Bos indicus maternal signal in Nigerian cattle is attributable to vulnerability bottleneck of mtDNA lineages and concordance with the view of male zebu genetic introgression in African cattle. Our study shades light on the current genetic diversity in Nigerian cattle and population history in West Africa.The African cattle provide unique genetic resources shaped up by both diverse tropical environmental conditions and human activities, the assessment of their genetic diversity will shade light on the mechanism of their remarkable adaptive capacities. We therefore analyzed the genetic diversity of cattle samples from Nigeria using both maternal and paternal DNA markers. Nigerian cattle can be assigned to 80 haplotypes based on the mitochondrial DNA (mtDNA) D-loop sequences and haplotype diversity was 0.985 + 0.005. The network showed two major matrilineal clustering: the dominant cluster constituting the Nigerian cattle together with other African cattle while the other clustered Eurasian cattle. Paternal analysis indicates only zebu haplogroup in Nigerian cattle with high genetic diversity 1.000 ± 0.016 compared to other cattle. There was no signal of maternal genetic structure in Nigerian cattle population, which may suggest an extensive genetic intermixing within the country. The absence of  Bos taurus and the Indian Sub-continent for B. indicus  markers in the control region and the entire mtDNA genome to understand phylogenetic tree models for describing origin, divergence times and domestications of cattle and their population expansion to different parts of the globe . MtDNA s. taurus  and hapl. taurus  both defrevealed , 2009. Trevealed . Majoritrevealed , with norevealed , with onrevealed .Genetic studies on paternal Y-chromosomal DNA markers have previously reported the frequency of both haplogroups Y1 and Y2 for taurines and of Y3 haplogroup an exclusive for zebus . Some auNigeria, a country in West Africa harbors both the taurine and zebu cattle  and theiTo disclose the genetic diversity in Nigerian cattle, we employed the use of both mtDNA and Y-chromosomal markers, which have been widely used in assessing the diversity and phylogeographic structure of many domestic animals . In thisAll experimental procedures in the present study were performed in accordance to Research Guidelines for the Institutional Review Board of Kunming Institute of Zoology, Chinese Academy of Sciences (SMKX2017009) and the Central Abattoir, Ibadan, Ministry of Agriculture and Rural Development, Oyo State, Nigeria. Several cattle are usually transported from farms in different states in Nigeria to the Central Abattoir in Ibadan. Therefore, all cattle samples were then collected at the Central Abattoir, Ibadan.n = 19 females; n = 3 males), Kano State , Katsina State , Sokoto State , Mambilla plateau in Taraba State , Zamfara State , Oyo State  and Jos city in Plateau State . During sample collection, genetically unrelated cattle from the eight states in Nigeria, ecological and geographical perspectives were considered. This included randomly sampling of at least two animals per household and only from those households located approximately 0.5 km further apart. Farmers were also interviewed on the pedigree information of their animals prior to carrying out blood collection. Blood samples were kept in 95% ethanol at room temperature before transportation to the laboratory. Samples were stored at 4 °C for immediate use, or at −80 °C for later use.A total of 139 Nigerian cattle individuals  were sampled from farmer’s herds in eight different States in Nigeria as follows ; Kaduna Bos grunniens: Accession no. MN398192, Yak  intron 10 was used as previously described  and the generated products from this step were further purified by alcohol precipitation. Lastly, we used ABI PRISM 3730 automated DNA sequencer  to sequence the purified products. All sequences were assembled in SeqMan Lasergene package in DNASTAR software.We have sequenced 286 bp of the bovine Y-chromosome in 20 Nigerian cattle  and S3 iescribed  for the B. taurus mtDNA sequence ((GenBank accession no. V00654); ; ). Variatequences . The polH) and polymorphic sites (PS), haplotype diversity (HD), nucleotide diversity (π), the mean number of nucleotide differences (Df) and their standard deviations (SD) estimated across all African populations used in this study. Notably, the comparisons of the genetic diversity estimates were considered for only those populations with sample size above 5.MitoToolPy_Linux  was used and bootstrap test was employed at 1,000 replications so as to assess the confidence of each node (www.fluxus-engineering.com).To investigate the evolutionary relationship of Nigerian cattle with other cattle samples mined from GenBank  and S2, ach node . To furtach node  was geneviz the Nigerian cattle as a single cluster, Nigerian cattle vs the other African countries but also vs cattle from Europe and West Asia. The levels of significance in each hierarchical cluster tested were evaluated using FST parameter at a significant P level of 0.05.To infer the matrilineal genetic variation within populations, among populations, and groups of populations, analysis of molecular variance (AMOVA) was carried out following 50,000 permutations in Arlequin v3.5 software. The analysis was conducted for Nigerian cattle at various hierarchical levels r”  and B. indicus (I1 and I2) lineages as expected  with exceptional of variation among populations within groups for Nigerian and European cattle . The FST distance values between most Nigerian cattle sub-populations were low . Our AMOVA results complemented by genetic distance estimates suggest general absence of maternal genetic structuring in Nigerian cattle sub-populations, likely due to extensive genetic intermixing within the country.Analysis of molecular variance incorporating the eight populations from Nigeria showed that more than 99% of the total genetic variation present in Nigerian cattle occurred within individuals . Furtherwere low . HoweverD −2.315 (P < 0.05) and Fu’s FS statistics −26.203 (P < 0.05) on the other hand were both negative and significant indicating an agreement of recent population growth and expansion respectively. Cattle population from the Western region of Nigeria showed Tajima’s D value of 0 possibly due to only three individuals were sampled, which might indicate that the population in that region evolved as per mutation drift equilibrium with no evidence of selection.To elucidate the demographic dynamics of Nigerian cattle, mismatch distribution patterns, for each geographical region in Nigeria were assessed . The misMW284951–MW284970. Our results show that all Nigerian cattle belong to haplogroup Y3 solely a B. indicus haplogroup due to similar mutations (C) and Y3b  haplotype families (B. grunniens (yak) and B. bison, these two latter populations are considered distantly related populations to the major lineages of domestic cattle , and Y3C (or Y3a)  , with Y3ears ago . Howeverears ago .Bison bison), the domestic yak (B. grunniens) and Nigerian cattle. This was clearly confirmed by the patrilineal phylogeny where some of the Nigerian cattle clustered closely with yak, the