Metacarcinus edwardsii in a system in southern Chile with a biogeographic break at latitude 42°S. Specimens were collected at eight sites within its geographic distribution, with collection at four of these sites was performed twice. Using population genetic approaches, we found no evidence of geographic or temporal population differentiation. Similarly, we found no evidence of an effect on gene flow of the biogeographic break caused by the the West Wind Drift Current. Moreover, migration analyses supported gene flow among all sites but at different rates for different pairs of sites. Overall, our findings indicate that M. edwardsii comprises a single large population with high levels of gene flow among sites separated by over 1700 km and demonstrate temporal stability in its genetic structure.Elucidating the processes responsible for maintaining the population connectivity of marine benthic species mediated by larval dispersal remains a fundamental question in marine ecology and fishery management. Understanding these processes becomes particularly important in areas with a biogeographic break and unidirectional water movement along the sides of the break. Based on variability at 4209 single-nucleotide polymorphisms in 234 individuals, we determine the genetic structure, temporal genetic stability, and gene flow among populations of the commercially important mola rock crab  Although the larval period only represents approximately 1–5% of the total life cycle of these species, it is important for population connectivity2 because it is fundamental to maintaining the cohesiveness of benthic populations, enabling them to persist through ecological and evolutionary time3.Most adult benthic marine invertebrates have limited mobility or are sessile, as the larval stage is the period that enables dispersion5. Planktonic larval duration is positively correlated with dispersal distance6 and depends on the species, ranging from merely hours among corals7 to a year among lobsters8. In addition, larval behavior contributes to changes in magnitude and direction of larval movement, enabling offshore transport or residence near the coast9. One of the most important larval behaviors described in the water column is active vertical migration10. This behavior could regulate larval engagement with physical forcing and circulation, which would prevent them from straying from the coast11. Finally, all scales of oceanic water movement affect larval dispersal. Small-scale processes  combine with nearshore physical processes  to affect the degree of larval retention in each system12, while mesoscale behaviors  and global-scale physical processes  affect the degree of larval dispersal and population connectivity at a large scale13.Factors influencing marine population connectivity and larval dispersal include planktonic larval duration, larval behavior, and oceanographic currents14, Point Conception in North America15, and latitudes 30°S and 42°S in Chile16. The biogeographic break at 30°S is likely caused by differences in eddy kinetic energy (high south of and low north of 30°S) and equatorward wind (strong and variable south of and weak but persistent north of 30°S)17. The biogeographic break at 42°S is caused by the collision of the West Wind Drift Currents (Antarctic Circumpolar Current) with the Chilean coast, producing the northward Humboldt (Peru) Current and southward Cape Horn Current19. These biogeographic breaks act as barriers for species with low dispersal21 and promote non-random spatial movements of larvae in plankton, such as unidirectional movement22 or asymmetric dispersal among populations23. Overall, these factors can impact the survival of the planktonic larvae24, stochasticity in the recruitment of benthic species25, and the substantial changes in allelic frequencies observed when different cohorts are analyzed26.At large scales, the hydrographic regime and bottom topography affect biogeographic breaks. Examples include Cape Cod in the Atlantic Ocean16 for examples) is the mola rock crab Metacarcinus edwardsii, an important commercial fishery species that accounts for 75% of the Chilean artisanal cancrid fishery industry27. M. edwardsii typically inhabits sandy, muddy, and gravel substrates up to 70 m deep in intertidal and subtidal zones. Its distribution stretches from Guayaquil (Ecuador) to the Strait of Magellan (Chile)28, crossing the biogeographic breaks at 30° and 42°S.Among the species whose distribution spans the 42°S biogeographic break (see Lancellotti and Vásquez (2000)Metacarcinus edwardsii attains sexual maturity at a carapace width of 100 mm for both sexes29. Females mate with more than one male during the breeding season, but only one male becomes the genitor of the entire egg clutch31. Hundreds of full-sib zoea are released from each female32. Megalopae are abundant during October and December, coinciding with the advection of warm waters towards the coast33. Larvae recruit in association with the estuarine environment34. Laboratory experiments have demonstrated a planktonic larval duration of 60 days at 15 °C35, and a population genetic study based on eight microsatellites found high gene flow among populations over 700 km apart36. However, the possible effect of the Humboldt Current on gene flow, temporal genetic stability, and population differentiation of the species across the biogeographic break at 42°S remains unknown.M. edwardsii population using 4209 single nucleotide polymorphisms (SNPs). We explore the genetic differentiation, temporal stability, and gene flow patterns of M. edwardsii populations throughout their geographical distribution along the path of the Humboldt Current. Our study covers 1700 km of coastline, and we analyzed samples obtained in two different periods (2013–2014 and 2020–2021) on both sides of the biogeographic break at 42°S. Furthermore, we evaluate different migration models to infer the most probable gene flow patterns among M. edwardsii populations.In this study, we examine the spatial and temporal genetics of the From the 274 individuals collected, 20,230 raw SNPs were obtained. Following the removal of low-quality and outlier SNPs, 4209 SNPs and 234 individuals were retained for analysis. Many of the samples that failed genotyping were collected in 2013–2014, and this was likely due to poor DNA quality. The sample sizes before and after filtering are presented in Table FIS (inbreeding coefficient) were observed at sites with the smallest sample sizes (Table Allelic richness (AR) and expected heterozygosity (Hexp) were similar across sites and time periods. Observed heterozygosity (Hobs) varied between 0.084 in Ancúd 2013) and 0.132 in Dichato and Tumbes (2021). Higher values of 3 and 0.1ST values among sites were not statistically significant, except for comparisons between sites from the 2013–2014 period with small sample sizes and the other sites (Table P = 0.999). Barplots of higher values of K showed no evidence of differences among sites, even from different years. Therefore, K = 1 represented the biological model with the greatest support in our dataset  found individuals from all sites to overlap in the multivariate space, indicating no genetic differentiation among populations Fig. . PairwisP > 0.05). Overall, the proportion of migrants between pairs of sites appeared to vary based on the type of analysis performed, all three methods used  consistently indicated gene flow among all sites for both time periods.Among the models evaluated with MIGRATE software, the full model had the highest Bezier approximation scores for both the 2013–2014 and 2020–2021 datasets Fig. , bootstrM. edwardsii populations and temporal genetic stability across its geographical distribution. In addition, they indicate that the biogeographic break at 42°S and the Humboldt Current do not have a significant impact on gene flow among its populations. Compared to a previous study using eight microsatellites that sampled M. edwardsii from 700 km of the Chilean coastline, we found similar results in a broader geographical area.The results of this study show a clear pattern of high gene flow among M. edwardsii has a planktonic larval phase of 60 days35, the brown crab Cancer pagurus of three months41, the Norway lobster Nephrops norvergicus of four to eight weeks42 and the blue crab Callinectes sapidus of five to ten weeks43. For these species, population genetic analyses not showed statistical differences among populations of M. edwardsii separated by 1700 km (this study), populations of C. pagurus separated by 1300 km (from the Norwegian Sea to the Kattegat straits)44, populations of N. norvergicus separated by 500 km in southern Iceland42 and populations of C. sapidus separated by 740 km in the Brazilian coast45.Gene flow over large geographic areas has also been reported for other crustacean species with a similar duration of planktonic larval development (two to three months), for example, the Chilean mole crab 46, for different benthic invertebrates on the North and South islands of New Zealand47 and the Southeast Australian Biogeographic Barrier48, and for stomatopods located in Northern and Southern Indonesia49. However, the biogeographic discontinuities are not impermeable for all species. Previous studies have demonstrated that two-thirds of benthic species with pelagic development do not present a genetic discontinuity between Alaska and California21 and show that populations of echinoderms and some crustaceans do not show discontinuity either side of the 30°S biogeographic break in Chile20.Biogeographic breaks generally produce discontinuity between populations located on either side. Evidence for this phenomenon has been observed in different coastal areas. For example, genetic differences were observed for gobiid fishes located on opposite sides of the Mona Passage in the Caribbean SeaMacrocystis pyrifera, whose zoospores quickly settle a few meters from their parents50, and the mytilid Mytilus chilensis, whose planktonic larval phase lasts between 20 and 45 days52, show genetic differences between the two zones53. However, for the commercial gastropod Concholepas concholepas that have a planktonic larval duration of three months54, Cardenas et al.55 did not detect genetic differences in populations located at north and south of the 42°S biogeographic break. Therefore, as would be expected for a species with the longest period of planktonic larval development, this break was found not to affect gene flow among its populations. Overall, the analysis suggest that the duration of the planktonic larval stage is an important aspect in the gene flow of species inhabiting both sides of a biogeographic break.In the Chilean biogeographic break at 42°S, there is evidence of species with different propagule (zoospores or larvae) duration inhabiting both sides of the zone. The kelp species M. edwardsii is the temporal stability of the genetic variability across time periods (2013–2014 and 2020–2021). The analyses did not detect population differentiation, except for slight but significant differences in FST when pairs of sites with small sample sizes were compared. This temporal stability has been previously described for this species; Rojas-Hernández et al.36 did not detect differences in microsatellite variability in four cohorts of megalopas (over the