual for the pth trait, pth trait, mth marker in the ith individual , mth marker for the pth trait, and The base/training population was first generated by randomly sampling y of hp2  with no TPN = 600 individuals from the simulation starting material. Informed by the results of the first simulation (see below), we used only the simpler RR-BLUP model to predict marker effects. Potential parents for the first breeding cycle were selected by determining the best 30 individuals in training population based on the predicted genotypic values of the first trait (the primary trait under direct selection). We predicted the mean, genetic variance, and genetic correlation for all possible non-reciprocal crosses between the potential parents. We then calculated the superior progeny mean of the first trait and the correlated progeny mean of the second trait using the predicted parameters and i.e., selection of the best 5%).We conducted a second simulation experiment to measure the long-term response of two correlated traits under different cross selection strategies. The range of perturbed parameters was smaller than in the first simulation , though qtl R package  QTL haplotypes, and the proportion of QTL with fixed alleles. Simulations were replicated 250 times, and we report the mean and 95% approximate confidence interval for each measured variable.Twenty crosses were selected based on i) equal-weight sum of the normalized predicted superior progeny mean of the first trait and predicted correlated response in the second trait  package , during Fusarium graminearum Schwabe), and plant height. To estimate the genetic correlation between pairs of traits in the TP, we regressed the phenotypic observations of two traits, i indexes genotypes, j environments, and p traits. We fitted a bi-variate mixed model:sommer  of the TP using the univariate model in n = 330,078), we used estimated marker effects and the R package PopVar to predict the genetic correlation for each pair of traits.  Twenty-six crosses were made based on the predictions, producing “validation families” ranging from 28 to 160 F5 lines. The criteria for selecting crosses are described in Marker effects were estimated from marker genotypes and phenotypic best linear unbiased estimates . Genomewide marker data for empirical validation is also available from the Data Repository for the University of Minnesota (DRUM): https://conservancy.umn.edu/handle/11299/204785. All simulations and analyses were performed in R , and genetic architecture. We provide a cross-section of results in TPN = 150 to TPN = 600. We generally did not observe a pattern of diminishing returns when increasing TPN, though some evidence of that pattern was present under the tight linkage architecture  and this difference under loose linkage vs. pleiotropy was 0.017 (6.2%). With tight linkage and loose linkage genetic architectures, accuracy was slightly higher when 100 vs. 30 QTL influenced both traits , but the reverse was true under pleiotropy, where the accuracy was about 8% lower (a difference of about 0.03) with more QTL  correlation between FHB severity and heading date.We used genomewide markers and phenotypic data to empirically estimate the genetic correlation for three pairs of quantitative traits in our 175-line training population (TP). The genetic correlation was -0.84 between Fusarium head blight (FHB) severity and heading date, -0.44 between FHB severity and plant height, and 0.48 between heading date and plant height . These eP > 0.05; bootstrapping). The ability to predict the genetic correlation appeared to coincide with the heritability of both traits; the entry-mean heritability in the TP (and in the VF) was 0.45 (0.11) for FHB severity, 0.96 (0.78) for heading date, and 0.52 (0.74) for plant height (The mean (and range) of estimated genetic correlations among the validation families was -0.18  for FHB severity and heading date, -0.038  for FHB severity and plant height, and -0.13  for heading date and plant height . Estimatt height .Our second simulation showed that the genetic gain for two correlated quantitative traits was impacted by the base genetic correlation, the genetic architecture, and the strategy to select crosses . We founvs. FM cross selection ranged from 0.30 (11%), with tight linkage architecture and positive correlation, to 0.53 (27%), with loose linkage architecture and negative correlation.Gain from selection, and marginal differences between selection methods, depended on the genetic architecture and correlation. The final genetic gain was, on average, less when the genetic correlation was negative. With pleiotropic architecture, the reduction in genetic gain from a correlation of 0.5 to -0.5 was more severe (a roughly 100% decrease) than with tight or loose linkage architectures (a roughly 20% decrease). After 10 cycles, the marginal genetic response (based on an index) when using CPM When considering traits individually, we found that much of the advantage of selecting crosses on CPM was realized in the correlated response of the second trait . Selectivs. pleiotropy. Under the latter, genetic variance for the second trait was reduced at a rate comparable to the first trait . This change was much larger when the base correlation  size, trait heritability, prediction model, and genetic architecture. Our results implicated the usual suspects driving genomewide prediction accuracy for individual traits. Increasing the TP size and the heritability of both traits improved accuracy, an expected result given the importance of these parameters  assume that many more markers than true QTL have non-zero effect on both traits. Our approach to predicting genetic correlations relies on the recombination and segregation of these markers, implying that all contribute to variability in genetic variance and covariance, while only true QTL generate this variability. With pleiotropy, this would manifest as a downward bias in the covariance between traits, as we predict a greater possibility of recombination between markers than what is possible for the true QTL. Under loose linkage, an opposite, upward bias in covariance would be expected, as the many markers with uneven trait effects would be predicted to co-segregate more often than what is possible for the true QTL. Indeed, when we calculated the average bias of the predicted genetic correlations, we observed a roughly 30% upward bias under loose linkage and an opposite 30% downward bias under pleiotropy . Additionally, though the bias in predicting genetic covariance was always negative, it was less so under loose linkage than under pleiotropy. This bias, particularly if uneven across predicted crosses, could lead to the observed loss in accuracy. Practically, the impact of genetic architecture may be less important, since architecture is generally immutable and the effect on prediction accuracy is small  are attributable to the nature of each statistic and have practical implications. Greater accuracy when predicting the cross mean vs. genetic variance was predicted by theory . This was true under all conditions of genetic architecture, trait heritability, and base genetic correlation (rG(0)) . FurtherrG(0)) .i = 0.05; spk = 2.06), more weight is given to the predicted genetic variance vs. the predicted mean , it uses information differently from the CPM method. Finally, predictions of genetic correlations or correlated responses could enhance multi-objective cross optimization procedures . This condition is often encountered by breeders and would typically discourage the use of indirect selection  likely constrained prediction accuracy, as suggested in our first simulation  are commonly available in many breeding programs. Second, it is relatively inexpensive, in both time and computing power, to generate such predictions. Thus, it is possible that this procedure can be an additional tool for breeders to make decisions. We note, however, that validating predictions of genetic correlations requires phenotypic data on many large families, leading to population sizes that are generally unrealistic for a breeding program . It is l


Aedes are a cause of increasing concern in Europe owing to their ability to vector important human viral diseases. Entomological surveillance to early detect alien mosquito and flavivirus circulation in Liguria, northwest Italy, has been carried out since 2011.Invasive mosquito species (IMS) of the genus Aedes koreicus was first detected in Genoa in September 2015, when a male specimen was caught near the international airport; species identity was confirmed by genetic analysis. Over the next three years, 86 more adult specimens were trapped at sites throughout the city, accounting for 0.50% of all mosquitoes and 1.04% of Aedes sp. mosquitoes trapped in Genova in the four-year period 2015–2018. So far, no other monitored sites in Liguria have revealed the presence of this species. Ovitraps at two sites became positive for the species in July–August 2017. All female Ae. koreicus pools analysed were negative in biomolecular assays for Flavivirus.The invasive species Ae. koreicus in Genoa constitute, to the best of our knowledge, the first report of the species in northwest Italy and in a Mediterranean port city. The species appears to be established; trapping and climatic data support survival of Ae. koreicus in the area through three consecutive winters. Monitoring of adult mosquitoes detected the species two years before its discovery with ovitraps; trapping for adult specimens appears to be a more effective tool for the early detection of IMS. The airport  and the flower market are the most probable sites of introduction; however, the exact time and place of arrival of this IMS in Liguria remain unknown. Based on morphological and genetic data, a common origin for most of the Ae. koreicus populations established in Europe is suspected. So far, no control measures have been adopted in Genoa and the species will probably colonize an even wider area in the next few years.Our findings of  Aedes, are a source of increasing concern in Europe because of their ability to spread into new territories and cause outbreaks of human viral diseases, such as dengue, Zika, chikungunya, yellow fever and Japanese encephalitis [Aedes albopictus, endemic to southeast Asia, was the first invasive exotic mosquito species to become established in Europe, where it was first reported in Albania in 1979 [Ae. aegypti (established in Madeira and on the Eastern Black Sea coast), Ae. atropalpus, Ae. japonicus and Ae. koreicus [Invasive mosquito species (IMS), particularly of the genus phalitis . The Asi in 1979  and in I in 1979 . It was  in 1979 , and for in 1979 . Severalkoreicus , the latkoreicus .Ae. koreicus was first found in Belgium in 2008, which was the first report of this species outside its native range; it established in a small area of 6 km2 and does not seem to be colonizing the surrounding territory [Ae. koreicus specimens found in Europe are morphologically consistent with the species phenotype characteristic of Jeju-do Island, located south of Korea, as they carry a basal band of clear scales on hind tarsomere V, which is absent in mainland specimens [Originally endemic to southeast Asia, erritory . In 2011erritory , where ierritory –12, and erritory , along territory , in Hungerritory  and Sloverritory . Most ofpecimens , 9. The pecimens .Aedes spp., it might have been introduced at the egg or larval stage through the trade of used tyres or plants [Aedes koreicus is able to produce cold- and drought-resistant eggs, allowing it to survive winter temperatures; moreover, as it tolerates lower