B. grunniens and B. bison (B. javanicus). Nonetheless, previous studies have also reported possibility of secondary introgression events that might have occurred from the wild oxen stock into the gene pool of domestic cattle during early domestication  North West region (B) North East region and (C) the overall Nigerian cattle as a whole.Click here for additional data file.10.7717/peerj.10607/supp-3Supplemental Information 3Source of the data for the haplogroups was retrieved from Click here for additional data file.10.7717/peerj.10607/supp-4Supplemental Information 4Clade colours represent samples fromdifferent geographical locations: Green-Nigeria, Blue-Europe, Orange-South Asia, Cyan- Outgroups.Click here for additional data file.10.7717/peerj.10607/supp-5Supplemental Information 5Click here for additional data file.10.7717/peerj.10607/supp-6Supplemental Information 6Click here for additional data file.10.7717/peerj.10607/supp-7Supplemental Information 7Click here for additional data file.10.7717/peerj.10607/supp-8Supplemental Information 8Click here for additional data file.10.7717/peerj.10607/supp-9Supplemental Information 9Click here for additional data file.10.7717/peerj.10607/supp-10Supplemental Information 10Click here for additional data file.10.7717/peerj.10607/supp-11Supplemental Information 11Click here for additional data file.10.7717/peerj.10607/supp-12Supplemental Information 12Click here for additional data file.10.7717/peerj.10607/supp-13Supplemental Information 13Click here for additional data file.10.7717/peerj.10607/supp-14Supplemental Information 14Click here for additional data file.10.7717/peerj.10607/supp-15Supplemental Information 15Click here for additional data file.10.7717/peerj.10607/supp-16Supplemental Information 16Click here for additional data file.


Rhododendron is an iconic group with an extraordinary diversity in southwest China. However, it remains unknown whether the recorded species therein comprise independently evolving lineages or artificially delimitated morphological entities. In this study, we carried out species delimitation of four Rhododendron species in the R. vernicosum-R. decorum species complex based on morphological analyses and population genetic data from nuclear simple sequence repeats (SSR) markers. We randomly selected a total of 105 specimens of different individuals identified as four species across their distributional ranges to examine the statistically distinct phenotypic clusters based on 19 morphological traits. Similarly, we genotyped 55 individuals of four species from 21 populations using 15 SSR markers. The morphological analyses sorted R. decorum and the other three species into two different phenotypic clusters. The genetic clusters were consistent with the morphological clusters. However, we also recovered the third genetic cluster, comprising six R. vernicosum populations and containing the admixed genetic compositions of the other two distinct genetic clusters. This hybrid group was morphologically similar to the typical R. vernicosum  but with more genetic ancestry from R. decorum. Based on our findings, we identify two distinct species and one putative hybrid group due to introgression in the R. vernicosum-R. decorum species complex. We propose to merge R. verruciferum and R. gonggashanense into R. vernicosum based on genetic compositions and our morphological analyses. The hybrid group inferred from our findings, however, needs further investigations.Delimitating species boundaries is the primary aim of biological classification and could be critical for evaluating the evolving process of species and conserving biodiversity.  Accurate species delimitation is crucial for biodiversity conservation because an error in species recognition will result in wasted effort in species conservation and may cause erroneous scientific inference when using species as the basic analysis unit . This isRhododendron L. Most of the recorded 1,000 species in this genus are distributed in southwest China  failed to diagnose the closely related species and detect hybridization and introgression due to the lack of distinct genetic divergences in these DNA sequences  Do R. verruciferum and R. gonggashanense comprise two independent morphological and genetic clusters? and (2) Did hybridization and cryptic introgression occur under the similar morphology in this species complex?In this study, we aimed to delimitate closely related species in a large and taxonomically difficult plant group, st China . Howeverst China . Becauseequences . Howeverequences . Therefo decorum ,b. HowevRhododendron vernicosum-R. decorum species complex belong to subsection Fortunea within the section Ponticum of the subgenus Hymenanthes based on the traditional taxonomy (R. decorum was described to have bigger stigmas than other threes (R. decorum subsp. parvistigmaticum) was described to also have small stigmas. In addition, differences from leaf base, gland color, glandular hairs of pedicles, and styles and corolla size were used to distinguish R. vernicosum, R. verruciferum, and R. gonggashanense  and another possible storage (CDBI). Therefore, we explored and collected the specimens from the type locality of both species: Geka village, Daofu County, and Moxi valley, Gongga Mountain, Kangding city, respectively  in the herbaria with taxonomic names determined by specialists for final morphological clustering analyses. In total, we used 105 specimens of different individuals (46 ones from our field exploration and 59 ones from the herbaria collected before) from different locations across the distributional ranges of the four species for final morphological data analyses .2. Subsequently, we conducted principal coordinates analysis (PCoA) and hierarchical clustering on the standardized variables in the software. We used ANOVA that attached in the software PAST v3.0 to compare variances of the quantitative and qualitative morphological variables between groups detected by PCoA. For computing data in the hierarchical clustering analysis, we chose the Euclidean as similarity index and set the bootstrap values (“Boot N = 999”) to establish a clustering dendrogram.Based on the previous taxonomic treatments and descriptions of these four species ,b, we obNa), the observed heterozygosity (Ho) and expected heterozygosity (He) were calculated  from 1 to 10 with a set of 1200,000 steps in Markov chain following a burn-in of 600,000 steps  between successive K-values and the log probabilities of data [ln P (D)], we determined the optimal genetic cluster (K) using a combination of the Pritchard method (FST) between four species using GenALEx v6.501.We conducted a population genetic clustering analysis of all genetic polymorphisms using the software STRUCTURE v2.3.4 . Twenty 00 steps . Both thd method  and the d method  performed method . For theR. vernicosum, R. gonggashanense, and R. verruciferum, and the other cluster (Cluster B) included R. decorum. The test of variances among 19 morphological traits using ANOVA (P < 0.05) in PAST showed a significant difference between two groups (R. decorum formed a reasonably well-supported clade [bootstrap support (BS) = 99] and the remaining