period 2011 to 2014) collected at Los Molinos . To our knowledge, there is little evidence of the temporal genetic stability of populations of benthic marine organisms. For example, temporal genetic stability was described in the crab Carcinus maeneas in the Iberian Peninsula57 and in the crab Cancer pagurus in Sweden42. Temporal genetic similarity of different adult cohorts was also studied in the Pacific Geoduck Clam Panopea generous58 and the Arctic surf clam Mactromeris polynyma59. Until now, there have been limited studies on temporal genetic stability as compared to those describing changes in allele frequencies between generations in other species of benthic marine organisms61.An interesting issue observed in Nematocarcinus lanceopes62. In addition, the Benguela Current drives asymmetry in gene flow in the cosmopolitan bluefish Pomatomus saltatrix63, the Asia Northwestern Pacific Current in the brown seaweed Sargassum fusiforme64, and the North Pacific Current in the sea cucumber Parastichopus californicus65. Overall, our data suggest that the planktonic larval duration of M. edwardsii prevents the 42°S biogeographic break from negatively impacting in gene flow, consistent with the absence of spatial genetic differentiation in our results.It is important to note that we expected a northward asymmetric gene flow following the Humboldt Current. However, the migration analyses suggest that gene flow is not unidirectional in this area. The different models tested with the Migrate software showed gene flow among all sites but with different proportions between pairs of sites. This observation is supported by EEMS and divMigrate analyses, which also indicated a variable number of migrants between pairs of sites. In other studies, clear patterns of asymmetry produced by global circulation have previously been described for different species. In the Southern Ocean, the ocean currents produce asymmetry in population connectivity of the shrimp M. edwardsii since artisanal fishing is partly dependent on this species in the south-central zone of Chile.Finally, our results suggest that the duration of the planktonic larval stage is an important factor in determining the genetic structure of the species, allowing gene flow between distant populations despite the presence of a biogeographic break and currents that are primarily unidirectional. The findings of this study will be important for fishery management of M. edwardsii crabs were collected for this study. Nations (1975)28 described the geographical distribution of M. edwardsii from Guayaquil (Ecuador) to the Strait of Magellan (Chile). We searched for this species at different sites in its described geographic distribution in Chile however it was not found north of Valparaiso (32°S). Our sampling effort north of Valparaiso consisted of field work in Arica (18° 48′ S), Pisagua (19° 35′ S), Iquique (20° 12′ S), Antofagasta (23° 65′ S), Bahía Inglesa (27° 07′ S), and Coquimbo (29°59’S) in Chile. Our observations highlight the need for current, up-to-date biogeographical distribution for this and other crab species. We used two group of samples, first group collected in 2013–2014 and a second group collected in 2020–2021. The samples from 2013–2014 were reported by Rojas-Hernández et al.36 that performed a population genetic analysis using eight microsatellites and covering sites along 700 km of the Chilean coast. The samples used here and reported in Rojas-Hernández et al.36 were from Tomé (n = 23), Valdivia (n = 23), Ancud (n = 22), and Quellón (n = 22). The samples collected in 2020–2021 were collected in Valparaíso (n = 28), Dichato (n = 24), Tumbes (n = 10), Valdivia (n = 31), Ancud (n = 31), Quellón (n = 30), and Aysén (n = 30)  amplification. The PCR products were then standardized and sequenced using the Illumina HiSeq 2500 platform .For each crab, DNA was extracted from a small piece of muscle and subjected to massively parallel sequencing at Dart Diversity Arrays Technology Pty Ltd. . Following the methods of Kilian et al.69 in the R statistical software68, retaining: (a) only one SNP in reads containing two or more SNPs, (b) SNPs with a read depth > 5 or < 100, and (c) SNPs with a > 95% reproducibility score, an index provided by DArT PL that indicates the proportion of replicate technical samples with a consistent marker score (reproducible result). SNPs that were monomorphic, had > 15% missing data, or a minimum allele frequency (MAF) < 1% were removed, as were samples with > 15% missing data. Based upon a relatedness value r > 0.4, we detected a pair of related individuals collected in Concepción in 2014. One individual was removed to avoid potential bias in the population genetic estimation.Sequences generated from each lane were processed using proprietary DArT PL analytical pipelines. Barcode region and complete reads were filtered by quality parameters . Using DArT PL proprietary algorithm, identical sequences were collapsed into “fastcoll files” and low-quality bases from singleton tags were corrected into correct bases using collapsed tags with multiple members as a template. The proprietary DArT PL algorithm (named DArTsoft14) was used to call the SNPs. For this study, call quality was assured by a high average read depth per locus  and a sequencing volume per sample of 1.64 million reads. A total of 83 technical replicates of the 275 unique samples were run to estimate the reproducibility of the reported markers (> 99%). All this information was provided by DArT PL. The resulting SNP data was filtered using the dartR libraryoutflank function of the dartR library in R, (b) the Bayesian method implemented in the BayeScan software70, and (c) the relationship between FST and heterozygosity implemented in the Fsthet library71 in R software. We removed all SNPs that showed evidence of selection in any of these three approaches. Finally, SNPs with significant departures from Hardy–Weinberg equilibrium for one or more sites were removed using the dartR library in R, and SNPs with linkage disequilibrium > 0.2 in all sampling sites were removed using the PLINK 2.0 software40.All SNPs showing signs of selection were removed to avoid potential bias in estimating the differences among sampling sites. Three different approaches were used here: (a) the likelihood-based method implemented by the IS) estimated using the GENETIX v 4.05 software72. Allelic richness (AR) was estimated using the divBasic function of the diveRsity library in R72.Genetic diversity at each sampling site was described with expected heterozygosity (Hexp), expected heterozygosity corrected for sampling bias (Hn.b), observed heterozygosity (Hobs), and the inbreeding coefficient  estimation of the most probable number of genetic clusters (K) using the Bayesian approach implemented in the STRUCTURE software74. The admixture model and correlation of the allele frequencies were used as input. The procedure was performed three times for each K between 1 and 6 with a burn-in of 100,000 iterations and an after-burn-in of 200,000 iterations. The probability of each value of K was estimated as described in the STRUCTURE manual75.Population genetic structure was estimated using the SNP database after removing all SNPs with signals of selection. Three population genetic methods were used with all data obtained in 2013–2014 and 2020–2021: (a) PCoA to describe the distribution of individuals in multivariate space, using the dartR library in R, (b) pairwise Separately analyzing samples from periods 2013–2014 and 2020–2021, we estimated the direction and magnitude of the gene flow among sampling sites using three methods.76 and two random subsets of 1000 SNPs per period. This approach employs a coalescent method to estimate mutation-scaled migration rates (M) for each group over the last 4NE generations. The Bayesian inference of the Migrate software was used with the default settings except for the following run options: (a) one single long run utilizing heating with temperatures of 1.0, 1.5, 3.0, and 1,000,000; (b) 1,000,000 genealogies were run with a sample increment of 10; and (c) the first 100,000 genealogies. The uniform prior distribution was used for Θ (from 0 to 0.1) and M . We tested four models that represent the probable gene flow in the studied area: (a) panmixia model, (b) full migration, (c) directional migration towards the north (considering northern variation in ocean circulation37), and (d) northbound migration at sites north of the biogeographic break and southbound at sites south of the biogeographic break. To identify the best model, each analysis was performed twice for two independent subsets , and we used the bf.py Python script provided by Beerli et al.38 that compares the Bezier log marginal likelihood values obtained in each model. MIGRATE was run at the Cyber Infrastructure for Phylogenetic Research .First, the historical migration rates was assessed using the Migrate software77. To capture the continuous population structure, EEMS covers the habitat with a dense regular grid, in which each deme exchanges migrants with its neighbors. If habitable regions are unsampled, estimates are based on the prior, which assumes no heterogeneity in migration rates77. EEMS was run with the full set of 4209 SNPs using 500 demes and three independent chains of 5,000,000 MCMC iterations with a burn-in of 1,000,000 and sampling performed every 9999 iterations. The proposed variances were adjusted considering an acceptance rate ranging from 10 to 40%. Results were plotted using the rEEMSplots package77 in R. Note that the results for effective migration rates are on a log10 scale (denoted as log(m) in the plot) relative to the overall migration rate in the habitat. Thus, a log(m) = 1 represents an effective migration ten times greater than the average, and a log(m) = -1 corresponds to an effective migration ten times less than the average.Second, the Estimating Effective Migration Surfaces (EEMS) software was used to visualize the gene flow patterns among sampling sites. EEMS estimates migration rates so that the genetic differences observed in the data match the genetic differences expected under an idealized stepping-stone model. These estimates are then interpolated across sampling sites to produce an “estimated effective migration surface”—a visual representation of genetic variation—that highlights regions with higher-than-average and lower-than-average historical gene flowM. edwardsii were estimated using the divMigrate function of the diveRsity library72 in R. The Alcala’s statistic  was used as a distance measurement, which incorporates information from both Gst and D and maybe generally better suited to different demographic scenarios72. Furthermore, the asymmetry of gene flow between pairs of sites was tested with the full set of 4209 SNPs using a bootstrap of 1000 iterations with NmAlcala used as a distance measure.Finally, the direction and magnitude of the gene flow between pairs of sampling sites of