temperatures better than the congeneric Ae. albopictus, it is active earlier during the season and can occupy an empty niche at higher altitudes [Ae. japonicus japonicus, Ae. koreicus might go undetected in areas already invaded by the latter, as happened in Slovenia [Ae. koreicus as a vector of viral and parasitic diseases. Field-collected Ae. koreicus specimens were found infected by the Japanese encephalitis virus [Dirofilaria repens [D. immitis [Importation routes in Europe for this species remain unknown ; howeverr plants . Aedes kltitudes . Given iSlovenia . Geneticis virus  and the a repens . Moreovea repens  and of D immitis , 23. EntStarting in 2011, our institute (IZSPLV) has carried out entomological and virological surveillance of mosquitoes in northwest Italy  within the framework of research projects funded by the Italian Ministry of Health and the European Union. In 2016, due to the global Zika emergency, mosquito surveillance in Liguria was intensified through the support of the regional government and the collaboration of the public Health Services (AASSLL) and the City of Genova.Ae. koreicus in Genoa over four consecutive years. It is, to the best of our knowledge, the first report of the species in northwest Italy and in a port city of the Mediterranean basin. It provides clear evidence of the establishment of Ae. koreicus in the area, which may herald further spread of this IMS in Italy and beyond.This study reports the finding of 2-lure-baited BG-sentinel traps  and hay infusion-baited gravid traps  in sites throughout Liguria . Trapping sites were chosen according to risk factors, i.e. the possible introduction of alien mosquito species  or the potential circulation of endemic and/or imported mosquito-borne viruses, such as West Nile virus [In the four-year period 2015–2018, adult mosquitoes were trapped fortnightly by trained operators, by means of COle virus  or dengule virus   [Ae. koreicus (ND4KorF/N4N-8944D) [Doubtful N-8944D)  and one N-8944D) . ExpecteAe. koreicus specific primer set was also screened for the characteristic single nucleotide polymorphism (SNP), where a T is present in Ae. koreicus, a G in Ae. japonicus, and the other Aedes spp. have an A [Both forward and reverse reads were sequenced on an ABI Prism 3100 Genetic Analyzer , and assembled with DNASTAR Seqman software. The consensus sequences were then compared with those deposited in GenBank (NCBI) and species assignment was based on a minimum similarity value of 98%. Consensus obtained with the ave an A .Flavivirus genome [Female specimens underwent a biomolecular essay to detect flaviviral infection: an RT-PCR targeting the NS5 gene locus of the s genome .Ae. koreicus in 2016, a retrospective investigation of samples collected in 2015 was also performed based on: (i) visual examination of a photographic database of damaged Aedes spp. specimens; and (ii) a biomolecular assay for the mtDNA nad4 locus on damaged Aedes spp. archival specimens.After the initial detection of Aedes mosquito ovitraps (12 cm upper diameter black vases filled with 1000 ml of water and equipped with masonite™ strips as oviposition support) were deployed at various sites throughout Liguria and monitored biweekly. The number and location of the ovitraps located in Genoa varied depending on the sampling year  and included five sites not previously surveyed for adult mosquitoes  data recorded at three sites representative of three different areas of Genoa , were analysed and compared with mosquito trapping data from the four-year period July 2015 to October 2018. The sites were located in: Genoa Pegli , Genoa Pontedecimo , and Genoa Centro Funzionale , respectively.http://www.cartografiarl.regione.liguria.it/SiraQualMeteo/script/PubAccessoDatiMeteo.asp).Climatic data were obtained from the weather and climatic online database run by the Osservatorio Meteo Idrologico della Regione Liguria (OMIRL), based on data collected by the Agency for the Protection of the Environment of Liguria (ARPAL)  and a gravid trap (site GE6), respectively. The two sites are located 1.1 km apart. The presence of a clear band at the base of the fourth tarsomere of the hind legs confirmed their species identification as Ae. koreicus. A further clear band on tarsomere V of the hind legs was consistent with the same phenotype already detected in most of the other European sites, including northeast Italy. Further morphological evidence of their species identification was obtained by visual comparison of the two Ligurian specimens with some Ae. koreicus collected in Trentino, northeast Italy.Ae. koreicus sequences deposited in GenBank . Moreover, the primer set specific for Ae. koreicus confirmed the previous genetic results and showed the presence, at position 203 of our alignment, of the SNP distinct for this species. Six newly generated DNA sequences were deposited in the GenBank database under the accession numbers MH321447-MH321452.For both samples from Liguria, analysis with the N4J8502D/N4N-8944D primer set showed an identity of 99% with Ae. koreicus female specimens were caught at the same sites  as of 28th September and 12th October, respectively. A single female specimen, though visibly damaged but still resembling Ae. koreicus, was caught on 1st September at site GE3, located 5.7 km from the closest positive site GE6. Unfortunately, DNA amplification failed in this case and genetic confirmation could not be achieved. The other species collected in the traps positive for Ae. koreicus in 2016 were: Culex pipiens , Ae. albopictus , Culiseta longiareolata , Culex sp. , and Aedes sp. . The Ae. koreicus female specimens collected in 2016 were not analysed for Flavivirus detection. Following the first Ae. koreicus captures in June–July 2016, one supplementary trapping session using a BG-sentinel trap was performed in August at site GE17, not usually monitored for adult mosquitoes but located in the same quarter of the city; no Ae. koreicus specimen was caught. Potential breeding sites were also searched and inspected at sites GE6 and GE7; they consisted of an abandoned plastic container (GE6) and seven manholes . Only Cx. pipiens and Ae. albopictus larvae were found.Eight Aedes sp. samples  similar to Ae. japonicus/Ae. koreicus in several morphological characters, caught in a BG-sentinel trap located at the Genoa International airport (site GE1) on 3rd and 30th September, respectively. As the male specimen was still preserved, frozen at − 80 °C, a biomolecular assay for the nad4 gene performed as previously described obtained an identity of 99% with sequences of Ae. koreicus, as was determined for the samples collected in 2016.Based on these findings, a retrospective investigation of the 2015 photographic database revealed three damaged Ae. koreicus male individual, included 91 Cx. pipiens and 25 Ae. albopictus. The two damaged Aedes sp. female specimens were negative at biomolecular assays for Flavivirus detection.Site GE1 is located 2.47 km from the closest positive site in 2016 (GE7) . Because the latter site, located at the Flower Market, lies 8.5 km inland from the closest site that tested positive in 2016–2017 (site GE6), genetic analysis was performed to exclude misidentification with the morphologically similar Ae. japonicus. The male individual from GE18 was confirmed as Ae. koreicus by the mtDNA nad4 assay. Furthermore, 33 Ae. koreicus individuals  were trapped at eight sites  between July and October 2017. The other mosquito species collected in the Ae. koreicus-positive traps in 2017 were: Cx. pipiens , Cx. hortensis , Cx. territans , Culex sp. , Ae. albopictus , Cs. longiareolata , Cs. annulata , Aedes (Ochlerotatus) sp. , Anopheles maculipennis , and Anopheles sp. .In 2017, a total of 3436 adult mosquitoes, including 1073 Ae. koreicus specimens, were collected in Genoa. All four sites found positive for Ae. koreicus  were monitored by gravid traps and had already been found positive in previous year (GE6 the two previous years). Other species collected in Ae. koreicus-positive traps in 2018 were: Cx. pipiens , Cx. hortensis , Culex sp. , Ae. albopictus , Cs. longiareolata , Cs. annulata , Anopheles plumbeus  and Anopheles sp. .Between June and October 2018, 5417 mosquitoes, including 41 Ae. koreicus adult specimens were collected in Genoa in the four-year period 2015–2018  tested negative.All female specimens analysed for Aedes sp. eggs were collected in ovitraps in Genoa in 2015, 2016, 2017 and 2018, respectively, and reared at the IZSPLV laboratory. Ovitrap data are reported in Table Ae. albopictus specimens were obtained. Some eggs collected at site GE18 in July and August 2017 appeared unusually shaped on visual inspection, i.e. slightly longer than normal Ae. albopictus eggs; 62 of them hatched and the specimens were identified as Ae. koreicus at the fourth-instar larval stage (n = 8) or at the adult stage . One more adult specimen  was obtained from eggs collected at site GE3 on 27 July.A total of 885, 6397, 12,388 and 10,308 Ae. koreicus was still present at site GE18, located in front of the GEPTX weather station, where the lowest winter temperatures had been recorded. Cumulated rainfall and average temperature vs mosquito trapping data  are reported in Fig. Ae. koreicus were caught during the months with less precipitation preceded by months with higher precipitation.Monthly absolute minimum temperature values recorded for the four-year period 2015–2018 at the three weather stations are presented in Fig. Aedes koreicus in northwest Italy, four years after the species was first detected in northeast Italy. Aedes koreicus seems to have successfully survived three consecutive winters in Genoa. Although one or more re-invasions after winter extinctions cannot be excluded, they seem unlikely since the species has been found at the same sites over several consecutive years, e.g. three years at site GE6.To our knowledge, the present findings represent the first report of the IMS Aedes, for instance Ae. albopictus and Ae. aegypti, stressed the ecological importance of absolute minimum temperatures in limiting expansion of the species [Ae. koreicus in Korea [Experimental studies on other IMS of the genus  species , 33. In in Korea . TemperaAe. koreicus specimens of both sexes. Apparently, the former type was more effective than the BG-sentinel trap, as reported by a previous study in northeast Italy [Ae. koreicus arrival in Liguria, as similarly observed for the detection of Ae. japonicus in the USA [In our study, both trap types, gravid and BG-sentinel, were found effective in trapping st Italy . As no tst Italy . Convers the USA . Use of Ae. koreicus to September 2015. Archives for future investigations can be easily established by preserving male specimens, which are not used for monitoring the circulation of mosquito-borne diseases, as well as female specimens that did not undergo biomolecular assay. Performing genetic analysis to confirm species identity in case of doubtful and/or damaged specimens can also be recommended, especially at sites at high risk of the introduction of IMS.By establishing an archive for retrospective studies, we were able to date back the presence of Ae. koreicus, the average shift of the invaded area centroid in northeast Italy between 2011 and 2014 proceeds at 8 km/year [vice versa (a distance of c.8.5 km). Pontedecimo and the city centre are connected by railway, roadway and highway. As road traffic can play a role in the long-range dispersal of IMS [Ae. koreicus has been documented since 2011 and its range is still expanding, cannot be ruled out. However, given the presence of an international airport and a very