three species in R. vernicosum-R. decorum species complex were resolved into a strongly supported (BS = 100) morphological clade , and the individuals of R. decorum in the other cluster (cluster B). There is no distinct phenotypic difference between R. vernicosum, R. gonggashanense, and R. verruciferum. Morphological traits examined in this study not only included the traits referred in the key to discern different closely related species of the subsection Fortunea  in PCoA analysis accounted for 28.46 and 8.61% of the total normalized variance, respectively . Arrangeo groups . The anaal clade . Moreovernicosum . Both thFortunea , but alsK = 3) (K = 3). The first cluster comprised all the individuals of R. decorum, the second cluster comprised six populations of R. vernicosum and the third cluster comprised seven populations of R. vernicosum and all individuals of R. gonggashanense and R. verruciferum. Interestingly, the second cluster also included the genetic introgression from the third cluster. When the value of K was 2 (K = 2), two relatively pure genetic groups were identified for R. decorum and R. vernicosum-R. gonggashanense-R. verruciferum while the second group comprised six populations of R. vernicosum with genetic mixtures from the other two genetic groups particularly from the R. decorum group  ,2, dividK = 3) , K = 3. um group .R. vernicosum (STF = 0.075) was detected  and R. gonggashanense and R. verruciferum were obviously low . In addition, the genetic differentiation between R. gonggashanense and R. verruciferum was similarly low (STF = 0.05).Genetic differentiation between two genetic groups representing six and seven populations, respectively, from detected . HoweverR. verruciferum and R. gonggashanense should be incorporated into R. vernicosum. In addition, morphological traits that were used to differentiate R. gonggashanense R. vernicosum, and R. verruciferum, including gland or glandular hairs color in pedicel, style and ovary, and the shape or size of the leaf and corolla  . In fact, these two groups (Cluster A and B) were distinguished by numerous characters, including the color of spot in inner corolla and corolla color, the length of rachis and pedicle, and the distributional altitudes. In addition, both R. verruciferum and R. gonggashanense were recorded to confined in two very small sites in southwest China. The distributional range of R. vernicosum obviously encompasses these two small sites, as R. vernicosum is relatively widespread in southwest China (tively.) ,b. Both rnicosum . The samst China .R. verruciferum and R. gonggashanense were likely described based on the intraspecific variations of the widespread R. vernicosum. Two distinct genetic groups were recovered for R. vernicosum and R. decorum, respectively, when the population genetic group (K) is 2 (K = 2). All individuals of R. verruciferum and R. gonggashanense were placed in the genetic group represented by seven populations of R. vernicosum. In the R. vernicosum group, the individuals collected from the type locality  of R. vernicosum were included. When the optimal genetic cluster is 3 (K = 3), another genetic group was identified for the six populations of R. vernicosum, while still retaining R. verruciferum and R. gonggashanense within the R. vernicosum genetic group. All of these findings suggest that R. verruciferum and R. gonggashanense are conspecific to R. vernicosum. The taxonomically revised R. vernicosum should comprise at least seven populations of R. vernicosum, R. verruciferum, and R. gonggashanense.Our population genetic analyses of the four species based on 15 SSR markers revealed that (K) is 2 , K = 2. ter is 3 , K = 3, R. decorum and R. vernicosum-R. gonggashanense-R. verruciferum populations. When K = 2 (R. decorum. This group comprises six populations of R. vernicosum, whose morphological traits examined herein showed high similarity with the R. vernicosum-R. gonggashanense-R. verruciferum genetic group without distinct phenotypic differences (R. vernicosum, although less than that from R. decorum, might have contributed greatly to this similarity in the examined morphological traits. In addition, when K = 3, this hybrid genetic group comprised one distinct group from the other two groups (We identified three genetic groups by genotyping 21 populations of the four species. Especially, we recovered one hybrid genetic group between the other two groups represented by en K = 2 , the genferences . The geno groups , suggesto groups .Rhododendron (R. decorum and R. vernicosum groups occupies a different distributional range than the ones occupied by the other two species. It may likely represent a new hybrid species as other hybrid species reported previously by some studies in southwest China (R. decorum and R. vernicosum group. It may might result from long-distance seed dispersals after hybridization between two parents because the winged Rhododendron seeds can be dispersed by wind (Because of high outcrossing abilities and incomplete reproductive isolations, interspecific hybridizations occur frequently in the genus odendron . These ist China . However by wind . Alterna by wind . However by wind , for exaR. vernicosum-R. decorum species complex based on statistical morphological analyses and population genetic data from SSR markers suggest that R. verruciferum and R. gonggashanense should be taxonomically reduced to R. vernicosum. In addition, some populations placed under R. vernicosum based on the currently used morphological traits for species delimitations may represent one likely hybrid species because this group comprises multiple populations with a distinct distribution. Such a hybrid group may have started independent evolution as a separate lineage. The genetic ancestry of this hybrid species is derived more from R. decorum than from R. vernicosum although it is morphologically similar to R. vernicosum. Further studies and confirmations are needed based on the detailed examination of more morphological traits at the population level and genomic analyses of the currently sampled populations as well as more from the total distributional ranges of the three identified genetic groups. Only after rigorous analyses, can the taxonomic revisions be correctly performed for the R. vernicosum-R. decorum species complex.In conclusion, our findings on the The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.JL supervised the writing. XM collected materials, designed experiment, and wrote the manuscript. JW extracted DNA and analysed SSR data. NS revised the manuscript. YM provided the ideas. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