This review aims to summarize and synthesize thefragmented information available on the genetic improvement of local goats on the American and other continents, wherepopulations with these goats have an important role in food security and theeconomy of rural communities, as well as in conservation of biodiversity andproductivity improvement. Topics such as the current state of goatproduction globally, conservation programs, resistance to parasites anddiseases, use of phenotypical characteristics and genomic information, andmolecular markers for genetic improvement are addressed. The mainchallenges, opportunities, and limitations described in recent literatureconcerning local goats in the immediate future are discussed. Worldwide, there arearound 1094 million goats; most of them (94 %) are in countries of Asiaand Africa, followed by the Americas (3.4 %) and Europe (1.4 %). In China, there are around 58 domestic local breeds,distributed in different environments . India has 23well-recognized goat breeds . In Africa, most of the goats(63 % of the population) are non-improved native breeds, and in the Americas, there are around28 recognized local breeds . In addition, themajority of these populations are utilized for self-consumption of productssuch as milk, meat, and skin or fibers, and they are found in herds thatbelong to low-income producers .On the other hand, the available information about genetic improvement (GI)of local goats , also known as criollo, indigenous, ornative, in the Americas and other regions of the world is limited; however,the available results indicate that local breeds have a high potential forimprovement . In addition, the variation betweenand within these breeds is highly valuable, since great geneticvariability is required for the populations to adapt and face theenvironmental changes that they are subjected to . Intime, GI has been limited to the “commercial” breeds, although their lowparticipation in the animal registry and improvement plans has resulted inslow progress and an accelerated loss of genetic variability .In this sense, the incipient generation of information about populations oflocal goats is due, in principle, to the fact that there is the notion thatthey have a lower productive and economic performance, which decreasesinterest among producers and places a specific breed or genotype at risk ofextinction . Therefore, the greatest challenge of GIin local breeds is the adaptation of selection schemes and classicimprovement in small populations and production systems characterized bypoor organization from producers . In addition, it isnecessary to include the ideology of small-scale producers in the objectivesand selection criteria. For example, Gunia et al. (2010) mention that theconformation and growth of males are among of the most desirable traits forproducers in the Caribbean (77 % of the interview respondents), followedby maternal behavior, reproduction, and milk production. They conclude thatGI programs must consider the use of local populations as maternallines.1.1In countries like Iraq, Syria, Morocco, and Tunisia, efforts have beendirected to design GI programs, which have consisted of the distribution ofpure breed bucks . So, this has nothad the foreseen success due to the low adaptation of bucks to theenvironment. In addition, there is limited participation of producers in thedesign of GI plans . Consequently, farmersare not motivated to invest in these programs, resulting in intermittentimplementation and low success . This situation issimilar in Latin American countries such as Mexico , Ecuador , Peru, and Bolivia .The goats that migrated to the “new world” (the West) have European,African, and Central Asian origins, from which the local goats found in theAmericas are derived and represent a reservoir of genetic diversity to be usedin breeding programs, selection, and conservation .Genetic improvement has been done in Brazil by introducing goat populationsfrom Portugal and Spain and more recently from Asia, Africa, and Europe. This caused these goats to go through intenseadaptation processes to overcome severe climate conditions in this country,particularly in the northeast of Brazil, thus originating a particular goattype that is clearly separate from the other local breeds of the rest of theAmerican continent, with a marked influence from Cape Verde goats .Deza (2007) proposed a genetic improvement plan in Argentina for localgoats in “agroecologically restrictive” environments, stemming from thecharacteristics attributed to the local goat. Among these characteristics,the following stand out: animals that are polymorphic, polychromic, rustic,and adapted to extreme environments, which have not been sufficientlydescribed and therefore have still-unknown productive potential, with highproductive variability between and within the herds. For this reason, mostof the efforts to conduct GI in these populations continue to be donetraditionally .1.2In countries such as Bangladesh, community-based breeding programs (CBBPs)have been established, whereby, contrary to what was mentioned before,producers participate with the common interest of conserving and improvingtheir genetic resources in low-income production systems . Liberia also incorporated a pilot CBBP in three countries with theparticipation of goat farmers . In Ethiopia, theimplementation of this GI plan increased producers' income by 20 % byimproving the size of the litter. In addition, meat consumption at the farmlevel increased, so a CBBP is considered a feasible plan with measurablegenetic gains in performance characteristics and the impact on the standardof living of producers .In Turkey, positive effects were observed beyond improving the animals,since the living standard of producers and some market situations improved;however, a critical success factor for these programs is the monitoring andcontinuous training of the producer . Likewise, Mueller (2017) evaluates the characteristics of some CBBP cases for the productionof dairy goats in Mexico, Cashmere goats in Iran, Mohair goats in Argentina,and dairy goats in Kenya. The study concludes that planning andparticipation by local institutions are of utmost importance for support inthe organization, financing, and technical support of the participatingproducers. Since one of the main problems faced by this strategy issustainability in time, GI efforts for local goats must be conducted froman integral perspective .For example, in Malawi and Uganda, the use of CBBPs increased growthperformance and survival of offspring; however, to achieve adoption of thismodel, it is recommended to establish producer cooperatives and reformregional and supportive policies . Also, it mustinevitably correlate the existing genotypes with the environment withoutunderestimating its potential for improvement and emphasizing the need tomake more significant conservation efforts, such as what has been proposedin Kenya . Given the variability of CBBP success inEthiopia, valuable recommendations have been generated that could improvethe impact of these programs. The actions to be implemented are reproductiveimprovements such as artificial insemination and synchronization of oestrus,which will allow knowing the pedigree of the animals, removal of the effect ofthe birth season, and acceleration of the breeding process with thebest identified individuals .1.3Knowledge of the genetic structure of organisms, genetic populations, andphylogenetic studies is essential to provide opinions about effectiveconservation and reintroduction plans, mainly when the target population isat risk of extinction . For the specific case oflocal goats, these have high significance due to their unique adaptationcharacteristics, with a particular relevance because of their lowmaintenance, which makes them a vital ally to face and combat the effects ofclimate change . In this sense, some characterizationefforts in Sri Lanka, Slovenia, and Greece have found that local goatpopulations have a distinct genetic identity and are heterogeneous. Thecontemporary structure of the population is highly influenced byanthropogenic actions, making it necessary to establish immediate activitiesfor their conservation . However, the lack of emphasis on production based ontechnology and appropriate characterization of breeds remains a limitingfactor for the sustainable use of these goats .Liu et al. (2019) conducted a study to define conservation priorities of 26local breeds in China to establish protection programs according to theimportance within and between breeds given by genetic diversity, and theyfound that the Inner Mongolia Cashmere, Jining Gray, and Liaoning Cashmeregoats were the ones that contributed most to heterozygosity and totaldiversity. However, for the case of Daiyun and Shannan Blanca goats, theirconservation should be prioritized based on the population'seffective size.Due to the low productive indices of local goats in Brazil, “exotic”breeds were introduced, which, even though they are more productive, do not haveadaptation characteristics (resistance to diseases and parasites) thatlocal goats have. Despite this fact, exotic breeds have substitutedlocal breed , placingthe latter in danger of extinction. To avoid the loss of this geneticresource, the Program for Conservation of Animal Genetic Resources wascreated through “conservation nuclei” in habitats where the goats aresubject to natural selection (in situ) and also from storage of semen andembryos (ex situ) .In Cuba, an exploration of 48 herds that were thought to be “local” wasperformed, finding that only one of them was indeed local. Therefore, aresearch–action process was implemented for the conservation of thiszoogenetic resource, with the active participation of farmers facing anadverse environment with social complexities . Similarly, this effort has been carried out in countries like Mexico, where the conservation processresulted in a fundamental scenario for the development of several studies,which have contributed valuable information related to geneticcharacteristics. With this learning, peasant systems acquired newdevelopment opportunities, but they conserved the socioeconomicrationalities for breeding, whose capacity to “change and conserve at thesame time” was called “socioecological resilience” . Within this context of innovation for conservation, therewere community livestock fairs held as a tool to revitalize theparticipative management of zoogenetic resources. This strategy eases theflow of specimens through purchase–sale practices or solidary practices ofexchange and loan.Another conservation program for local goats that has entailed goodplanning, organization, and monitoring has taken place in the FrenchAntilles  and to a lesser degree in Ecuador. In Mexico, without official programs, theconservation of local goats in some regions has been found to be a necessityby the producers themselves, who have confirmed the advantages of localgenotypes compared to the improved breeds that have been introduced. Someexamples are the Tarahumara goat in Sierra de Chihuahua , the White Celtiberian goat in Zacatecas , the local goats inComarca Lagunera , the Black goats in Querétaro, and the Pastoreña goat from the Mixtecaregions in Puebla and Oaxaca .Likewise, in France, the interest in the conservation of biodiversity ofdomestic animals, including goats, has been “rekindled”, since a fastdecrease or even disappearance of certain breeds has been observed.Therefore, the choice of “returning” to grazing as an option to conservethese local zoogenetic resources is being studied, since historicallyextensive livestock production has been linked to local aspects,traditional breeds, and