busy commercial port, any of these other areas may represent the first site of introduction. Interestingly, however, no other Ae. koreicus specimens were found at the airport site (GE1) after September 2015.Regarding the dispersal of  km/year . In Genol of IMS , introduAe. albopictus calculated an average total dispersal distance of 3.6–4.6 km/year/generation in Italy, with a passive dispersal component of 2.8–4.1 km/year/generation [Ae. koreicus in Europe remains unknown. However, a laboratory-based study under different temperature conditions performed on specimens of the ecologically similar Ae. japonicus japonicus collected in Germany calculated an average of 4.72 potential generations per year [Ae. koreicus, we estimate a theoretical average total dispersal distance of 17.0–21.7 km/year in favourable conditions.A study on neration . The numper year . Should Ae. koreicus and Ae. albopictus vs climatic data. To allow visual comparison of the data trends, trapping data are not given to scale: Ae. koreicus data are shown 10-fold higher and Ae. albopictus 10-fold lower than the actual values.Figure Aedes koreicus trapping data in 2016–2018 followed a bimodal trend, unlike the congeneric Ae. albopictus, although there was no difference in the trapping set up for the two species  and in July 2018 (one trap night only at site GE6)  Table . HoweverAe. albopictus and Ae. koreicus under natural conditions needs to be investigated. In a laboratory-based study, weak larval competition was observed, with a slight advantage of the former owing to their faster development [Aedes koreicus seems to take advantage of higher altitudes and lower temperatures, as noted for northeast Italy, where its presence has been recorded at elevations up to 1250 masl [Ae. koreicus were also positive for Ae. albopictus. However, as all the sites monitored during this study were located at less than 100 masl, colonization at higher elevations by Ae. koreicus in the absence of Ae. albopictus cannot be ruled out.Concerning interspecific interactions, larval competition between elopment . Aedes k250 masl . All sitAe. koreicus was detected during our study; this might be explained by the low density of the species in the sampling area and the consequent low encounter rate with infected hosts.Finally, no flaviviral infection in Ae. koreicus in Liguria. This is, to our knowledge, the first report of the species in the area, and in a port city in the Mediterranean basin. So far, this invasive mosquito species appears to be present at low densities in most of the urban area of Genoa. Both morphological features and genetic data support a common origin for the Ligurian and most of the other European populations; however, the ways of entry of this species in Europe remain unknown. Future in-depth genetic analysis, including short tandem repeat (STR) genotyping, would help to determine the exact origin of the European populations and their dispersal pathways.Entomological surveillance of sites at risk in northwest Italy allowed for the early detection of the IMS Ae. koreicus adults and eggs at the Flower Market in 2017, which lies inland more than 8 km from the closest positive site in 2016 and 2017, but was not monitored for adult specimens in the previous years, raises questions about how the species was introduced in Liguria and how much of the area is already invaded, which might be much greater than observed so far. To date, however, no other monitored sites throughout Liguria have been found positive for the species. Although multiple introduction events cannot be excluded, Ae. koreicus seems to have overwintered at least three times in the city and has become established in key areas. There were clear indications of species expansion in the city in 2017. Regarding monitoring tools, ovitraps were less effective for monitoring the species than the traps for adult mosquitoes. Although all Ae. koreicus pools analyzed were negative for flaviviruses, virological surveillance on this IMS still makes sense, given its potential to act as a vector of mosquito-borne diseases. Mosquito surveillance in Liguria, with a particular focus on Genoa city, will be continued in 2019. Given the importance of Genoa as a commercial and tourism hub, further and accelerated spread of the species in Italy and beyond can be expected, as was observed for the Asian tiger mosquito Ae. albopictus. Unfortunately, no control measures have been deployed or are foreseen to eradicate the species or slow down its expansion.In Genoa, the species was first detected in September 2015 in the area of the international airport, which is located near the commercial port. Either the former or the latter might be the site of introduction, but this cannot be demonstrated. The finding of


This study was conducted with the aim of evaluating the genetic variability of Polish national goose breeds, using polymorphism of 15 microsatellite markers. The results revealed a highly mixed genotype of all the examined geese, suggesting that breeds cannot be distinguished from each other on the basis of microsatellite markers.® goose and 12 conservative flocks: Kielecka, Podkarpacka, Garbonosa, Pomerian, Rypinska, Landes, Lubelska, Suwalska, Kartuska, Romanska, Slowacka, and Kubanska, maintained in Poland using microsatellite data. The genetic diversity of geese kept in Poland remains poorly analyzed at the molecular level. In total 392 samples were examined with the usage of 15 microsatellite markers. 119 alleles were identified and the number of alleles per locus ranged from 1 to 13. The highest number of alleles was observed in TTUCG5 (16) and the lowest in CAUD-G007 (2), while CKW47 was monomorphic. The lowest value of expected heterozygosity (He) was observed in Landes, while the highest in Romanska. Similarly, the observed heterozygosity (Ho) was the lowest in Landes but the highest in Kartuska. The polymorphism information content (PIC) indicates loci TTUCG5 as the most valuable microsatellite marker among those examined. The Structure software was used for the first time to identify goose populations, revealing high admixture between breeds and their close genetic propinquity. Moreover, the presented panel of microsatellite markers remained polymorphic and is useful for population studies of geese and assessment of genetic diversity.The aim of this study was to evaluate the genetic variability of the White Kołuda This breed represents 90% of the goose population bred in Poland. It was selected to enhance meatiness and reproduction traits, but also to improve resistance to diseases [® goose is consumed worldwide, while the plumage is commonly used in production of high quality clothes, pillows, and duvets. At the same time, it constitutes a common object of falsification during production.Nowadays, monitoring of the genetic diversity of many species is based mainly on analyses obtained by advanced molecular methods. The information about population structures and variety is crucial to choose an appropriate conservation and management breeding program for species maintained in each country . Anserifdiseases . The meaAnser anser) [Branta canadensis L.) [Anser cygnoides L.) [Anser albifrons) [Anser brachyrhnchus) [The genetic variability of domestic poultry based on DNA markers has been described by several papers, but generally avian species exhibit a low level of divergence at the molecular level . Microsar anser) , Canada nsis L.) , swan goides L.) , white-fbifrons) , and pinrhnchus) . Moreoverhnchus) ,13,14,15rhnchus) , and Slorhnchus) , which arhnchus) ,19. The rhnchus) ,21. Amonrhnchus) . The aim® goose and 12 conservative geese flocks: Kielecka (Ki), Podkarpacka (Pd), Garbonosa (Ga), Pomerian (Po), Rypinska (Ry), Landes (La), Lubelska (Lu), wSuwalska (Su), Kartuska (Ka), Romanska (Ro), Slowacka (Sl), and Kubanska (Ku), maintained in the National Research Institute of Animal Production, Department of Water Fowl Breeding in Kołuda Wielka and Dworzyska. Ethical approval is not needed for research on plumage samples, while sourced blood was collected during routine slaughter of geese in Kołuda Wielka (statutory activity No. 04-011.1).The experimental material was collected from the White Kołuda® goose) and additionally from 96 blood samples of the White Kołuda® goose . DNA isolation was performed with the use of the Sherlock AX Isolation KIT  according to the instructions provided in the protocol.The DNA was isolated from 300 plumage samples   and analyzed by PCR reaction using labelled primers with one of four dyes: 6-FAM, VIC, NED, and PET, presented in The multiplex PCR was carried out on 20 ng of genomic DNA in two multiplex sets of primers and performed on a Veriti Thermal Cycler  (Mix 1 (7plex): Bca µ8, Ans02, Ans18, Ans25, Aal µ1, CAUD-G012, Ans07; Mix 2 (8plex): Bca µ1, TTUCG5, CKW21, Bca µ9, CAUD-G013, CAUD-G007, CKW47, Afa35). The amplification protocol comprised initial denaturation and enzyme activation at 95 °C (5 min), followed by 29 cycles of denaturation at 95 °C (30 sec), primer annealing at temperature 55 °C and 58 °C (3 min), extension at 72 °C (30 sec), and final extension at 72 °C (5 min). Afterwards, products of PCR were separated in polyacrylamide gel performed on a 3130xl Genetic Analyzer . The allelic sizes of all loci were estimated relative to the in-line 500 LIZ Size Standard marker. The results were genotyped in GeneMapper 4.0 .o) and expected heterozygosity (He) for mentioned loci and populations of geese. Moreover, we used it to compute the fixation index (FST). Departures from the Hardy–Weinberg equilibrium (HWE) were estimated in GENEPOP 4.2, while Arequin 3.11 software was used to calculate analysis of molecular variance (AMOVA) in order to evaluate the genetic variance in the populations and between them. Our own statistical program IMGBOVSTAT IZOO PIB was used to calculate polymorphic information content (PIC), estimated according to Botstein et al. [GenAIEx 6 software was used to obtain allele frequencies, standard diversity indices , as well as observed , whereas Garbonosa (2.714) and Rypinska (2.714) were the lowest  and CKW21 (15) and the lowest in CAUD-G007 (3). The population of White Kołudae lowest .o was observed for Kartuska (0.479) and Romanska (0.415), while the lowest was computed for Landes (0.280). Romanska (0.638) and Kartuska (0.620) showed the highest values of He, whereas Landes (0.305) has the lowest value of this coefficient. The average value of He was 0.447 in the analyzed population  was 3.941 and the average number of effective alleles (Ne) per locus ranged from 1.800 (Rypinska) to 3.041 (Romanska). The mean value of observed heterozygosity was 0.361 per tested goose breed, the highest Hpulation . The nulST values for each locus are shown in ST values for examined populations are shown in ST was observed in Landes (0.080) and the lowest in Romanska breed (0.068). PIC values obtained in this study ranged from 0.165 (CAUD-G007) to 0.813 (TTUCG5) with an overall average of 0.463 (The Fof 0.463 .No deviations from HWE of examined microsatellite loci across the population were detected.p < 0.05) and 7.5% was distributed among them. In AMOVA analysis we obtained a fixation index amounting to 0.075.According to AMOVA analysis, 92.5% of the total genetic variance was distributed within populations  and significantly greater than other breeds. Moreover Rypinska and Romanska was also significantly larger (0.233). The rest of the FST index among breeds was characterized by medium values. We presume Romanska geese perform the highest differentiation among those examined breeds.We have also conducted a Fanalysis . The FSTST pairwise analysis. The rest of the breeds are grouped close to each other.Principal component analysis (PCA) is shown plotted on Waterfowl represent a diverse group of birds which are intensively examined worldwide. Investigation of the genetic diversity of goose breeds using modern methods of molecular genetics can be a great support in the development of goose breeding programs and conservation of old local breeds’ purity. The identification of breeds’ genetic diversity and genetic uniqueness is applicable in breeding of animals and is becoming essential nowadays.