We are pleased to announce a Special Issue on the Genetic Basis and Epidemiology of Myopathies. This Special Issue is collecting papers pertaining to various lines of research focusing on the genetic basis and the epidemiology of myopathies. The Guest Editors’ note combines the contributing authors’ reviews and findings of relevant research, and we hope that future studies on myopathies will attempt to confirm these findings and, additionally, evaluate supplementary phenotypic and histological expressions of myopathies, as well as genetic factors in their pathogenesis. Congenital myopathies are a group of genetic muscle disorders clinically characterized by wide genetic and clinical heterogeneity. Identifying the candidate genes responsible for the various histological and phenotypic expressions of myopathies is of extreme importance for both highlighting the genetic basis of many forms of myopathies and improving treatment efficacy. While the genetic basis of myopathies has been extensively investigated, the genes involved in defects, especially cognitive ones, are still unknown.International Journal of Molecular Sciences has attracted both research papers and reviews that contribute to our understanding of the genetic factors in the pathogenesis of myopathies and their epidemiology, their treatment, and their impact on the patients’ cognitive abilities. The first paper, titled “Description of a Novel Mechanism Possibly Explaining the Antiproliferative Properties of Glucocorticoids in Duchenne Muscular Dystrophy Fibroblasts Based on Glucocorticoid Receptor GR and NFAT5”, by [2+. The fourth paper, titled “Preclinical Research in Glycogen Storage Diseases: A Comprehensive Review of Current Animal Models”, by [This Special Issue of the AT5”, by , examineAT5”, by  investigAT5”, by  exploresels”, by  attemptsels”, by  presentsels”, by  providesels”, by  classifiels”, by  classifiels”, by  presents


Time courses of search behavior displayed a continuous interest in STIs with synchronal and national rather than regional peaks. Volumes of search queries lacked periodic patterns. Based on the findings of this study, a more open public discussion about STIs with linkage to increased media coverage and clarification of responsibilities among all STI-treating disciplines concerning management of STIs seem advisable.Incidence of sexually transmitted infections (STIs) such as chlamydia, gonorrhea, and syphilis has increased in recent years in the US and in European countries. In order to implement effective educational programs, the interests of target populations have to be identified. Since the internet is an important source of information-gathering on health issues, this study investigates web search data in large German cities related to STIs. Google Ads Keyword Planner was used to identify STI-related terms and their search volume in eleven German cities from June 2015 to May 2019. The data obtained were analyzed descriptively with regard to total search volumes, search volumes of specific thematic areas, and search volumes per 100,000 inhabitants. Overall, 741 terms with a total search volume of 5,142,560 queries were identified, with more than 70% of all search queries including a specific disease and “chlamydia” being the overall most often searched term ( Worldwide, more than one million sexually transmitted infections (STIs) occur every day, resulting in approximately 376 million new infections with chlamydia, gonorrhea, syphilis, and trichomoniasis per year ,2. AdditTo target STIs effectively, different control strategies are applied worldwide, such as increased screenings combined with partner notifications and simplified therapies in order to reduce the time of infectiousness. Furthermore, sexual health education is intensified . LimitedHealth education programs inform target populations and often aim at inducing behavioral changes . In ordeIn order to improve sexual health education programs, this study investigates German inhabitants’ interest in STIs and analyzes whether there were regional and periodic differences in search interest and frequency in eleven German cities.A retrospective longitudinal study displaying the web search volume of terms related to STIs in eleven large German cities between June 2015 and May 2019 was conducted. The selected cities were Berlin, Hamburg, Munich, Cologne, Frankfurt, Stuttgart, Dusseldorf, Dortmund, Leipzig, Hannover, and Nuremberg, which are all among the fifteen biggest cities in Germany and are representative of all German regions . By usinAll identified search terms were reviewed, and keywords that did not refer to the initial search term, “venereal diseases” , were excluded from further analysis. The remaining keywords were assigned to the following seven categories: “Specific diseases” , “gender” , “symptoms” , “diagnostics” , “treatment” , “transmission” , and “general” . Within the category “gender”, keywords containing male references  and female references  were differentiated. Keywords that fit into multiple categories were assigned to all of them.Descriptive data were generated for the identified and categorized keywords. To compare the search volume within the cities, the search volume was calculated in relation to the average number of inhabitants between the years 2015 and 2019 and displayed as number of searches per 100,000 inhabitants ,30. To an = 1,196,160), “genital warts” , “HIV” , “clap” , and “venereal diseases”   .n = 1,241,130), Hamburg , and Munich , while the lowest number of searches was found in Nuremberg . However, when calculating the search volume per 100,000 inhabitants, Frankfurt and Stuttgart had the highest search volumes, with 52,669 and 51,959 queries per 100,000 inhabitants, respectively  was 1.7 times higher than the search volume of keywords including female references . Neither the search volume of keywords with female references nor the search volume of keywords with male references per 100,000 inhabitants differed significantly between cities. The category “specific diseases” had by far the highest search volume with 3,685,580 queries . In this category, the five most common keywords were “chlamydia” , “genital warts” , “HIV” , “clap” , and “gonorrhea” . Since clap is the colloquial term for gonorrhea, these two keywords together represent 15.36% of the category “specific diseases”. In the category “symptoms”, the five most common keywords include either “chlamydia” or “clap”. Furthermore, the word “symptoms” itself was predominant as opposed to naming specific symptoms such as “discharge”. In the category “treatment”, four out of the top five keywords contain the word “physician” (21.74%), but none included “chlamydia” . The sean = 131,660; 1081 searches/100,000 inhabitants) and the lowest in August 2016 . The biggest range in number of searches within one city was found in Dusseldorf with 1678 searches per 100,000 inhabitants in June 2015 compared to 694 searches per 100,000 inhabitants in April 2016 and August 2018, displaying a range of 984. Considering all cities, the average monthly number of searches was 9554, resulting in 863 queries per 100,000 inhabitants. The highest number of searches was in October 2015 , Frankfurt , Dusseldorf , and Leipzig . Another common peak was identified in November 2017.In addition, the time course of search terms related to chlamydia, gonorrhea/clap, and HIV was investigated. Regarding all keywords containing “chlamydia”, two main peaks were observed in October 2015 and November 2017. Keywords with “gonorrhea/clap” showed especially high peaks in July 2017, in March 2018, and in October 2018, and keywords containing “HIV” peaked in November 2015 and February 2016 . The aim of the presented study was to assess