therefore direct conservation .22.1The most significant efforts for research on this topic have been made with local goats from the French Antilles . However, Brazil maintains animprovement program between breeds that also includes resistance tonematodes .Infections due to gastrointestinal nematodes (GINs) in small ruminantsrepresent the main limitation of production in grazing systems in thetropics because they cause economic losses when decreasing the production. In that regard,anthelmintic products to control GINs had success for many years; however,resistance to these products has spread throughout the world.Haemonchus contortus. The resultsindicated a negative correlation between egg counts and blood values andsuggest differences between breeds in PCV and HB; this, in turn, is relatedto resistance to infection by H. contortus or the effects.Concerning this, Costa et al. (2000) studied the variability between andwithin goat breeds by measuring the number of eggs per gram of feces (EPG),packed cell volume (PCV), and hemoglobin (HB) in local kids of the breedsCanindé and Bhuj, as well as in Nubia, all exposed to Another alternative to counteract the problem of parasitosis fromgastrointestinal nematodes is dietary supplementation. In this regard,Torres-Acosta et al. (2006) studied the effect of dietary supplementation inlocal kids that graze on native vegetation during the humid season inYucatán, Mexico, on resilience to infections by GINs. The resultsshowed that dietary supplementation improved the kids' resilience to GINinfections, which, in addition, is an economically viable technology.Haemonchus contortus and Trichostrongylus colubriformis, showing that the GI for resistance to GINs is viable.Creole goats from the Guadeloupe islands in the Caribbean are one of the moststudied breeds regarding resistance to infections by GINs. This geneticresistance has been studied since 1995 because they are very susceptible tothese infections. In this regard, Mandonnet et al. (2001) studied thegenetic variation for resistance to infection from nematodes to introducethis variable into genetic improvement plans. The researchers found aheritability value  addressed the appropriateness andviability of performing the selection of local goats based on theirresistance to GINs and developed three strategies to face this problem: (a) reducing the host's contact with the infectious larvae through a reducedload in grazing, (b) extending the efficiency of molecules from syntheticanthelmintic molecules by implementing directed selectivetreatments or the use of phytotherapeutic drugs, and (c) increasing theability of the host to tolerate the negative effects of the worms(resilience) and eventually responding to the parasites (resistance) fromgenetic selection.The problem of infections from GINs has been studied at the moleculargenetic level. In this regard, a large number of loci for quantitativecharacteristics have been detected (QTLs) associated with resistance to GINsin small ruminants in more than 20 chromosomal regions . The first scan of the genome for resistance to GINs ingoats was carried out in local goats from Guadeloupe  and identified 13 QTLs for resistance, resilience, and immunitycriteria. Later, after performing a quality control analysis of SNPs (single-nucleotide polymorphisms), they identified 46 643 markers for studies byGWASs (genome-wide association studies) .Likewise, Aguilar-Caballero et al. (2008), in their review, highlighted theexistence of resilience and resistance as natural defense mechanisms oflocal goats against GINs. In addition, they discussed the situation ofgastrointestinal parasitosis in goats, the control measures applied, theircurrent situation, and the alternative methods for GINs control-tested ingoats that can be transferred to the field .2.2Disease resistance is a topic in which the component of genetic resistancehas been studied as part of control mechanisms, not only because of itsimpact on productivity but also because of the zoonotic and economicimplications that it represents . In this sense, this genetic resistanceis considered an alternative for the control of diseases and the use ofantimicrobials; it includes both immune and non-immune mechanisms and isdefined as the inherent capacity of an animal not previously exposed topathogens. It has been found that natural resistance is inherited andpassed from parents to offspring . This paperwill consider some studies that have evaluated the genetic resistance oflocal goats to various diseases.Brucella melitensis. Regardingthis disease, transmission patterns and dynamics have been studied, as have some induced and natural resistance mechanisms. To date, it has beenfound that genetic resistance to intracellular pathogens is linked to agenomic region of the SLC11A1 gene, which is considered a candidate forresistance to this disease .Brucellosis is a zoonotic disease of public importance in countries such asMexico, Nigeria, and Algeria, which is caused by the bacterium Ehrlichia ruminantium, and transmitted byAmblyomma ticks. So, it occurs in nearly all the countries of Africaand nearby islands, as well as the Caribbean. The disease can cause high mortalityin susceptible domestic ruminants (up to 90 %); goats and sheep are morevulnerable than cattle and European breeds more than African ones . In this regard, Bensaid et al. (1993)suspected resistance to this disease in Creole goats from Guadeloupe, andtherefore Bambou et al. (2010) performed a study to confirm thisresistance and susceptibility in local goats to a standardized sub-lethalinfection of E. ruminantum, inducing 70 % mortality. They measured the intensity ofthe disease using clinical reaction indices , and differences were found between themortality rate after infection. This was the first study wherein geneticvariability of this disease was found, and there is an attempt to link thisvariability physically with areas of the genome. Likewise, Matheron et al. (1987) concluded that resistance seems to be under genetic control since aherd studied for 10 years and exposed to the disease reached a resistancerate of 78 %.On the other hand, hydrocarditis or aqueous heart (“cowdriosis” or“heartwater”) is an acute infectious disease that is non-contagious andfatal. It is produced by rickettsiae in ruminants, caused by Even more, the goat arthritis encephalitis (GAE) is a chronicdisease eased by a retrovirus of the Lentivirus genus. There are no vaccinesor effective treatments. Therefore, the hypothesis has been suggested thatthrough genetic selection, there could be a feasible alternative for thecontrol of this disease, as reported by Schultz et al. (2020), who estimatedheritability values of 0.077 (with ranges of 0.026 to 0.128) for resistanceto GAE in Alpine and Saanen goats.Kim et al. (2019) found candidate genes for resistance to Salmonella (LBPand BPI) and heart disease (TTN and ITGB6) in Korean, Iranian, and Moroccangoats, which is of maximum importance to direct future efforts to conservespecies biodiversity and contribute to genomic improvementprograms. For their part, Meydan et al. (2017), identified resistantgenotypes in variants of the gene that encodes the prion protein. Most of the variations observed in phenotypicalcharacterization studies are due to environmental factors, topography, andvegetation, which give rise to different ecotypes . Inaddition, it fosters differences between and within breeds (Table 2). Forexample, the withers height of Bolivian local goats (51–58 cm) is lower whencompared to that of Sabanero local goats from Colombia (75–80 cm). Thegreat difference in body length between local goats from Arque, Bolivia (47 cm), and Amatepec, Mexico (104 cm), is also worth noting, representing adifference higher than 100 %. Even among the same local goats, there aredifferences for these same characteristics .In this sense, the external characteristics of local goats are an essentialselection criterion that must be considered, since they are the firstimpression of the animal. It is a critical point to ensure thedissemination of the genetic material of those valuable animals and toguarantee appropriate genetic progress . In this regard,producers from Patagonia, Argentina, and Oromia (Ethiopia) use severalmorphometric and phaneroptic criteria to select their replacements,highlighting the size, animal conformation, type of hair, and coat color.Valencia-Posadas et al. (2017) evaluated the phenotypical relations betweenconformation and milk production traits and reported that goats with betterbody conformation were not the best to produce milk, which can be directlyrelated to the productive aptitude of the genotype in question andshould therefore be considered at the time of implementing GI schemes.Because of this, a new methodology has been developed that combines the useof phenotypical distribution models to predict the behavior of thelivestock, and it has been concluded that it might be a highly valuable toolto evaluate and conserve the breeds that adjust better to specificenvironments .Undoubtedly, data collection in productive phenotypical characteristics fromproducers, particularly under field conditions, represents devoting time,effort, and concentration, which in many cases is not enough to have areliable database for their later use in GI programs. In this sense,phenomics, understood as the application of technologies that allow thecollection of phenotypes easily, economically, and in large volumes,represents a great opportunity to achieve considerable improvements , since, with the widespread growth of communication technologies,GI programs for local populations could be revolutionized in developingcountries. Some examples include the use of sensors in females to detectpatterns of reproductive behavior, the prediction of body weight in animalsfor meat production using a measuring tape and measurements of the thoracicperimeter, and the use of mobile devices that help to evaluate milkproduction and weight gain, among others .4High-density genomic tools have been used in the last decade to study andcharacterize livestock's genetic diversity and populationstructure. However, many individual phenotypes and genotypes are required toobtain accurate genetic values, which in the case of local populations withlow numbers of individuals can only expect low genetic gains .A large variety of techniques has been developed to help solve this problemin order to evaluate variability and diversity at the DNA level (Table 3). Nowadays, techniques are available, such as random amplifiedpolymorphism DNA (RAPD), amplified fragment length polymorphism (AFLP),restriction fragment length polymorphism (RFLP), simple sequence repeat(SSR), and short tandem repeats (STRs), among others. According to theliterature consulted, the most frequently used techniques to estimate thegenetic diversity between populations of sheep, goats, bovines, buffaloes,camels, and horses are RAPD  andmicrosatellite markers or STRs .On the other hand, genome-wide association studies (GWASs) help to explore therelationship between genetic and phenotypic variation in terms ofgenomic markers, identifying variants that can be part, or not, of knowngenes. Stemming from this, molecular research has opened new possibilitiesfor the genetic characterization, conservation, and utilization of the onlygenetic