® goose. Generally, we observed a similar level of polymorphism in analyzed loci as previously reported in literature. In our study, the most polymorphic loci were TTUCG5 and CKW21; we observed 16 and 15 different alleles in all analyzed breeds. Accordingly, these loci displayed the highest PIC values. Similar results were obtained by Parada et al. [o were observed in Bca µ1 locus, which in our study displayed intermediate polymorphism. The same number of alleles (four) were observed in Bca µ8 according to our studies and Andres et al. [® breed, while in Rypinska, Pomerian, Landes, Podkarpacka, and Slovacka only one allele was monomorphic. However, the number of White Kołuda® individuals was higher than other breeds, so that the probability of private alleles increases. According to Barker [We analyzed 14 microsatellite loci tested previously and proved to be polymorphic: in Polish local breeds  and European breeds  ,24,25. Mo Barker , the micIt is accepted that the value of polymorphism information content should be above 0.5, which indicates the most informative markers in population. Moderately informative markers are those between PIC value 0.25–0.5, while low informative are those under 0.25 . PIC in o = 0.35, He = 0.38) and to the wild graylag geese where the observed and expected heterozygosity were 0.36 and 0.42, respectively [o value is TTUCG5, as was obtained in our study [One of the most important coefficients estimating genetic variability in the population is heterozygosity. The average observed heterozygosity of the populations was 0.361, ranging from 0.119 (Afa35) to 0.721 (TTUCG5), while the expected overall polymorphic loci was 0.447, which corresponds to results obtained by Andres et al. [ur study . The meaur study ,24. To cST pairwise ; however, two breeds have a different ancestor—Anser cygnoides (Garbonosa and Kubanska) [Anser anser and Anser cygnoides [® are reported to have whole body white plumage. White and speckled grey or brown plumage occur in Garbonosa, Kartuska, Podkarpacka, Rypinska, Suwalska, Kubanska, and Landes [The Structure analysis revealed that the most probable number of subpopulations in analyzed breeds is 13 , which ipairwise ) do not ribution . The majubanska)  and theiubanska) . Moreoveubanska)  and the ubanska) . Wrzaszcygnoides . Anotherygnoides . This mad Landes . However® goose constitutes 98% of the goose population bred in Poland [® goose progresses, the diversity within it will decrease, the diversity among breeds will increase, and this breed will create a separate genetic population. On the other hand, the high variability within the breed is a favorable phenomenon, indicating the high selection potential of this breed. In conclusion, we carried out the first analysis of the genetic variability of geese maintained in Poland based on Structure analysis. It has indicated that geese bred in Poland do not form separate populations in genetic terms and are characterized by a high level of mixing genotypes at the STR locus.The White Kołudan Poland  and was


Conservation of agrobiodiversity is a major concern worldwide. Several strategies have been designed and programmed to reduce biodiversity erosion due to anthropic and non-anthropic causes. To this end, we set up a multidisciplinary approach based on the genetic analysis of selected cultivars and recognition of the environmental parameters. We genotyped the sweet cherry cultivars of Campania region in southern Italy by using simple sequence repeats and further investigated them by cluster analysis, disclosing a homogeneous genetic constitution, different from that of commercial accessions. By structure analysis we identified three distinct genetic clusters, each characterized by common and distinct alleles. Survey of the cultivars’ geographical distribution by quartic kernel function identified four preferred districts further characterized for soil origin, pedologic, agronomic features and urbanization impact. We correlated these environmental parameters, typical of the identified areas, with the three genetic pools and found a statistically significant association for each cluster. When we overlaid the cultivation traditions and cultural heritage, we found they have a dominant role; on these premises, we generated new territorial maps. In conclusion, we propose a novel methodological approach based on molecular, geo-pedological and cultural parameters with the aim to recognize biocultural refugia and preserve endangered or valuable cultivars. Over the centuries, farmers have deliberately selected and preferentially cultivated certain cultivars due to their fruit qualities (genes/phenotypes) and their adaptation to specific habitats. The territories, where this selection was practiced, were generally confined and characterized by geomorphological and environmental features that guaranteed context specificity and characteristics so that a specific cultivar can be defined typical or autochthonous. The so-called “local varieties” are, therefore, a significant component of agro-biodiversity4 have emphasized on traditional cultivars being one of the main sources of biodiversity, therefore the access to germplasm should be one of the pillars for sustainable agricultural development7. Traditional cultivars, however, have been reported to have a reduced, if any, market value and relegated to a marginal role; it could be argued, instead, that their absolute value is much higher than the sole monetary one4. In line with this reasoning, numerous international institutions and individual countries have developed a conservation-oriented strategy that involves the recognition, identification and conservation of traditional endangered varieties9. Their survey is a crucial goal to be pursued because loss of autochthonous cultivars is an indicator of biodiversity erosion that can lead to complete extinction of that variety and, ultimately, of the entire territory features10. In order to design appropriate conservation and management strategies, it is mandatory to acquire information on the genetic characteristics of the cultivars under investigation and relatedness among them14. This can be obtained through a specific “DNA fingerprinting” that can be used for traceability and for selecting diverse individuals with desired quality traits as breeding parents6. A molecular tool largely employed to detect such a genetic signature is represented by Simple Sequence Repeats (SSRs), recognized as useful genetic markers in plants and in animals due to their high degree of polymorphism, abundance in genomes, co-dominance and suitability for automation15. Conservation strategies, then, recognize, on one side, its absolute value in terms of biological and cultural heritage and, on the other, imply and justify its potential use in agricultural future programs17.Several authorsPrunus avium L.) is definitely a traditional culture, as evidenced by historical sources; its presence dates back to Pliny the Elder (I century A. C.), who described ten varieties and, since, it has always been a hallmark of the rural environment of this region18. Sweet cherry is a self-incompatible, out-breeding diploid species in the family of Rosaceae, having a genome of 2n = 16. Precise identification of the existing cultivars is essential for orchard establishment, efficient germplasm collection management and selection of genotypes in cherry breeding programs. In Prunus, microsatellites have been used for germplasm characterization19 and management20, determination of genetic diversity21, parentage analysis22, cultivar identification23 and mapping genetic linkage24. The growing demography and the continuous consumption of soil in many areas of the Campania region has reduced the natural agricultural locations with subsequent loss of certain varieties and traditional techniques of cultivation and conservation that were selected for a territorial vocation. In this paper, we analysed the genetic characteristics of several Campania sweet cherry cultivars and correlated these data with local territory features and urban settlements to generate a novel type of environmental map that could help in reducing the risk of extinction and preserving these habitats as “niche” or “biocultural refugia”27.Campania Region is notoriously recognized as an area with a strong agricultural tradition starting from the Roman civilization times (the famous “Campania Felix”). Furthermore, Campania displays very diversified environmental and phytoclimatic characteristics that contribute to the formation of particular agro-pedo-environmental contexts so to permit specialized and selected cultivation traditions. It is clear, then, that the combination of such a diversity and traditions has produced over the centuries many specialties with a high degree of biodiversity. In Campania, sweet cherry 31 and plums (0.77 by Šiško)32 using equivalent SSR markers. A lower level of sweet cherry polymorphism has been detected by Stockinger et al.33 and Gerlach & Stoesser34 using RAPD markers and by Beaver et al.35 and Bošković & Tobutt36 using isozyme markers. This finding probably reflects: (i) a higher polymorphic sensitivity of the present SSRs compared to those reported in published works; (ii) a better outbreeding degree of the cultivars that is an index of the population structure analysed. In addition, we identified 26 private alleles (P.A.), 1.733 for each locus, with the private/total alleles richness ratio (ARR) that clearly indicated a high percentage of selective ability , except for EMPA001, EMPAs02, EMPAs13 and EMPAs01 that gave no private alleles. Finally, the estimated frequency of null alleles was close to zero for 12 out of 15 loci , with some of them slightly negative . Furthermore, a locus with a large positive estimate of null allele frequency indicates an excess of homozygotes but does not necessarily imply the presence of a null allele, as shown for EMPA015 (0.289). These results indicate that the loci identified and the primers used have a high discrimination power for each cultivar within the entire population. Finally, we analysed whether our population is in a Hardy-Weinberg equilibrium by calculating the Inbreeding coefficient (Fis) and the Fixation Index (Fst). Fis negative values reflect high heterozygosity and a Fixation Index (Fst) above 0.25 for all loci, indicate genetic differentiation among subpopulations. Moreover, Fit (Fitness), indicates heterozygosity reduction for each individual and ranges from −1 to +1, with the highest value corresponding to the lowest heterozygosity within the entire population. In our case, Fit was close to 0 for 12 out of 15 loci.The analysis of the 155 Campania’s sweet cherry samples (N), belonging to the 99 putative autochthonous cultivars, identified 110 distinct alleles Table . The allP. avium (true K) and subsequently evaluate it as reported by Evanno et al.37. This model assumes that unknown K ancestral populations are at both Hardy-Weinberg and linkage equilibrium38 and, nonetheless, all individuals are probabilistically assigned to clusters or connected to each of several