STI-related web search data to examine people’s interest and to assess whether there were regional or periodic differences across German cities. It was found that the vast majority of searches focused on specific diseases such as chlamydia and gonorrhea. No considerable differences between the cities regarding search interest and time course were observed.n= 21,701 searches/100,000 inhabitants) and also higher than that of “skin cancer”  [During the analyzed time period of four years, a total of 5,142,560 queries were identified in the eleven large German cities examined, indicating 41,411 queries per 100,000 inhabitants. A trend toward fewer searches per 100,000 inhabitants in larger cities compared to smaller cities was seen. This observation remained after adjustment to the proportion of foreigners in the analyzed cities and has already been described in the context of other Google data analyses ,33. Overbitants) ,33, reprbitants) ,35. Withbitants) . A seconbitants) ,36. TherAnalyzing the categories and their most frequent keywords, it immediately becomes apparent that more than 70% of all searches included a specific disease, especially chlamydia. Chlamydia represents the most common bacterial STI in Germany . AdditioToday show, and in February 2016, German scientists reported a breakthrough toward curing HIV [A relatively consistent monthly search volume was seen during the whole study period except for a few peaks. Nevertheless, the majority of cities had their largest search volume in October 2015, which was mainly caused by an increase of searches for chlamydia-related keywords, and which indicates a national rather than regional trend. In contrast to studies that investigated pruritus, skin cancer, or borreliosis, no seasonal variations were detected ,32,33, wring HIV ,51. TherIn general, the internet is frequently used as a source for health-related information ,52, and In summary, the study results showed a relatively high search volume related to STIs in German cities, with search queries focusing on specific diseases, especially chlamydia and gonorrhea. Furthermore, instead of regional peaks, national trends with no seasonal correlations were seen. The knowledge gained may be helpful for the planning of big educational campaigns as well as future awareness and prevention strategies. It may be advisable to intensify efforts to discuss STIs more publicly, to clarify responsibilities among STI-treating disciplines especially for management of men with STIs, and to link educational programs directly to broadcast news when public attention is already present.


Profiling of individuals based on inborn, acquired, and assigned characteristics is central for decision making in health care. In the era of omics and big smart data, it becomes urgent to differentiate between different data governance affordances for different profiling activities. Typically, diagnostic profiling is in the focus of researchers and physicians, and other types are regarded as undesired side-effects; for example, in the connection of health care insurance risk calculations. Profiling in a legal sense is addressed, for example, by the EU data protection law. It is defined in the General Data Protection Regulation as automated decision making. This term does not correspond fully with profiling in biomedical research and healthcare, and the impact on privacy has hardly ever been examined. But profiling is also an issue concerning the fundamental right of non-discrimination, whenever profiles are used in a way that has a discriminatory effect on individuals. Here, we will focus on genetic profiling, define related notions as legal and subject-matter definitions frequently differ, and discuss the ethical and legal challenges. In healthcare, potentials of big data receive more and more attention as the volume, variety, and velocity of healthcare data is increasing steadily. Big companies, for example Google, Apple and IBM are investing huge resources in this area in order to exploit their data assets. As data have an intrinsic value, for example, as resource of gaining knowledge about human needs and preferences, buying and selling them or using them for various purposes is tempting. Customizing product offers and pricing based on our habits, needs, and characteristics usually increases profits in various different areas, but might entail detrimental effects for the customer and unacceptable implications, such as ethnical and gender discrimination, for the society as a whole. This danger does not primarily stem from the central risk data protection law is addressing: the risk of unwarranted disclosure of person-related data. It is rather the risk of creating general profiles, which are later used in decision making, and might lead to unfair and discriminatory treatment. For such profile creation, re-identification is not needed, i.e., in most cases, anonymized and aggregated data are sufficient. An overall picture is given in “By definition, big data in healthcare refers to electronic health data sets so large and complex that they are difficult (or impossible) to manage with traditional software and/or hardware…”  does not prevent insurers from charging more for such expected conditions , experiences and empirical evidences. They are cognitive processes of identifying and choosing a belief or a course of action among several alternatives. By shifting toward empirical facts and analyses, it becomes urgent to reconsider the way the other components of decisions should be involved. Statistical results seem to show an inherent credibility and correctness due to the mathematical methods by which they are developed. People tend to accept profiles and decisions based on such results without seeking explanation or reasons for the conclusions based on them. Providing a reasoning for certain decisions beyond “facts” (which are themselves a construction), however, is a basic requirement for preventing unfair discrimination and allowing actionable transparency. It is therefore necessary to balance data-driven results with norms and thus keep control of their use in decision making. To this end, we suggest new approaches for addressing the threats of genetic profiling and also show the shortcomings of the current European legal framework, mainly GDPR .profiling can be summarized by following two descriptions  and analyzing their characteristics or behavior patterns in order to place them into a certain category or group, and/or make predictions or assessment about, for example, their ability to perform a task, interests, likely behavior.”In health care, physicians use profiling as a part of their professional duties. Another term that can be used is “risk stratification,” i.e., using certain patient characteristics for classifying different types of disease forming , and whole genome sequences. These markers are directly related to the DNA without any translation step in-between , which allows to focus on stable characteristics at the molecular level. STRs are highly relevant, because they are frequently used for genetic fingerprinting of individuals , genetic profiling can and in some cases must be achieved by automated decision making. Using