resource that local goats have . However, the use of these tools has not beenimplemented for goats on a broad scale. In that regard, in Greece, studies ofthis type in native goats are limited. Only microsatellite markers or SNPshave been used to characterize genetic distances between breeds based onpolymorphisms of blood proteins, finding significant genetic variabilityand potential for improvement in productive and aptitude traits . In Italy, studies with SNPs have been carried out to characterize thegenetic diversity of native dairy goats such as Argentata dell'Etna,Derivata di Siria, Girgentana, and Messinese goats .Likewise, Ceccobelly et al. (2020) mention that molecular tools are of great helpto discriminate breeds adequately at a low cost. In addition, they must beconsidered to trace goat products and distinguish their origin.In India, Jayashree et al. (2019) conducted a study to identify the diversity ofKarnakata goats through 23 microsatellite markers and found a heterogeneouslocal population, which is highly valuable because of its adaptationcharacteristics. Likewise, in Sri Lanka, many localized native goats covermost of the country's goat population and are at high risk ofextinction from intensive crossing with exotic breeds. This situationpositions them as an invaluable genetic resource from their highenvironmental adaptation and resistance to diseases. Therefore, SNPs havebeen used to identify regions of the genome that are correlated with theproductivity, resistance, and fertility of goats .Based on the preliminary information, the use of these genomic and moleculartools has become of utmost importance for the improvement andconservation of native breeds in general, since they allow combiningpedigree, phenotypes, and genotypes in a simple evaluation without the needfor post-analysis processes .In their review, Mrode et al. (2018) indicated that CBGI is a reasonable frame ofreference; innovative genomic selection will be required in fragilegrowth systems wherein adaptation is an important characteristic, and it willbe essential to identify regions of the genome related to aspects ofadaptability with the aim of maximizing the diversity of animals. Inaddition, the same authors  point out that an adequatecost–benefit analysis ought to be part of any strategy to implement genomicselection in these production systems.An example of the use of these techniques is reported by Sevane et al. (2018), since they generated a perspective of the diversity of goats in theAmericas using genomic tools, by using information from Iberian, African, andlocal breeds. For this case, they obtained important signatures of Iberianbreeds, particularly Cuban Criollo, but with a significant contributionfrom African breeds that have given rise to many local breeds. With thisinformation, there are advances in revealing the evolutionary history oflocal goats and defining conservation priorities to maintain the diversitythat they have inherited.55.1During the last century, erosion of goat genetic resources has been observedas a result of a massive replacement of “low-productivity” local breedsby other “highly productive” specialized breeds .However, the statement that specialized breeds are more productive is notentirely correct, since there is evidence suggesting that crossbreeding withpure breeds does not necessarily improve the productive aptitude of localgenotypes under the management conditions in which these genotypes aretraditionally developed. This way, the overall result is lower productionthan expected from the interaction of an unfavorable genotype with theenvironment . Evidence of this fact was given byGaddour et al. (2010), who found that crosses of Damasco with Alpine andMurciano–Granadina goats improved milk production and kid growth, butnegative effects in reproductive traits were also detected.Due to the above, producers of local goats face the challenge ofmaintaining or increasing the size of their populations and thus avoidingextinction. Therefore, strategies should be sought that help apply allavailable tools to improve the productivity and profitability of thesefarms, including a wide range of GI technologies like genomic profiles,targeted genetic improvement schemes, and different reproductive, marketing,and traceability tools that could help small-scale producers to survive. On the other hand, acritical challenge faced by producers is the availability of technical andscientific information, since, in general, information on new technologicaladvances is available mostly among the scientific community; forproducers, this information is massively disseminated because in some partsof the world, access to this type of information is highly restricted or the cost to access it is extremely high, whichseriously affects decision-making in public policies and at the farmlevel. The abovementioned issue is not exclusive to rural areas, but this lack ofinformation is also present in urban and metropolitan areas; therefore, thechallenge is to generate strategies whereby new information ontechnologies and/or findings in any aspect of the production chain reachesproducers and decision makers so that they can be applied. In addition,another of the great challenges observed is to seek strategies that helpsustainability and mitigate the effects of climate change to guarantee thesupply of food of animal origin to a growing population .5.2A severe limitation in GI programs for these populations is the lack ofcontinuity between research and practical implementation, which isaggravated by the deficiency of resources to monitor these programs due inprinciple to the fact that government research and development programs haveonly considered productivity, without considering aspects of populationadaptation. In this sense, some research objectives are altered based onscientific trends, resulting in intermittent studies without futureefforts . In that regard, Djemali (2000) points out thatin countries such as Tunisia, those who have invested for decades in GIprograms for local goats to be successful have found that governments hardlysupport animal registry and selection costs for prolonged periods. Inaddition, there is a scant connection between state entities that implementGI programs and researchers who are the ones with the “know-how” aboutwhat should be used. Furthermore, involvement from producers is notobserved, leading to constant changes in the objective's selection, thuslimiting the genetic progress. An example of the failure of these GIprojects, wherein the producer is not considered, happened with goat producersin Morocco and Senegal . In other words, there is a will toimprove the production schemes but a lack of real organization of all theactors involved. Concerning this, Giovannini (2011) suggested that thegreatest limitations for the transference of GI plans are inadequatepolicies, precarious economic development, problems inherent to productionsystems, precarious institutional development, and precarious andunsustainable financing.5.3One of the great opportunities presented by local goats is exceptionalgenetic diversity and variability, which is essential to adapt productionsystems to future challenges and represents a critical point to face climatechange and its effects .Advances have been found for reproductive traits. Since the estimators ofheritability for these traits are low, huge amounts of data are required forthe GI process to be effective, which is complicated in local populations. However, researchers can develop strategies to improvereproduction in local goat genotypes, given the advancement in genomic andmolecular tools . This could allow identifyinggenomic–genetic variants with relative ease, which would make it possible toapply scanning techniques of the genome, association studies in the genome,and genomic selection to increase prolificacy . Inaddition, high genetic variability and a low level of inbreeding in nativebreeds have been found, indicating that there are no negative signs for thesustainable use of goats in the future .A wide range of possibilities has been explored for GI in populations oflocal goats. In that regard, Atoui et al. (2020) pointed out that some managementpractices seem to have an impact on estimating genetic components for growthin local kids; that is, the selection at critical ages that defines changesin the growth components seems to be more important when using frequentweighing. As pointed out by Torres-Hernández et al. (2020), this should beconsidered within GI programs for an accurate estimation of milk productionthrough lactation. Although all the strategies contribute to knowledge, themain limitations for improving local goats in many parts of the world arefundamental issues such as diseases and parasites, poor nutrition , genetic potential without quantifying, inadequateinfrastructure and access to markets, minimal institutional and servicessupport, and poor access and underutilization of knowledge,information, and technologies .Finally, countries such as Sudan and Italy have clearly defined theproduction objectives for their native genotypes and believe that the useof genomic–genetic technologies should be made widespread for thecharacterization of genotypes or breeds. It is thought that these would saveconsiderable time and resources  although emphasizing thatspecial attention must be paid during the selection process to not alteringthe adaptation of goats to local conditions, specifically thosecharacteristics that are of interest for conservation .Therefore, an urgent need has been generated to consider different measuresto address the limitations identified so far in terms of the GI of localgoats to exploit the potential genetic diversity and benefit of theseanimals .6Significant advances have been observed in recent years in the conservationand genetic improvement of local goats globally, primarily due to thelast-generation molecular tools. However, it is still perceived that effortsare isolated and intermittent. They are still not enough to conserve andrecover these populations, despite them being an invaluable reservoir ofgenetic material resistant to diseases and parasites that is adapted to produceand reproduce under extreme environmental conditions.These characteristics make local goats one of the few viable and sustainableoptions of low economic, nutritional, and environmental requirements. Theycan help to recover both food self-sufficiency, with products of highbiological value, and income in developing countries with extreme povertyfacing the adverse effects of climate change.Some other genetic improvement and conservation strategies for thesepopulations should focus on the characterization of the productive system inan integral manner and where phenotypic and genotypic characterizationshould be considered part of the evaluation of the various mechanisms ofadaptation to the environment that these goats have developed since thisinformation can contribute to the development of programs for bettercomprehensive genetic improvement schemes.Because of this, it is urgent to redouble efforts in research, support, andaccompaniment in all the links of the productive chain that seek practicalsolutions to the significant problems presented by the production of one ofthe noblest animal species that has been vital for the development of humanity.