clusters if their genotypes are mixed. Under the admixture model of genetic rearrangements, an individual’s probability of assignment to each cluster (q) can be interpreted as the proportion of that individual’s genome that originated from each cluster /Giulia (Carinola), Lettere/Lauretana, Moscarella/Montenero, Mazzetti di Maggio/Marfatana, Cirio/Ciauzara, Campanarella/Campanara, Bertiello/Aspra, Antuono/Agostina; Cluster 2: San Michele/San Giorgio, Maggiaiola/Limoncella, Maiatica di Taurasi/Maggiaiolella, Cerasa Uva/Cerasa bianca, Zuccarenella/Torano, Culacchia/Corvina, Corona/Corniale, the two Biotipo (1/2), Pagliaccio Bianca/Pagliarella, Paccona/Paesanella, Napoletana/ Nera dura di Mugnano; Cluster 3: Sciazza/Sbarbato, Palermitana/Passaguai, San Pietro/Sangue di bue, Spernazza/Spernocchia del vallo di Lauro, Imperatore/Imperiale bianca, Imperiale nera/Lattacci, Cuore/Della calce, Cervina/Cervone, Murana/Muzzecata, Mulegnana nera/Mulegnana riccia, Del Monte/Donna Luisa, Durona del Monte/Falsa del Monte. The three clusters account for 54% of total Campania’s sweet cherry cultivars.The genotypes of 12 cultivars account for 10.5%, suggesting they are clones derived from an ancestral variety [5% < genetic distance rate (gdr) <10%], Tentolella/Tenta di Serino, Biotipo 3 belongs to the other two; Sant’Anna/ Sant’Antonio with Santa Teresa; Chiacchierona/Chiapparella; Don Vincenzo with Del Monte/Donna Luisa, Formicola/Gambacorta.The remaining cultivars, not listed above, exhibit a unique identity and account for 35.5% of total accessions.We analysed our population also with the Neighbour Joining method and recognized three major related groups, strongly supporting the results obtained with the STRUCTURE analysis as shown by the dendrogram in Fig. P. avium cultivars investigated here. They represent true genetic structures as deduced by the presence of highly assigned individuals to each cluster and by the biologically meaningful clustering of individuals within accessions. By applying different methodological approaches, we can assign the 99 sweet cherry varieties analysed to three distinct gene pools, each characterized by distinct and common genetic traits.All together these data indicate that we can identify three distinct genetic clusters among the Thereafter, we assessed the cultivars’ spatial density using a quartic kernel function to calculate the density of sampling point features. This analysis highlighted four hotspots: the Marano area, the Roccamonfina region , the Carinola district and the Irno valley Fig. . We alsoEach of the four hotspots was further analysed for the soil origin according to the World Reference Base international standard for soil classification system endorsed by the International Union of Soil Sciences Fig. . We founQuercus pubescens Willd prevailing. The Roccamonfina region’s soil is part of the volcano’s caldera, includes the flat pedestrian areas and is deep with a moderately coarse texture without limestone. The land is typically used for fruit crops. The ecomosaic is very interesting because specialized cherry and chestnut trees orchards are interspersed with chestnut coppices and mesophilous Mediterranean woods with prevalence of Quercus pubescens Willd and Quecus ilex L. The Marano (and Chiaiano) district’s soil originates from the volcanic system of Campi Flegrei, is very deep with good permeability, has a moderate coarse texture and a fairly low pH. Limestone is absent. The ecomosaic is dramatically modified due to a massive urbanization from the city of Naples and restricted to slope lands towards Marano and Chiaiano where chestnut coppices are interspersed with mixed orchards with a prevalence of very valuable cherry cultivars. Because of the traditional and economic value of these orchards, the area is protected within the metropolitan park. Finally, the Irno valley’s soil is deep with medium to moderate fine texture, moderately alkaline pH, non-calcareous, with high base-cation saturation ratio , but also on soil’s physical structure or texture. This, in fact, affects cherry trees distribution as it strongly influences soil hydrology  and possibly guides selection of specific types of trees to place in orchards. The cherry trees prefer sunny, damp clayey soils, without water stagnation and, in fact, in typical cherry districts, the cation-exchange capacity is primarily due to the presence of pyroclastic soils and high amount of organic matter, factors that improve the agricultural quality of cherry tree soils. More specifically, the Carinola district soil, as part of internal volcanic plains, is moderately deep, with medium texture that ensures good permeability, a typical requirement for sweet cherry cultivation. The soil pH is slightly to moderately alkaline, with a good fertility due to cation-exchange capacity and to the high base-cation saturation ratio, ensuring a good amount of K, Ca and Mg adsorbed on colloids Table . The ecoio Table . Also in40. We found a positive and significant correlation between geographical and genetic distances   as well as by anthropic factors, critical parameters for their propagation. Indeed, sweet cherries of Cluster 1 (C1) are preferentially distributed and cultivated over a soil with volcanic sandy clay loam (black) or enriched on sand with silty gravel (gray). Sweet cherries of Cluster 2 (C2) are also distributed over a soil of volcanic origin . The optimal layer of sweet cherries Cluster 3 (C3) is, instead, characterized by loam soils  with the corresponding geographical distribution (latitude/longitude) by performing a Mantel Test using GenAlEx 6.41 software01) Fig.  indicatisee Fig. . This ty43. In fact, the chemical-physical properties, the taste and flavour of these cultivars, their ability to resist to pathogens and productivity in terms of crop yield and farmers’ income are unique to the identified areas and cannot be or can be only partially reproduced in other contexts. A typical example is represented by the famous red pulp varieties  rich in anthocyanidines, likely because of their own substrates specificities.Another result of this latter correlation is that the sweet cherry orchards are located into urban or suburban areas with prevalent human activities that date back to the Greek and Roman civilization times. The Marano area corresponds to “Campi Flegrei” where the Greek immigrants landed in Italy and settled their first locations. It also corresponds to where the cities of Cuma and Puteoli flourished during the Roman times, likely because of the fertile land and good climate. The Roccamonfina volcanic area was the place where the pre-Roman inhabitants settled their communities, presumably for the same reasons as for the Irno valley, which was colonized because of soil fertility, proximity to water and gentle climate. Of note, these initial settings persisted over the centuries because agriculture has been the main source of food and income. Even today it is still possible to relate selected and typical cultivars with well-identified areas that, with good reason, can be defined “niches” or “biocultural refugia”Finally, we took into account the cultural heritage and cultivation traditions of the identified hotspots and found they play a crucial role in the cultivars’ selection so to overwhelm many of other features. These considerations imply that behind the choice of a selected cultivar there are genetic, bioclimatic, geo-pedological, cultural and traditional cultivation factors. We overlaid all these data to generate a new type of territorial map that provides sufficient information density at the scale of interest with the advantage of having unit boundaries based on the mentioned criteria and not solely on administrative ones as were the thematic maps of the Regional Territorial Plan (PTR).Collectively, these data indicate that the genetic constitution of the Campania sweet cherry cultivars analysed correlates not only with the spatial and geographical distribution, with the soil and pedologic features but also with the cultural heritage of the cultivation areas.30.In this study, we employed a multidisciplinary approach that combines molecular/genetic, environmental and geo-pedological parameters to characterize the sweet cherry populations of the Campania region located in Southern Italy. We chose this region because there is a long-lasting tradition of sweet cherry cultivation that dates back to the Roman times and because, as from the eighteen century, some areas were dedicated uniquely or mostly to this crop. Survey of the genetic signature of the local varieties identified three major groups, each comprising cultivars characterized by common and domestic genetic features. Only few studies have been carried out so far to analyse the genetic constitution and structure of sweet cherry populations in general and of the Campania’s cultivars in particular. Our data indicate that these cultivars show a defined and wide genetic differentiation as compared with reference cultivars. The existence of genetic diversity in a given population underlines the plasticity of the genetic material and its ability to best accommodate to the environmental conditions and to reprogram the metabolism to local available resources. Moreover, the SSR markers employed result effective in differentiating cultivars and the data are consistent with those previously and independently reportedThe three genetic clusters identified positively correlate with spatial distribution and soil, geo-pedologic and environmental parameters. Interestingly, each gene pool exhibits a preferential distribution over the major hotspots identified by the spatial density analysis. Indeed, two areas (Marano and Roccamonfina) have a volcanic origin and share some common features as one derives from the Campi Flegrei caldera and the other from the more distinct and distant Roccamonfina region, likely generated from a different volcano. While gene clusters 1 and 2 are preferentially distributed over these two areas, cluster 3 appears to have as site of election the Irno valley that has a completely different soil and environmental composition. The cultivation traditions of the identified areas originating from different cultural backgrounds provide a higher level of complexity and, for some aspects, overwhelm other considered parameters.Taking into account all these criteria, we generated a new map based on genetic/molecular, ecological and environmental data and not only or exclusively on soil composition or administrative criteria as most of those presently available. Our map may be a powerful tool for conservation and management strategies to preserve biodiversity, a topic that is acquiring growing interest as it is constantly endangered or eroded by anthropic and non-anthropic causes. As a result, we may lose useful and critical traits, as those related to resistance to parasites, tolerance to extreme temperature or to complete or partial water loss, the first steps towards complete extinction of that population. Our map may also help to stimulate specific productions in selected areas to ensure their quality and characteristics and may be a support for new strategies to select distinct areas as “niches” or “biocultural refugia”. The derived products combine genetic backgrounds with specific neighborhoods, support the sustainability of certain cultivars and provide an added value on the market.44 and genotyped with a set of fifteen microsatellite primers pairs developed from P. avium. Eight primer sets were isolated by enrichment from P. avium “Napoleon”29 and seven identified from a P. avium “Charger” genomic DNA library28. The selected microsatellites