methods like deep neural network are additionally related with a black-box character, making it difficult to achieve transparency regarding the mechanism for risk prediction. We will discuss implications of these difficulties in the next section.For making the discussion of potentials and problems of genetic profiling for individual as well as social profiling more concrete, we will use diabetes mellitus as a disease for which diagnosis and treatment can be tailored with the help of genetic profiles. “Diabetes mellitus is a chronic disease of major global health concern due to its increasing prevalence in both developing and developed countries, with a projection increase of 214% from the year 2000 to 2030” Leung, .In contrast to single-gene profiles for Mendelian disorders with relatively certain prediction of developing a disease, genetic profiling for diabetes mellitus type 2 (DMT2) only allow to generate disease risk information Haga, . Among tHow and when should predispositional screening for disease prediction be used?To whom and how should the risk information be communicated?thrifty gene theory proposed by Neel  was adopted in the USA to prohibit discrimination by health insurers or employers. Health insurers  are prohibited from adjusting premiums or contribution amounts, requesting or requiring an individual or a family member of an individual to undergo a genetic test, obtaining and using genetic test results in making a determination regarding payment, or requesting, requiring, or purchasing genetic information for underwriting purposes. The statute does not cover schools, mortgage lending, or housing. And it excludes other forms of insurance like life insurance, long-term care, and disability insurance. Therefore, the American Medical Association has pointed to the shortcomings at an early stage  profiles while harnessing their advantages for health research and healthcare?If society does not want to slow down developments in data science, solutions cannot rely on prohibitions of all kind applications, but has to focus on increased transparency as well as on ethical debates regarding good and bad purposes of profiling independently of economic impacts.For answering the question of how to prevent the use of personal genetic profiles derived from personal health records or research data bases for discrimination, it has first to be decided where, by whom, by which security technique, under which format and under which rules such profiles are stored. In order to guarantee as much freedom as possible, disclosing of information should mainly dependent on the free will of the data subject. However, health insurances, life insurances, etc., want to be able to customize their offers according to the information they can receive from their customers. If such information is available, it is difficult to prevent its usage. Most important, however, is the fact, that in many cases, such as ethnic or family membership, it is unrealistic to hide certain genetic characteristics. As the diabetes case clearly shows, it is not the personal genetic profile of a certain individual that is harmful for an individual's life opportunities, but the mere fact that he/she obviously belongs to a certain group. The “typical” genetic profile due to ethnic origin is sufficient to trigger assumptions about the health status. The same will become true for an increasing number of genetic group profiles connected to obvious characteristics. In contrast to other profiles based, for example, on the outer appearance, such genetic profiles are related to a broad range of aspects, which are not immediately visible.As AI algorithms can lead to socially unintended discrimination, a public debate on the transparency of the decision-making process and results of machine learning algorithms is necessary. It should be clear: Algorithms do not rule us but provide the result we need for decisions. The public debate has to determine how transparency with respect to the algorithms, underlying assumptions, and their results can be achieved. What we need, is a general right to get to know and assess the presumptions behind decisions affecting individuals. This is highly relevant, as it is possible to hide characteristics such as race or genetic disposition behind less suspect items that are highly correlated with them. The latter is all the more true regarding social profiling, which does not need personal data and can therefore undermine privacy of individuals that have kept their profiles secret.In conclusion, decisions concerning individuals should always be challengeable, especially when sensitive genetic information is involved. Regulations regarding genetic profiles cannot cover all possible uses and misuses, which means that the legal gap cannot be closed only by more detailed prohibitions. In addition to that, mechanisms of oversight should be established, allowing standardized and transparent procedures for deciding whether the use of genetic profiles is based on unjustified or discriminatory assumptions.MS and IS designed and structured the manuscript. MS and IS equally contributed to the section Introduction. MS wrote most of the section What is Genetic Profiling? IS wrote most of the section Legal Approaches and Gaps for Addressing Genetic Profiling. MS and IS equally contributed to the section Discussion and Conclusion.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Rhinopithecus roxellana) is an endangered primate endemic to China. The lack of standardized genetic markers limits its conservation works. In the present study, a total of 1,400,552 perfect STRs was identified in the reference genome of R. roxellana. By comparing it with the 12 resequencing genomes of four geographical populations, a total of 1,927 loci were identified as perfect tetranucleotides and shared among populations. We randomly selected 74 loci to design primer pairs. By using a total of 64 samples from the Chengdu Zoo captive population and the Pingwu wild population, a set of 14 novel STR loci were identified with good polymorphism, strong stability, high repeatability, low genotyping error rate that were suitable for non-invasive samples. These were used to establish a standardized marker system for golden snub-nosed monkeys. The genetic diversity analysis showed the average HO, HE, and PIC was 0.477, 0.549, and 0.485, respectively, in the Chengdu Zoo population; and 0.516, 0.473, and 0.406, respectively, in Pingwu wild population. Moreover, an individual identification method was established, which could effectively distinguish individuals with seven markers. The paternity tests were conducted on seven offspring with known mothers from two populations, and their fathers were determined with high confidence. A genotyping database for the captive population in the Chengdu Zoo (n = 25) and wild population in Pingwu country (n = 8) was acquired by using this marker system.Golden snub-nosed monkey ( Rhinopithecus roxellana) is an endangered Old World Monkey that is endemic to China, and it is currently under the National Protection level I2. Alongside the giant panda, the golden snub-nosed monkey is known as ‘China’s national treasure’ and is