Genetic testing for hereditary cancers can improve long-term health outcomes through identifying high-risk individuals and facilitating targeted prevention and screening/surveillance. The rising demand for genetic testing exceeds the clinical genetic workforce capacity. Therefore, non-genetic specialists need to be empowered to offer genetic testing. However, it is unknown whether patient outcomes differ depending on whether genetic testing is offered by a genetics specialist or a trained non-genetics clinician. This paper describes a protocol for upskilling non-genetics clinicians to provide genetic testing, randomise high-risk individuals to receive testing from a trained clinician or a genetic counsellor, and then determine whether patient outcomes differed depending on provider-type.An experiential training program to upskill dermatologically-trained clinicians to offer genetic testing for familial melanoma is being piloted on 10–15 clinicians, prior to wider implementation. Training involves a workshop, comprised of a didactic learning presentation, case studies, simulated sessions, and provision of supporting documentation. Clinicians later observe a genetic counsellor led consultation before being observed leading a consultation. Both sessions are followed by debriefing with a genetic counsellor. Thereafter, clinicians independently offer genetic testing in the clinical trial.Individuals with a strong personal and/or family history of melanoma are recruited to a parallel-group trial and allocated to receive pre- and post- genetic testing consultation from a genetic counsellor, or a dermatologically-trained clinician. A mixed method approach measures psychosocial and behavioural outcomes. Longitudinal online surveys are administered at five timepoints from baseline to one year post-test disclosure. Semi-structured interviews with both patients and clinicians are qualitatively analysed.This is the first program to upskill dermatologically-trained clinicians to provide genetic testing for familial melanoma. This protocol describes the first clinical trial to compare patient-reported outcomes of genetic testing based on provider type (genetic counsellors vs trained non-genetic clinicians). CDKN2A, incur a lifetime risk of 52–80% [The average lifetime risk of cutaneous melanoma in Australia is 5% , howeverf 52–80% . First df 52–80%  without f 52–80% . HoweverGenomics is increasingly being incorporated into clinical care to identify high-risk individuals and customise treatment . CurrentA recent cross-sectional survey on Australian Dermatologists provides insight into the current use and attitudes towards genetic testing in dermatological practice . This stThis paper describes the protocol for a trial to evaluate whether patient psycho-behavioural outcomes and satisfaction with the genetic testing process is impacted by provider type. The authors have developed a training program for providing genetic testing for familial melanoma and are piloting the program in a small cohort of dermatologically-trained clinicians  prior to wider clinical implementation. This study uses mixed methods for data collection of both quantitative and qualitative outcomes from both consumers of genetic testing, and healthcare providers. Longitudinal, validated instruments are used to analyse patient reported outcomes. Qualitative methods are employed to describe patient’s experience of living with familial melanoma and the genetic testing process. Interviews with clinicians participating in a training program provides constructive feedback to guide a future training initiative for clinical implementation.patients are people with significant personal and family history of melanoma, indicative of familial melanoma [intervention is receiving pre- and post-test genetic consultation from a non-genetic clinician trained in our pilot program. The comparator is receiving pre- and post-test genetic consultation from a qualified genetic counsellor, which is the current standard of care in Australia. The primary outcome is patient satisfaction with the genetic testing process, measured using the validated Genetic Counselling Satisfaction Scale (GCSS) [The clinical question addressed in the trial follows a PICO model  . In thismelanoma . The inte (GCSS)  two weekThis protocol has been prepared in concordance with the Standard Protocol Items Recommendations for Interventional Trials (SPIRIT) statement . The comThis research is being conducted by The University of Queensland’s Dermatology Research Centre (UQ-DRC). The UQ-DRC have been working closely with members of the public regarding skin surveillance research since 2010. The UQ-DRC have been conducting biannual consumer forums since 2016, to both inform the general public and research patients on our research progress, and to also provide a platform for consumer engagement.This protocol describes a longitudinal parallel group clinical trial, with quasi-experimental allocation using a 1:1 ratio. While the investigators have no influence in the group assignment of patients, patients are assigned to receive their pre- and post-test genetic testing consultation by either a genetic counsellor or a clinician trained in the study to deliver genetic testing. Assignment is based on patient and provider availability, which reflects the real-world clinical setting, as provider and patient availability is unpredictable.Participation in the clinician training program is offered to clinicians currently involved in research with the UQ-DRC. This cohort of clinicians include both experienced dermatologists, trainee dermatologists and dermatologically-trained clinicians. No minimum years of medical experience were required, nor are there other eligibility criteria for clinician involvement. This study aims to train between 10–15 clinicians to provide genetic testing in the clinical trial.Development of the training program for clinicians to provide genetic testing for familial melanoma predominantly follows the guiding principles described by Kolb’s Experiential learning model . This moAfter completing the workshop, clinicians observe a genetic counsellor conduct a consultation for familial melanoma, after which they lead their own consultation with a genetic counsellor observing. After both appointments the clinician reflects on the session with the genetic counsellor and any queries are answered. From then on, the trained clinician independently leads genetic testing consultations for familial melanoma within the parallel group trial. The process is repeated for the post-test disclosure session. All molecular results are discussed and reviewed in a multi-disciplinary team meeting to ensure consistency in result interpretation and upskill dermatologically trained clinicians in interpreting and explaining genetic test results.The primary outcome is patient satisfaction with the genetic testing process, measured using the GCSS , completThe flow of study procedures is illustrated using the SPIRIT schedule of enrolment, interventions, and assessments in The first baseline appointment (the ‘Pre-test appointment’) involves recording informed consent, completing online baseline questionnaire, pre-test genetic education and counselling (provided by either a trained clinician or genetic counsellor), and collection of a saliva sample. Participants are made aware (unblinded) of the qualifications of the provider leading their appointments. Visits take between 1 to 1.5 hours. The second appointment (the ‘test reporting appointment’) takes place approximately 3 months later, when genetic test results are available. The same provider, or provider type conducts the pre and post-test consultations. Any changes of provider are recorded, to allow examination of any impact on participant experience. Genetic test results are reported, using a standard protocol. If applicable, the research team discusses with the participant which family members to invite to the research study.One month after participants have received their genetic test results, they are asked to participate in a phone interview to discuss their experiences with melanoma in the family, and experiences with genetic testing. Interviews are conducted in-person or over the phone, and audio taped, then transcribed verbatim by a professional transcription service.This trial is designed as a non-inferiority study to consider whether genetic testing performed by trained clinicians is as satisfactory to participants as testing performed by genetic counsellors. The primary outcome is patient satisfaction measured on a 30-point scale (GCSS). Based on a non-inferiority limit of a two-point difference and using the previously reported standard deviation on GCSS in a cancer population of 3.87, sample size calculations were performed. Assuming type I error rate of 95% and 80% power, the required sample size is 46 participants per arm.CDKN2A mutational status in people from melanoma prone families [CDKN2A mutation, as calculated by the GenoMELPREDICT tool, are eligible to participate in the study.People at high risk of familial melanoma are identified using the GenoMELPREDICT tool, which is designed to predict families . The tooThe University of Queensland’s Dermatology Research Centre (UQ-DRC) maintains a database of volunteers interested in skin surveillance research, including those with varying risk of melanoma. This database is used to identify individuals with personal and family history indicative of familial melanoma who are contacted to invite to participate in the current study. Furthermore, the UQ-DRC receives ongoing referrals from local  Dermatologists and Skin Examination Centres for high-risk patients interested in participating in research. These prospective referrals are screened for eligibility. Eligible potential participants are initially contacted by phone to gauge interest in the study, confirm eligibility, and if receptive, a Participant Information and Consent Form (PICF) is emailed to them. They are