map to seven of the eight linkage groups of the P. avium “Napoleon” x Prunus nipponica map as reported in Supplementary Table S145. Fifty ng of each template DNA was subsequently subjected to PCR amplification in a total volume of 20 µl containing 0.2 mmol/L dNTPs, 10 mmol/L Tris–HCl (pH 9.0), 0.3 Units of AmpliTaq Gold PCR Mastermix , 0.3 µmol µl each primer. The PCR conditions were: 95 °C for 5 min followed by 40 cycles of 95 °C for 50 s, annealing temperature for 1 min, 72 °C for 50 s, and a final cycle of 72 °C for 7 min. All forward primers were labeled with the fluorescent dyes   and PCR products analyzed using an ABI 3100 genetic analyser  following the manufacturer’s instructions; GeneScan 500-ROX  was used as internal size standard. Data were collected and allele size determined using the Peak Scanner™ v.1.2 software .Genomic DNA was extracted from 80 ng of young leaf tissue with a cetytrimethylammonium bromide based methodhttp://www.fieldgenetics.com/pages/home.jsp, Tristan Marshall 1998–2007). A model-based Bayesian clustering method, implemented in the program STRUCTURE version 2.3.438, was used to elucidate the genetic variations and identify the number of genetically distinct gene clusters within P. avium. The program STRUCTURE identifies K clusters of individuals based on the multiloci genotypes of all sampled accessions. STRUCTURE was run twice on the total set of 155 distinct genotypes: in the first run, with a burning period from 5*103 to 5*104 Markov chain Monte Carlo replications, the ΔK ranged between 1 and 25; in the second run, with a burning period from 5*105 to 7.5*105 Markov chain Monte Carlo replications, the ΔK ranged between 1 and 10. The admixture model, which aestimates the fraction of ancestry from each cluster for each individual, was used and the analyses run with the correlated allele frequencies46. The appropriate K value was chosen as reported by Evanno et al.37. The ∆K formula is given by the following:Allele numbers, expected (He) and observed (Ho) heterozigosity, Polymorphic Index Content (PIC), and frequency of null alleles (F-null) were calculated using the CERVUS 3.0.3 software  was evaluated dividing Private Alleles (P.A.) by Total Alleles (T.A.) for each locus. The genetic relationships among genotypes, Fis (Inbreeding Coefficient), Fit (Fitness) and Fst (Fixation Index) were estimated by the Nei index48 using the GenAlEx 6.41 software40, [http://www.anu.edu.au/BoZo/GenAlEx/]. A dendrogram was generated based on the neighboring joining NJ, using MEGA v.7 software through which a genetic distance matrix was obtained49.Power of Discrimination (PD) was calculated as described by Kloosterman phytological and pedological aspects that affect production’s potentials;dominant agricultural and forestry uses;forms and structures of the agricultural landscape and their evolution during the last fifty years;relations with the urban and infrastructural system.Campania Region was divided into homogeneous areas that best represent the main environmental and landscape characteristics of the different territories, as defined by the environmental and agroforestry thematic maps contained in the Regional Territorial Plan (PTR) . In particular, twenty-eight Campania Rural Territorial Systems were identified upon assembling reasonably homogeneous municipal territories according to:50.The resulting rural systems tend to correspond, on a regional scale, to the main emerging ecogeographic and landscape units, such as Matese, Piana Campana, Volcanic System of Somma-Vesuvio, Cilento Costiera and others, even though the unit boundaries were defined on administrative rather than ecological criteriaad hoc forms during farmers’ interviews, explored available literature on the history of agriculture and election areas and, finally, reviewed all reported investigations carried out on the Campania Region genetic bank by other institutions. All accessions were additionally described and identified by morphological standard descriptors52. Fourteen additional sweet cherry accessions from different countries were obtained from the repository of the Fruit Tree Research Institute, Forlì, Italy and used as international references. The complete list of the cultivars investigated is shown in Table The sweet cherry cultivars distributed over the entire Campania territory were surveyed during years 2013–2016 to have a complete catalogue of the existing cultivars, recognize those threatened by the risk of extinction and characterize them at molecular/genetic level. Data were collected by specialized technicians who filled 53. The geographic database included accessions’ descriptors and locations, climatic, geologic and pedologic data obtained by Italy phytoclimatic and geologic maps  and Campania pedologic maps . Spatial overlay allowed to associate each accession to the pertaining bioclimate and soil composition. Accession’s spatial density was assessed using kernel function, specifically, the quartic kernel function described in Silverman54. Conceptually, each point, representing a single accession, was fitted with a smoothly curved surface with the highest value at the point location and diminishing values at increasing distance reaching zero at the search radius distance from the point. The search radius was defined using the default algorithm provided by the software. The output is a raster having a density at each cell calculated by adding the values of all the kernel surfaces where they overlay the cell centre.Spatial data were organized and processed in a G.I.S. environment, using ESRI ArcGIS 10.2.2 softwareSupplementary Information


In a recent publication Tom Douglas and Katrien Devolder have proposed a new account of genetic parenthood, building on the work of Heidi Mertes. Douglas and Devolder’s account aims to solve, among other things, the question of who are the genetic parents of an individual created through somatic cell nuclear transfer (i.e. cloning): (a) the nuclear DNA provider or (b) the progenitors of the nuclear DNA provider. Such a question cannot be answered by simply appealing to the folk account of genetic parenthood, according to which the genetic parents of an individual are those individuals who produced the egg and sperm, respectively, which fused to create the embryo. It cannot be so as in cloning there is no fertilization as such. In this article I critically examine Douglas and Devolder’s new account of genetic parenthood and demonstrate that it is vulnerable to counterexamples that exploit the lack of a condition specifying that genetic parents should cause a child’s coming into existence. A., Dinnyes, A., King, T. J., Paterson, L. A. … Young, L. E. (2002). Somatic cell nuclear transfer.  I say a nearly identical genetic copy because whereas the totality of the nuclear DNA would come from the nuclear DNA provider, the zygote’s mitochondrial DNA would most certainly not come from said nuclear DNA provider, or the provider’s maternal line. This is the case as in mammals mitochondria are matrilineally transmitted.2Proceedings of the National Academy of Sciences of the United States of America. 115(51), 13039–13044; Schwartz, M., & Vissing, J. (2002). Paternal inheritance of mitochondrial DNA. New England Journal of Medicine, 347(8), 576–580.It is very uncommon for paternal mitochondria to be incorporated into the zygote. Luo, S., Valencia, C. A., Zhang, J., Lee, N. C., Slone, J., Gui, B., … Huang, T. (2018). Biparental inheritance of mitochondrial DNA in humans.  For the clone to be an identical genetic copy, sensu stricto, of the nuclear DNA provider the latter, or someone from their maternal line, should also provide the would‐be enucleated egg that in turn contains the mitochondria.Dolly the sheep is probably the most famous sheep in the world, and she is rightly so as she was the first mammal produced via cloning. In cloning the nucleus of a somatic cell is transferred into an enucleated oocyte (i.e. an oocyte whose nucleus has been previously removed), and then it is activated by external means. If everything goes according to plan the cell will begin to divide, the embryo will be transferred into a womb  and then, after some time, an ‘nearly identical genetic copy’ of the individual who provided the somatic cell (i.e. the nuclear DNA provider) will be born.could be cloned, and if so whether it would be morally permissible to do so.3The Stanford encyclopedia of philosophy. Stanford, CA: Stanford University. https://plato.stanford.edu/entries/cloning/Devolder, K. (2017). Cloning. In Zalta, E. N. (Ed.).  Broadly speaking, two positions emerged. On the one had there are those who argue that it would be immoral to clone human beings, and on the other hand there are those who argue that under certain circumstances it would be morally permissible to do so. An example of the former is Leon Kass: ‘Mass‐scale cloning of the same individual makes the point vividly; but the violation of human equality, freedom, and dignity is present even in a single planned clone’.4Valparaiso University Law Review, 32(2), 697.Kass, L. R. (1998). The wisdom of repugnance: Why we should ban the cloning of humans.  An example of the latter is Carson Strong, who argued that in certain circumstances it would be ethical for infertile couples to resort to cloning, as a way of having kin that were genetically related to one of them.5Cambridge Quarterly of Healthcare Ethics, 7(3), 279–293.Strong, C. (1998). Cloning and infertility. After the birth of Dolly scientists around the world started to try to clone other mammals, and up to this date cats, coyotes, camels, dogs, goats, horses, mice, monkeys, pigs, rabbits and rats have already been cloned. Furthermore, one consequence of Dolly’s birth was that people got even more interested in the question of whether human beings does not fit our folk conception of genetic parenthood. According to this folk conception, the person who provided the egg and the person who provided the sperm, which fused and created an embryo, are the genetic parents of the created embryo. Cloning is problematic because in it no sperm and egg fuse, and thus the question of who are the genetic parents of any given clone arise: (a) the person who provided the nuclear DNA, or (b) the progenitors of the person who provided the nuclear DNA. Interestingly, Leon Kass noticed that reproductive cloning complicated our traditional understanding of human reproduction: ‘Asexual reproduction, which produces “single‐parent” offspring, is a radical departure from the natural human way, confounding all normal understandings of father, mother, sibling, grandparent, etc., and all moral relations tied thereto.’6Kass, op. cit., note 4, p. 690.One issue that becomes patent when we reflect on the possibly of employing human cloning for ‘reproductive purposes’ is that cloning 7Journal of Medical Ethics, 40(11), 744–447.Mertes, H. (2014). Gamete derivation from stem cells: Revisiting the concept of genetic parenthood.  