often cited as one icon of the national biodiversity conservation. These monkeys are threatened by large-scale forest shrinkage and ecological environment deterioration at present. The wild population is estimated at ~ 15–22 thousand in total, and now only occur in three isolate regions of temperate alpine forests: Sichuan-Gansu mountains (~ 66.7%), Qinling mountain (~ 26.6%), and Shennongjia mountain (~ 6.7%)2. Meanwhile, more than 452 captive individuals were kept in 44 institutions nationwide by the end of 20183. Although the international community and the Chinese government have made great efforts to protect this precious species, some urgent issues remain unresolved.Golden snub-nosed monkey  and simple sequence repeats (SSRs), are a well-known tool for genetic diversity analysis. Although STR loci analysis has been used to assess the genetic variability and population size for golden snub-nosed monkeys by some researchers, there are still some unresolved problems.8. For example, Pan (2005)4 analyzed the genetic diversity of three golden snub-nosed monkey populations using 14 microsatellite loci. Later, Chang (2012a)5 and Zhou (2018)6 used 16 loci and 12 loci to study the Shennongjia population, respectively. Most of these loci were different from those in Pan’s study, which made it difficult to compare and analyze among populations based on their findings and limited the formulation and implementation of conservation strategies. Furthermore, the lack of standardized genetic markers also makes it impossible to compare the genetic diversity within the same population of different periods. In this case, the two studies on the Shennongjia population seem to indicate that the genetic diversity of this population was the lowest among all golden snub-nosed monkey populations, but it was hard to say whether the diversity had increased or decreased after decades of conservation work.One problem is that different loci were applied to different populations, which makes it difficult to evaluate genetic diversity among populations. Most of the golden snub-nosed monkey loci in previous studies were screened from the loci of related primates, such as rhesus monkeys and humanSecondly, most of the loci in previously studies were not developed for non-invasive sampling, which can easily subject to mistyping during PCR amplification, especially in fecal samples or degraded tissue samples with low quality or concentration of template DNA. Unfortunately, the non-invasive fecal samples are much easier to obtain than blood and tissue samples, and it is a more practical sampling method in the wild. Therefore, there is still a lack of STR markers that can be widely applied to non-invasive samples.9. In addition, breeding programs in the zoo and between zoos can only rely on their incomplete pedigree records at present, lacking standardized genetic markers to support and validate these records. Breeding plans based on defective pedigree records are likely to lead to a series of problems, such as inbreeding, subspecies hybridization, loss of genetic diversity and population degradation3. In addition, the previous loci have not been tested for validity in captive populations with a very small population size. Therefore, it is necessary to develop a standardized marker system and to establish an accurate paternity test method and a clear genetic pedigree record for captive populations.Moreover, previous studies did not consider the needs of captive populations. In captive breeding, due to the factors such as unclear genetic background, very small founder population, irregular and incomplete genetic lineage records, inbreeding was very likelyThe traditional ways of STR development involve time-consuming, costly and labor-intensive approaches, such as magnetic beads enrichment and Random amplification of polymorphic DNA (RAPD). Fortunately, the availability of golden snub-nosed monkey high throughput sequencing genomes provide us with the opportunity for genome-wide mining STRs and discovery of polymorphic loci across geographic populations. This method is much cheaper, more effective and more successful than traditional methods. In this study, by genome-wide screening for STRs in the golden snub-nosed monkey and comparing it with 12 available resequencing genomes, we are committed to the development of tetranucleotide STR loci with high cross-population polymorphism, strong stability, good repeatability, low genotyping error rate and, most importantly, suitability for non-invasive samples. This standardized marker system in golden snub-nosed monkeys could be widely used in individual identification, pedigree validation, genetic diversity analysis and development of conservation strategies for both wild and small, captive populations.A total of 1,400,552 perfect STRs (ranging from mononucleotide to hexanucleotide) was identified in the golden snub-nosed monkey genomic data. By comparing them with the 12 resequencing genomes, a total of 864,838 shared STRs were obtained  and tested for polymorphism. Finally, 16 primer pairs were chosen that showed both with a good polymorphism in their loci and with excellent amplify ability on both fecal and blood/tissue DNA  while females can be identified by one single band (211 bp)  showed that the genetic diversity of the captive population was slightly higher than that of the wild population.In the end, only 14 loci were reserved in the standardized marker system. These 14 loci were used to analyze and compare the genetic diversity of captive and wild populations. The H10 to estimate the number of markers needed for individual identification , and all the 14 loci were matched. Meanwhile, no other candidate father was supported (Trio LOD range from 2.39 to − 9.06), their mismatch number of analyzed loci range from 1 to 3 Table .We also tried a few other loci combination for paternity testing, using all 16, 13 , 12  and 7  loci respectively. The results showed that the 14 loci combination seemed to be the best, its results were very similar to those of 16 loci combinations , reaching an astonishing rate 50%13. Therefore, the loci selected to establish the standard STR marker system should be stable enough to produce minimal genotyping error and sensitive enough to respond to non-invasive samples.One great challenge in the genetic research for endangered species is that it is challenging to get samples with high-quality DNA. Basically, tissue samples can only be obtained during post-mortem autopsy. Blood sampling is relatively easy in captive breeding, but involves a complex collection process and may cause health hazards, which result in issues of animal welfare and ethics, and is therefore used with caution. As for wild monkeys, it is impossible to collect enough blood/tissue samples needed for genetic research. Non-invasive samples, such as shed hair and feces, are a valid alternative. However, the DNA quality or concentration of non-invasive samples is usually not very good, which may increase the rate of genotyping errors such as allelic dropouts or false alleles in genetic research. The non-negligible error rate in many laboratories is usually range from 0.2% to 15% per locusIn previous