encouraged to read over and discuss the PICF with family members and healthcare providers. A follow up call approximately two weeks later answers any questions and schedules a baseline appointment for those willing to participate.Family members of participants who receive a positive genetic test results are invited to participate in the study (cascade testing). Segregation analysis is offered to family members of individuals who receive variants of unknown significance, to assess whether the variant segregates appropriately with affection status. Recruitment of family members is first discussed with the proband , who then initiates discussions with their at-risk family members. The proband is provided with copies of the PICF to share with family members, including the contact details of the study team. If family members express an interested in participating in the pilot study, they are contacted by the study team.To achieve the research objectives, four distinct categories of outcomes are established to guide questionnaire development of the study.Experience with genetic testing: How do patients rate their experience, are they satisfied, and is there any regret in learning genetic results? Are there any differences in these outcomes when testing is provided by a clinician as compared to a genetic counsellor?Health beliefs: Does genetic testing influence personal risk perception or perceived control of future melanomas? Has testing changed or produced fatalistic beliefs?Psychological well-being: Does genetic testing cause negative psychological impact such as anxiety or depression? If so, how does this vary over time or vary with provider type? Are there personality or demographic traits that are predictors for adverse outcomes?Sun behaviour and screening: is there any change from baseline preventative behaviour after receiving genetic test results? How do these factors vary over time, by test result and by provider type?Where possible, previously validated instruments are used to address the research questions, some of which modified slightly for applicability to familial melanoma. When selecting instruments to measure health beliefs and psychological well-being, a theoretical framework was selected to guide questionnaire development. The Health Belief Model (HBM), provides a paradigm for explaining protective behaviour when faced with a health threat . PreviouThe methodology, phenomenology is used to guide development of the qualitative component of this protocol. Phenomenology is the study of a phenomena, i.e., to understand the way different aspects of life are experienced from a subjective or first-person point of view . PhenomeInterviews are conducted with trained clinicians and participants who received their genetic testing result for familial melanoma. All interviews are informed by a semi-structed interview guide . ParticiBAP1, BRCA1, BRCA2, CDK4, CDKN2A, MC1R, MITF, POLE, POT1, PTEN, RB1, TERT, and TP53. The commercial testing can produce three possible results for each gene tested; negative, positive, or variant of uncertain significance (VUS). A copy of the results report is discussed and provided to the participants. Common red hair colour variants in the MC1R gene are also reported to participants, as they are known to be associated with increased risk of melanoma, and penetrance of CDKN2A variants [Genetic testing is conducted by an accredited laboratory using a commercial familial melanoma gene panel (Invitae©). Participants are asked to sign the Invitae© consent form, if they wish to proceed with testing. The panel covers the following genes: variants .The clinical trial uses five online questionnaires, completed longitudinally by participants, comprised of previously validated scales. Audio recordings of interview data are provided to a professional transcription service. Once interview transcripts are checked for accuracy, audio recordings are deleted. Both temporary audio files and interview transcript files are stored on The University of Queensland secured server and password protected. Genetic test results, and other appointment notes, are saved on the University’s secured server, with password protection.The primary outcome is the survey response to the GCSS at timepoint 3 (2 weeks after test results are disclosed). Secondary outcomes include patient’s long-term psychological impact of genetic testing, as well as any impact on engaging in protective behaviours, as captured using previously validated scales  approval received from both Metro South Health HREC (HREC/19/QMS/58196) and The University of Queensland HREC (#2019002762), and prospectively registered with the Australian New Zealand Clinical Trial Register (ANZCTR12620000043932). Any protocol modifications will be communicated to relevant parties. Study findings will be disseminated through peer-reviewed publications, conferences, and non-peer reviewed media outlets.The study received Human Ethics approval in November 2019, and recruitment commenced March 2020. An HREC amendment was approved in March 2020 to use teleconferencing for patient appointments. Due to the Covid-19 global pandemic the study was put on temporary hold for several months before commencing again in August 2020. The study has faced multiple other appointment postponements in response to local outbreaks and restrictions. Recruitment is continuing through 2022/23.This research addresses an important step towards meeting an emerging health challenge of integrating genomic medicine into routine clinical care. Mainstreaming genomic testing, by upskilling oncology specialists has already made a significant impact for participants with breast and ovarian cancer, through improving access to testing, reducing waiting periods, and significant healthcare cost savings ,12. The The successful development of an alternate health service delivery model requires engagement with stakeholders, including both consumers and healthcare providers to gauge receptiveness and perceived need. In conjunction with this research, the authors have recently performed a cross-sectional survey of Australian Dermatologists’ perceptions and use of genetic testing in practice . The resTo our knowledge, this is the first study to allocate participants to receive genetic testing from a genetic counsellor or a trained non-genetics clinician and determine whether provider type affects psychological and behavioural outcomes. The convergence of longitudinal quantitative participant reported outcomes, with qualitative insight from both participant consumers and from healthcare providers, provides both depth and breadth of understanding for delivery of genetic testing for familial melanoma. If findings support provision of genetic testing by clinicians, outcomes from this research will directly inform future training programs for dermatologists, facilitating the integration of genetic testing into mainstream dermatology clinics.S1 Fig(PDF)Click here for additional data file.S2 FigSemi-structured interview guides used for both participant and clinician interviews.(PDF)Click here for additional data file.S3 Fig(PDF)Click here for additional data file.S1 File(DOCX)Click here for additional data file.S2 File(PDF)Click here for additional data file.


Gekko japonicus, i.e., Schlegel’s Japanese Gecko, is an important species which is widely distributed in East Asia. However, the information about population genetics of this species from China remains unclear. To address this issue, we used sequences from a fragment of the mitochondrial protein-coding gene cytochrome c oxidase I to estimate genetic diversity, genetic structure, and historical demography of G. japonicus populations from China. Phylogenetic analysis indicated that G. japonicus had a close relationship with Gekko wenxianensis. A total of 14 haplotypes were obtained, of which haplotype 1 was the most common and widely distributed. The genetic diversity of G. japonicus was comparatively low across different geographic populations. The populations of G. japonicus were divided into four groups which exhibited low levels of genetic differentiation, and expressed an unclear pattern of population structuring. In addition, potential population expansion of G. japonicus has occurred as well. Overall, these results demonstrate that the populations of G. japonicus reveal low genetic diversity in China, which is attributed to the founder and bottleneck events among populations. Our results will provide meaningful information on the population genetics of G. japonicus and will provide some insights into the study of origin of populations. G. japonicus, known as Schlegel’s Japanese Gecko, is a nocturnal gecko which was reported to be distributed in China, Japan, and Korea [G. japonicus [G. japonicus an excellent flagship species for many issues in ecological balance and biological evolution. Predictions of present and future distribution studies which were based on MaxEnt modeling, suggest that suitable habitats are currently located in coastal cities of Japan, China, and Korea, as well as in isolated patches of inland China. Due to climate change, suitable habitats are expected to shrink along coastlines, particularly at the coastal edge of climate change zones [G. japonicus are growing, as are the range expansions of G. japonicus in Korea and Japan [G. japonicus from China is inferred to be the source population, which had higher genetic diversity and more private alleles compared to the populations of G. japonicus in Japan and Korea [G. japonicus in China will provide important information about the origin and evolutionary of this species. Nevertheless, to date, information of its populations, particularly from China, is unavailable. The genetic diversity, genetic structure, and historical demography of G. japonicus from China remains unclear.nd Korea . Currentaponicus . Undoubtge zones . Recent nd Japan . Geneticnd Korea . In brieG. japonicus in China includes the eastern coast extending westward to eastern Sichuan Province, northward to southern Shaanxi, and Gansu Provinces, which overlaps with Gekko scabridus, Gekko hokouensis, Gekko subpalmatus, and Gekko chinensis [G. japonicus and other species of gecko could be separated by morphological and molecular manners [The current distribution of hinensis ,3. G. ja manners . In some manners ,6. By de manners ,8,9,10.  