aims to solve the question of who are the genetic parents of an individual created through cloning. They defend the view that the progenitors of the nuclear DNA provider are the clone’s genetic parents. In this article I critically examine Douglas and Devolder’s new account of genetic parenthood. Firstly, I show that Douglas and Devolder draw an incorrect conclusion when they apply their new account of genetic parenthood to answer the question of whether an egg donor is a genetic parent, in cases where the egg used in the reproductive procedure has been enucleated . Secondly, I demonstrate their account is vulnerable to counterexamples that exploit the absence of a condition specifying that genetic parents should cause the child’s coming into existence.In a recent publication Tom Douglas and Katrien Devolder have proposed a new account of genetic parenthood. Their account, which builds on the work of Heidi Mertes,The article proceeds as follows. In the second section I briefly present and explain why previous accounts of genetic parenthood are flawed. In the third section I present Douglas and Devolder’s new account of genetic parenthood and show that they draw the wrong conclusion when faced with cases where an egg has been enucleated for a reproductive purpose. In the fourth, and final, section I present a case that shows that their account of genetic parenthood is found wanting.28Ibid, p. 744.[A] child is my genetic child when it has 50% of my DNA or when it has 23 of my chromosomes. This 50% overlap of genetic material is, for example, what is looked into when performing a paternity or maternity test.In this section I review the accounts of genetic parenthood that Heidi Mertes investigated in her article ‘Gamete Derivation from Stem Cells: Revisiting the Concept of Genetic Parenthood’; and explain why they are found wanting. I begin with Mertes, as Douglas and Devolder do likewise. The first account that she presents can be named the informational account of genetic parenthood:There are several problems with this account, as it focuses on information overlap. Foremost, under it my siblings would be my genetic parents and vice versa. This would be the case as I share 50% of the information contained in my genetic nuclear material with my siblings. Furthermore, it can also be the case that I share 50% of my nuclear DNA, in the informational sense, with someone who is not a close relative of mine, and that would entail that she is my genetic child or parent.9Cambridge Quarterly of Healthcare Ethics, 12(4), 401–410.Kolers, A. (2003). Cloning and genetic parenthood.  can be named the Direct Derivation Account of genetic parenthood: ‘X is a genetic child of Y if X is directly derived from Y’s genes’.10Mertes, op. cit., note 7, p. 744.A more promising account, which Mertes discusses and which was first presented by Avery Kolers,causal relationship; the offspring is as it is because of its relationship to its parents, whereas the inverse is not true’.11Kolers, op. cit., note 9, p. 402. Mertes contends that the problem with this account is that it leads to counterintuitive conclusions when we examine two reproductive cloning cases.12In what follows I will bracket the question whether the egg donor, for the cloning procedure, is a genetic parent under the Direct Derivation Account. I do so as I will expand on this issue later on. Let us, following Douglas and Devolder, call the first case the Cloned Child:13Mertes, op. cit., note 7, p. 745.[A] couple (Mr and Mrs X) may become infertile after already having conceived one genetically related child (Y). As they long for a second child, they opt to clone their existing child Y, which results in the birth of Z.The direct derivation condition rules out the possibility of my siblings being my genetic parents, as I was not directly derived from them, and vice versa. As Kolers asserts: ‘[d]erivation is fundamentally a are not the genetic parents of Z. They are not so as Z was not directly derived from their genes. On the other hand, Y is the genetic parent of Z, as Z was directly derived from Y’s genes. Nevertheless, according to Mertes, in this scenario ‘it is most likely that Mr and Mrs X will “feel” like the genetic parents of Z, whereas Y is unlikely to think of herself as Z’s mother.’ Let us now consider the second case that Mertes presents, that I will call Cloned Parent, also following Douglas and Devolder: ‘Mr and Mrs X decide to clone Mr X instead of Y, resulting in child Q.’14Ibid.According to the Direct Derivation Account, Mr and Mrs X only genetic parent of Q. He is so as Q’s genes were directly derived only from Mr X. Now, Mertes notices that in this case the nuclear DNA provider and the clone15Ibid.do not share 50% of DNA, but 100%. The people who would pass [in Cloned Parent] a maternity/paternity test would be the genetic parents of Mr X. In this second scenario, both Mr X and his parents might consider themselves as Q’s genetic parents and both would have good arguments (either a contribution of 50% DNA or direct derivation) to support their claim.According to the Direct Derivation Account, Mr X is the contradictory intuitions on similar cloning scenarios. On the one hand, in Cloned Child we seem to support the idea that the progenitors of the nuclear DNA provider are the genetic parents of the clone. But on the other hand, in Cloned Parent we seem to support the idea that the nuclear DNA provider is the genetic parent of the clone. Of course, holding both statements as true at the same time is contradictory.The overall issue here, according to Mertes, is that we have 16Ibid. Let us now move to Douglas and Devolder’s account of genetic parenthood.After presenting these two cloning cases Mertes does not bite the bullet and accept that, in Cloned Child, Z’s genetic parent is Y. And she also does not try to revise the Direct Derivation Account in order to solve this purported contradiction in our intuitions. What she does is assert that these two cases show that ‘[t]here is no fixed, scientific, everlasting criterion of genetic parenthood that everyone can agree upon’ and that ‘the term genetic parenthood is not value‐free, but dependent on personal intuitions, intentions or judgements’.317Bioethics, 33(1), 54–59, p. 4.Douglas, T., & Devolder, K. (2018). A conception of genetic parenthood.  Rather than falling for this subjectivist account of genetic parenthood they propose a new account, one that can deal with the Cloned Child and the Cloned Parent cases. But importantly, their account is intended to be one ‘that captures the concept of genetic parenthood implicit in everyday usage’.18Ibid, p. 1. Before engaging with Douglas and Devolder’s account, it is important to notice that they do not start from Mertes’s presentation of the Direct Derivation Account, but rather from a revised version of it: ‘Direct Genetic Descent: P is C’s genetic parent if and only if (a) C’s genes derived from P’s genes, and (b) not through deriving from the genes of some third, intervening individual, M.’19Ibid, p. 3.Douglas and Devolder contend that Mertes’s conclusion about genetic parenthood is premature, in the sense that she has not shown that genetic parenthood is ‘a subjective concept that depends on the views of people about what sorts of genetic relation matter’.20Ibid.Suppose a sperm from P1 is used to fertilize an egg from P2. The resulting zygote then has its DNA removed and replaced by DNA from some other individual T. This zygote is then carried to term and eventually a child, C, is born. There is a sense in which C derives directly from P1 and P2’s genes; those genes governed the development of gametes, which created a zygote from which C developed. But C’s genes do not derive from P1 and P2’s genes, they derive instead from T’s genes, and this surely prevents P1 and P2 from qualifying as C’s genetic parents.They start from this revised version in order to avoid a possible counterexample:21Ibid, p. 4.Direct Gametic Genetic Descent: P is C’s genetic parent if and only if (a) C’s genes derived from P’s genes, (b) through a gamete produced by P, and (c) not through deriving from the genes of some third, intervening individual, M.Douglas and Devolder’s Direct Genetic Descent, which is a revised version of Mertes’s presentation of the Direct Derivation Account, runs into the same issues mentioned above when we consider the Cloned Parent and Cloned Child cases. Now, Douglas and Devolder offer a refined version of Direct Genetic Descent, which seems to answer the question of who are the clone’s genetic parents, while at the same time maintaining the concept of genetic parenthood implicit in everyday usage:is not a genetic parent of the clone. In such cases he or she is not a genetic parent as the clone was not derived from one of their gametes. In Cloned Child, Y, who is the nuclear DNA provider, is not the genetic parent of clone Z. And in Cloned Parent, Mr X, who is the nuclear DNA provider, is not the genetic parent of Q.Douglas and Devolder here introduce the condition that the genetic derivation must be via a gamete produced by the intending genetic parent. Thus it follows from this account that the nuclear DNA provider, in cloning cases where the enucleated egg does not come from said nuclear DNA provider, 22Ibid. Let us remember that, broadly speaking, mitochondrial replacement techniques are those where the nuclear DNA of the intending mother (or intending parents) is transferred from an egg (or zygote) with deleterious mitochondrial DNA mutations, to an enucleated egg (or zygote) that possesses healthy mitochondria.23Bioethics. 31(1), 27–36.Palacios‐González, C. (2017). Ethics of mitochondrial replacement techniques: A Habermasian perspective.  It is also relevant to bear in mind that mitochondrial DNA corresponds to, roughly, 0.1% of the whole DNA content of the human organism.Douglas and Devolder also conclude, following the Direct Gametic Genetic Descent account, that in cases where we employ a mitochondrial replacement technique the egg donor is not a genetic parent of the created child. Direct Gametic Genetic Descent ‘also allows us to evade the conclusion that P3  is the genetic parent of C4  in Mitochondrial Donation.’is a genetic parent. Why? Because the child’s mitochondrial genes were derived from the egg donor’s genes (Douglas and Devolder does not specify if there is a minimum of genes that must be transmitted for someone to classify as a genetic parent), from a gamete produced by the egg donor, and not by deriving such genes from the mitochondrial genes of some third, intervening individual, M. And the same rationale would apply to the egg donor in cases of reproductive cloning: she would be a genetic parent of the clone, regardless of the fact if she is also the nuclear DNA provider.Douglas and Devolder are mistaken in their application of Direct Gametic Genetic Descent to mitochondrial replacement techniques cases. In such an account the egg donor for a mitochondrial replacement technique 24Douglas & Devolder, op. cit., note 17, p. 5.Stricto sensu Douglas and Devolder are incorrect. The clones created in Cloned Child and Cloned Parent have at least one genetic parent: the egg donor.Now, Douglas and Devolder assert that from Direct Gametic Genetic Descent it follows that neither of the clones (i.e. Q and Z) has genetic parents: Direct Gametic Genetic Descent ‘implies that the clones created in Cloned Child and Cloned Parent lack any genetic parents, since their genomes were not inherited via gametes’.25Ibid. If this were ever to happen then, under direct gametic genetic descent, we would have to accept that any resulting child from this biotechnology, let us call it (following Douglas and Devolder) Two‐Donor Genome Transplantation, would not have genetic parents. Yet it seems that in this case A and B would be the genetic parents.Bracketing the previous issue regarding egg donors, Douglas and Devolder assert that Direct Gametic Genetic Descent is not only problematic because the clones would not have genetic parents, which they do. They contend that Direct Gametic Genetic Descent is flawed because there are other cases that are ‘closer to those of normal human reproduction’ that also create problems for such an account. As a point in case, imagine that the following is possible: we enucleate a zygote, and we