manners ,12. Mean manners . Among t manners ,14. This manners ,16. SpecG. japonicus, 325 specimens were collected from 37 sampling sites in China. The sequences of COI genes were obtained from these 325 specimens in China. Subsequently, phylogenetic analyses of G. japonicus with other species of Gekko were conducted to clarify the genetic relationship among the genus Gekko, which is necessary for the further understanding of the evolutionary history of Gekko. Genetic structure, genetic diversity, and historical demography of G. japonicus populations were determined. To our knowledge, this study is the first to understand the genetic structure, genetic diversity, and historical demography of G. japonicus populations in China based on the mitochondrial gene COI.To detect the genetic structure and diversity of G. japonicus in China from 2008 to 2017  using map datum WGS84. The sample information that was used is shown in A total of 325 individuals were collected from 37 sampling sites that covered most of the range of  to 2017 . They weTaq PCR Master Mix Ⅱ , 0.7 µL of genomic DNA, 0.4 µL of each primer, and 8.5 µL of deionized water. The cycle profiles for the PCR were as follows: initial denaturation of 3 min at 95 °C, followed by 5 cycles of 30 s at 95 °C, annealing for 1 min at 45 °C, an initial extension for 2 min at 72 °C; followed by 35 cycles of 30 s at 95 °C, annealing for 1 min at 51 °C, an initial extension for 2 min at 72 °C; and final extension for 5 min at 72 °C. PCR products were visualized on a 1% agarose gel stained with 4S Red Plus, Bi-directional sequencing was performed using the primers RepCOI-F (5′-TNTTMTCAACANACCACAAAGA-3′) and RepCOI-R (5′-ACTTCTGGRTGKCCAAARAATCA-3′) [Genomic DNA was extracted from liver tissue using DNA extraction kit  according to the manufacturer’s instructions, and then the quality and integrity of the DNA samples were checked by agarose gel electrophoresis. The extracted DNA was stored at −20 °C. A partial fragment of the COI was amplified by the polymerase chain reaction (PCR) using primers: VF1-d (5′-TTCTCAACCAACCACAARGAYATYGG-3′) and VR1-d (5′-TAGACTTCTGGGTGGCCRAARAAYCA-3′) . AmplifiATCA-3′)  by Nanjihttps://www.ncbi.nlm.nih.gov (accessed on 1 February 2022)) for published COI of some species of the genus Gekko. Then forty-four COI sequences were retrieved and downloaded for further analyses , Gekko gecko group (Gekko gecko) and Gekko monarchus group (Gekko kikuchii), and Hemidactylus dracaenacolus and H. granti ).The K2P model was used to calculate genetic distances using MEGA 7.0 . For phyCT) [h) [π) for each population were estimated using DnaSP 6.0 program [ST using analysis of molecular variance (AMOVA) [G. japonicus were estimated from a TCS network using PopART v1.7 [D statistic [Fs [To identify similar groups of populations and to evaluate the amount of genetic variation among the partitions, a spatial analysis of molecular variance was conducted in SAMOVA v1.092 . SeveralCT) . The numCT) [h) , and nuc program . Spatial (AMOVA) . In addiART v1.7 . The reltatistic , Fu’s Fsstic [Fs  and mismstic [Fs . Mismatcstic [Fs  were calstic [Fs .G. japonicus were obtained and further analyzed. The sequences were deposited in GenBank under project SUB12126169. The average frequencies of T, C, A, and G were 28.6, 30.7, 21.1, and 19.6%, respectively. The sequenced region contained 564 conserved sites, 75 variable sites, and 16 parsimony informative sites. The ratio of transform to transition (Ts/Tv) based on the K2P base substitution model is 2.2.A total of 325 mitochondrial COI gene sequences of G. japonicus group cluster well together and form sister groups with Gekko gecko group and Gekko monarchus group. ML tree and BI tree revealed that the G. swinhonis samples were separated into A1, A2, and B. Both in BI and ML tree, G. japonicus cluster formed a sister group with G. wenxianensis, which suggested that G. japonicus has a close relationship with G. wenxianensis. Then, G. swinhonis was clustered with G. auriverrucosus and the two formed a sister group with G. subpalmatus. In addition, a total of 12 individuals were collected from Anqing, Anhui Province, of which 11 individuals were clustered into G. japonicus, undoubtedly. AHAQ06 draws our attention by forming a sister group with all the G. japonicus. Subsequently, according to the COI genes of the AHAQ06 and 10 gecko species of China, interspecific and intraspecific genetic distance was calculated to further illustrate the reliability of the phylogenetic results , the genetic distance between the G. subpalmatus and G. gecko was the largest (42.0–44.9). Meanwhile, the genetic distance within the G. auriverrucosus was the smallest (0.3 ± 0.2) and the genetic distance within the G. scabridus was the largest (4.3 ± 0.6). Moreover, the genetic distance between AHAQ06 and G. japonicus had reached 12.0–12.9. The genetic distances largely coincide with the phylogenetic results. Therefore, there are large differences between AHAQ06 and G. japonicas at the molecular level, which indicate that AHAQ06 is a special individual to be further studied. Hence, AHAQ06 is excluded from the population-level data set. A total of 324 mitochondrial COI gene sequences was depicted in further population genetic analysis.In the study, the ML tree and BI tree showed that all species formed a monophyletic group with high bootstrap and posterior probability values . Species results . Except G. japonicus (h was the HNYZ population (h = 0.591), whereas the lowest was the HNYY and HNCB populations (h = 0). In general, total genetic diversity values were low between populations , compared to Chilabothrus inornatus [Fourteen haplotypes were identified among the 324 sequences (AHAQ06 are excluded) in aponicus . The mosaponicus . Geograpnornatus .CT) was the highest (0.39527) when K = 4  and were responsible for 39.527% of the variance. The non-significant differentiation among populations within groups (Fsc = 0.01382) were responsible for 0.84% of the variance. Additionally, the FST = 0.40362 (p < 0.05) indicated low genetic diferentiation among four groups , indicating a distinct departure from a null hypothesis with selective neutrality and population equilibrium. The results of the mismatch analysis of G. japonicus did not exclude the sudden expansion model due to non-convergence. The neutrality tests results implied the possibility of population expansion [p > 0.05) and the HRag value  under the spatial expansion models failed to reject the spatial expansion model.A total of fourteen haplotypes forms a network exhibiting a star like topology with the haplotype Hap 1 and Hap 5 at the center . Hap1 waxpansion ,38. The G. japonicus in China. Phylogenetic analyses of G. japonicus with 9 other species of geckos were also conducted to clarify the genetic relationship among the genus Gekko. Additionally, the genetic diversity and genetic structure of G. japonicus in China was evaluated via mitochondrial COI. To the best of our knowledge, this study is the first to examine the mitochondrial genetic diversity of G. japonicus in China using the COI gene. Our study contributes a taxonomic dataset and also provides significant insights into the population genetics of an ecologically vital reptile species in China.In this study, the mitochondrial COI gene was explored for the identification and analysis of the genetic diversity and genetic structure of G. japonicus group was well supported, and the G. swinhonis were divided into A1, A2, and B. This result was consistent with a previous work using mitochondrial cytochrome b gene and 10 microsatellite loci, which revealed two genetic lineages in G. swinhonis [G. japonicus, we employed genetic distance to demonstrate the reliability of the phylogenetic analysis and the specificity of the AHAQ06. Phylogenetic analyses showed that G. japonicus has a close genetic relationship to G. wenxianensis in the genus Gekko  when k = 4 was the partition . Long-distance dispersal events tend to result in reduced genetic diversity due to sequential founding events and genetic drift [G. japonicus populations have historically experienced founder and bottleneck events causing low genetic diversity. Additionally, phylogenetic relationships between haplotypes show that no clear genetic lineage formed in populations of G. japonicus. Seven private haplotypes are found, which may be partially explained by limited migration and gene flow among them.SAMOVA provided the highest significant Fartition . Subsequic drift . Moreoveic drift . In the G. japonicus are not equal among the groupings in our study and this may have an effect on the diversity measures. Hence, more elaborate studies involving a relatively uniform sample size may uncover the mitochondrial genetic diversity of G. japonicus from of China. Admittedly, as our results are based solely on mtDNA sequence data, they should be viewed with some caution, since our conclusions might be biased due to the intrinsic mutation rate, mode of inheritance, and effective population size of mtDNA markers. Thus, further studies integrating ecological, morphological, and molecular (using mtDNA and nuclear markers) data are necessary to understand the evolutionary history of G. japonicus from China. Such studies will also give deep insight into the evolution of G. japonicus from China. It will further set the base for further genetic studies that would help design effective Ecological Resource Management policies. Also, the genetic approach used in our study can be extended in studying the population genetics of other reptile species in China.It is worth noting that the sample sizes of