replace its nuclear material with the genetic material obtained from two somatic cells taken from individuals A and B. In this case each individual contributes 50% of the nuclear DNA material.26Ibid.P is C’s genetic parent if and only if (a) some proportion X of C’s genes derived from P’s genes and (b) not through deriving from the genes of some third, intervening individual, M.In order to solve the problem posed by Two‐Donor Genome Transplantation, Douglas and Devolder propose to replace the condition of genetic inheritance via gametes with a condition of genetic inheritance of some determined proportion from parent to child. They call their new account Direct Proportionate Genetic Descent:nuclear DNA, then under this account the nuclear DNA provider is not the clone’s genetic parent. And if proportion X were to be > 0.1% of the whole DNA then the egg donor, in cases where we employ maternal spindle transfer, for example, would not be a genetic parent. Now, the upshot of the Direct Proportionate Genetic Descent account is that it does not entail the absurd conclusion that in Two‐Donor Genome Transplantation the resulting child has no genetic parents. According to this account A and B would be the child’s genetic parents. This would be the case if the proportion of genetic material established by this account (i.e. X) is set to include the proportion that obtains in cases of sexual reproduction.If proportion X, which they do not specify, were to be <100% of the 27Ibid.However, Direct Proportionate Genetic Descent remains too stringent in the cases of Cloned Child and Cloned Parent, for it continues to imply that the clones produced in these cases have no genetic parents – an implication that Mertes and Sparrow find implausible.Even though Direct Proportionate Genetic Descent can accommodate certain counterexamples, Douglas and Devolder maintain that according to it the clones created in Cloned Parent and Cloned Child still do not have genetic parents:does not necessarily follow from their account. It does not do so as proportion X could be a proportion of genetic material in the range between 50% and 100%. The fact that the nuclear DNA provider passes ‘too much’ of her genetic material does not rule her out from being a genetic parent in principle. Regardless of how we solve the previous point, under Direct Proportionate Genetic Descent the genetic parents of the nuclear DNA provider (i.e. the parents of Mr X and Y) cannot be regarded as the genetic parents of the clone (i.e. Q and Z); as in such cases they – the genetic parents of the nuclear DNA provider – are the ‘third intervening individual’.It is important to note that this conclusion do not have genetic parents. In the previous paragraph I have shown that this ‘softening’ is not necessary, but adopting such solution would entail abandoning the concept of human genetic parenthood implicit in everyday usage. The way in which Douglas and Devolder weaken Direct Proportionate Genetic Descent is by abandoning the idea that there cannot be a third intervening individual. Now they accept that in some instances there can be a third individual involved in the reproductive endeavour. But, interestingly, this third individual is not a genetic parent, but what can be described as a bridge between progenitors and descendants. For example, in Cloned Child case they ‘propose that the intervening individual (C1) does not break the genetic parenthood relation  in this case because she passes on too much of her genetic information to C2 [emphasis added]’.28Ibid. Douglas and Devolder formalize their revised account as follows:Modified Direct Proportionate Genetic Descent: P is C’s genetic parent if and only if (a) some proportion X of C’s genes derived from P’s genes and (b) not through deriving from the genes of some third, intervening individual M from whom C derived proportion Y of his genes.29Ibid.Douglas and Devolder contend that it is possible to revisit the conditions established in Direct Proportionate Genetic Descent and soften them, so we arrive at an account of genetic parenthood that does not conclude that in Cloned Parent and Cloned Child the clones proportion of genes’ will most probably not be a set figure but rather a range, and that this range could have fuzzy boundaries. Before I show why this account of genetic parenthood is found wanting, it is relevant to mention that according to it egg donors, both for cloning and mitochondrial replacement procedures, are not in principle ruled out as genetic parents. Why? Because, as stated above, the authors do not specify the proportion of genes that must be transmitted for someone to classify as a genetic parent. If the proportion were ≥ 0.1% of the whole DNA content of the human organism then the egg donor would be the genetic parent of the resulting child. This would be so as the mitochondrial genes of any resulting child would have been derived from the egg donor’s genes, and not at all through some third intervening individual M.30I thank an anonymous reviewer for bringing this point to my attention.Douglas and Devolder accept that ‘the 4causation condition built into their account. In order to appreciate this issue consider the following case, which I will call ‘Genome Editing ’. Alfred and Betty want to have a child. They have been unsuccessful in achieving their goal through sexual intercourse, as both of Betty’s fallopian tubes are completely blocked. Alfred and Betty decide to resort to Charles, a fertility expert. Charles prescribes Betty some fertility drugs and then proceeds to surgically retrieve her eggs. Once the eggs have been retrieved he uses Alfred’s sperm in order to carry out in vitro fertilization, and zygote E is produced. After the IVF procedure Charles does not transfer the zygote back to Betty, but rather he lets it grow in his lab for 3 days. On the fourth day Charles uses a Genome Editing technique in order to modify E’s cells. In this case he inserts 10% of his own nuclear genes into E’s cells. Finally, Charles transfers the genetically modified embryo to Betty, and after some months E is born.Even if Douglas and Devolder’s account avoids what they consider to be a counterintuitive conclusion , they run into a more severe problem for not having a is not his genetic parent, as he does not satisfy condition (a). But, Charles becomes E’s genetic parent per means of a Genome Editing technology when E is 4 days old. This is the case as 10% of E’s genes were derived from Charles’ genes, and not through deriving them from the genes of some third intervening individual.According to Modified Direct Proportionate Genetic Descent both Alfred and Betty are E’s genetic parents, if ‘proportion X’ is set to include a range between 5% and 50% of the total nuclear material. They are so in that 45% of E’s nuclear genes were derived from each one of them, and not through deriving from the genes of some third intervening individual. The question to answer now is whether Charle, the fertility doctor, is E’s genetic parent. When E is first created Charles becomes E’s genetic parent shows that there is something wrong with Modified Direct Proportionate Genetic Descent. The problem is that this account allows for an adult to become the genetic parent of an already existing individual; and this cuts against one of the necessary conditions of genetic parenthood: that one is one of the material causes of an individual coming into existence. Adopting a stance that maintains that such a causation condition is not necessary entails a radical revisionism of the concept of genetic parenthood, a revisionist position that needs to be defended.The fact that Charles 31Metaphilosophy, 38(2–3), 153–169.Devolder, K., & Harris, J. (2007). The ambiguity of the embryo: Ethical inconsistency in the human embryonic stem cell debate.  There are three ways in which I can address this objection. Firstly, I could show that early embryos are in fact individuals, but I do not have enough space to defend such a view (see Mathew Liao (2010) for a defence of such position).32Ratio, 23(1), 59–72.Liao, S. M. (2010). Twinning, inorganic replacement, and the organism view.  Secondly, my case could just be recast as referring to embryos that have passed the point where twining is possible. Third, Genome Editing works in non‐embryonic cases as well. Imagine that rather than being a 3‐day old embryo, E is a 1‐year old baby. If Charles were to edit his genome, at that point, so that now 10% of E’s genome derived from Charles then Charles, again, would become E’s genetic parent, but this is absurd.At this point someone could present two objections to my Genome Editing case. First, they could argue that given that early embryos can twin they are not individuals, in the sense of being unified biological organisms, and thus Genome Editing does not show that such an account is found wanting.becomes the genetic parent of an already existing individual, this is not so because replacing 10% of E’s genes would destroy E and create a new individual F.33I thank an anonymous reviewer for raising this objection. In other words, E’s numerical identity would not survive the extent of such procedure. If this were so then Charles would be the genetic parent of the recently created individual F, in as much as 10% of F’s genes derived from Charles’ genes and not through deriving them from some third intervening individual. According to this objection Genome Editing does not even get off the ground.The second objection holds that in Genome Editing it is not the case that Charles 34The Monist, 89(3), 334–350.Liao, S. M. (2006). The organism view defended. a) X begins to exist when the capacity to regulate and coordinate metabolic and other life processes is there; b) X persists as long as there is what may be called ‘organismic continuity,’ which is the continuing ability to regulate and coordinate metabolic and other life processes; and c) X ceases to exist when the capacity to regulate and coordinate metabolic and other life processes is permanently gone.In order to respond to this objection the first thing I need to do is provide an account of what an organism is. According to Liao, a being X is essentially an organism if35Genome Biology and Evolution, 9(7), 1880–1885.Graur, D. (2017). An upper limit on the functional fraction of the human genome.  This means that Charles could edit 10% of E’s non‐coding DNA, and this would not affect E’s capacity to regulate and coordinate metabolic and life processes thus, also, not affecting E’s numerical identity. Furthermore, my response to this second objection holds true even if it were to be the case that the findings of the Encyclopedia of DNA Elements project, which were able to assign biochemical functions to 80% of the genome, were true.36Nature, 489(7414), 57–74.The ENCODE Project Consortium. (2012). An integrated encyclopedia of DNA elements in the human genome.  Let me finish by saying that Genome Editing shows that Douglas and Devolder’s Modified Direct Proportionate Genetic Descent account of genetic parenthood is presently found wanting, and that they need to do more work in order for it to be a plausible account of genetic parenthood.Now, it could be the case that all our DNA is necessarily required for the capacity to regulate and coordinate metabolic and life processes to be there; and thus, if some of it were to be replaced by similar DNA, but from a different origin, then the original capacity to regulate and coordinate would be destroyed and a new capacity would be created. Even when it is intuitively appealing the former is incorrect. According to recent research 75% of our DNA is non‐coding DNA.