studies of golden snub-nosed monkey, most of the STR markers were screened from the STRs of other primates. These markers lacked response tests on non-invasive samples, which resulted in large number of markers being discarded due to failure in fecal DNA amplification (apart from lack of polymorphism) after population replacement. In this study, the sensitivity tests of our novel markers had a 100% amplification success rate in all 52 non-invasive DNA samples. Repeatability tests conducted by comparing the genotypes of fecal DNA and blood/tissue DNA showed no difference. Although the sample size of these tests was relatively small, the results showed that the selected markers had good potential in stability and reliability. Moreover, the tests on the relationship between the exposure time of fecal samples and the stability of these novel markers indicated that these markers could be used in wild fecal samples with an exposure time of one week. From here we see that this novel STR marker system is suitable for non-invasive sampling.2, our markers were indeed enough.Based on the 14 novel markers, we established the genotype database of Chengdu Zoo golden snub-nosed monkeys. This database can be used to effectively identify individuals of golden snub-nosed monkeys, evaluate genetic lineage records and guide breeding. It was observed that the seven loci combination was highly suited for individual-level identification, with a PID value suggesting that 1 in 30,000 unrelated individuals will share the same genotype. Considering that the total number of individuals in this endangered monkey was far less than 30,00016. Even if the rate of typing error is low, mismatches are relatively common. According to Kalinowski et al.10, in a paternity test with 10 loci, if the rate of typing error is 1% there is a 26% chance that one or more of those single-locus genotypes is mistyped. In our study, 14 STRs were applied, which may potentially increased the genotyping error. In addition, in the two cases of mismatch, offspring only had fecal samples. The lower DNA quality and template concentration in non-invasive samples also could lead to an increase in PCR error rate. On the other hand, it is known that the length and polymorphism of microsatellite repeat fragments are positively correlated with its mutation rate17. The GSM47 showed the highest polymorphism in our study may have a higher probability of mutation than other loci, which might be another reason for the mismatches. Therefore, in order to avoid the mistake of excluding paternity caused by STR mutations and PCR error, the basis of excluding paternity in forensic identification can not rely on single locus19.In the paternity test, the results showed that the 14 loci combination was adequate for parentage analysis of both captured and wild golden snub-nosed monkeys. Although two record fathers showed mismatched loci with their offspring, such mismatches may be related to PCR errors or germline mutations. Many researchers believe 6–12 STR markers are enough for individual identification and parentage assignment, and too many markers may increase genotyping errors and overestimations of population sizes18. In recent years, a considerable number of laboratories and forensic institutions in China have adopted another consensus, that is, at least three mismatched loci are needed to exclude paternity20. Microsatellites have decades of forensic experience in human paternity testing. With the widespread use of paternity test kits, it has been found that the mutation rate of microsatellites are higher than previously thought20. When only one or two exclusion loci occur , the laboratory can add additional loci to adequately exclude the possibility of mutation at the site, or test all candidate fathers to determine whether there is a more matched father. We think that the latter consensus is stricter on the exclusion of paternity, so it may be more appropriate for adoption. In this study all candidate fathers were tested, and the result showed that the two recorded fathers were the highest match among all candidates, thus confirming that the two father's paternity could not be excluded.An internationally recommended consensus requires at least two mismatched loci between offspring and candidate to exclude paternityIn paternity tests with fewer than 14 loci, some candidate fathers achieved a higher level of Trio LOD and Trio Confidence than the recorded fathers  with their offspring cross-breeding in various ways over the past decades. On the other hand, samples from Pingwu wild population were only collected from individuals from two small groups. Because of habitat fragmentation, their gene exchange with other wild populations was limited resulting in relatively low genetic diversity compared to the captive population. These results suggest that the marker system can effectively analyze genetic diversity, compare genetic differences among populations, and can be used to monitor genetic changes within the population.21, considering the monkeys in the Chengdu Zoo were a small population and they came from a variety of geographic populations. And in captive population, which is far from the ideal biological population, the failure to meet HWE was usually not a reason to discard a locus22.In the Chengdu Zoo population, six loci  deviated from Hardy–Weinberg equilibrium (P < 0.05). This might cause by a Wahlund EffectIn summary, by genome-wide screening for STRs in reference genomic data and comparing it with the 12 resequencing genomes in golden snub-nosed monkey, a total of 14 novel polymorphic tetranucleotide marker were proved to be reliable and valid for non-invasion samples to establish a standardized marker system. A subset of seven STR loci was appropriate for individual identification of both Chengdu Zoo captive population and Pingwu wild monkeys. The full set of 14 STR loci was appropriate for paternity assignment and genetic diversity analysis. This marker system showed a remarkably high success rate and a low error rate in the application of fecal samples. The novel system obtained here will facilitate the genetic management for the captive populations, and provide feasible solutions for the long-term assessment of genetic diversity and the formulation of conservation strategies for wild populations.Thirty-four specimens were collected from Chengdu Zoo , which represented 25 individuals in total. Four individuals were sampled for both fecal and blood/tissue samples, which could be used to test the stability of the markers. All samples were carefully collected to avoid cross-contamination. They were separately stored in sterile bags or EDTA anticoagulation tubes and frozen at – 80 ℃. The pedigree records from Chengdu Zoo indicated that the genetic background of these monkeys is complex. The ancestors were captured from multiple sites of Gansu moutains, Sichuan Qionglai moutains, Sichuan Minshan moutains and Hubei Shennongjia moutains. All samples were used in identification tests and to verify the pedigree records.Another 30 fecal samples were collected from Pingwu country, Sichuan Province, which mainly came from a small wild family of 18 individuals and a nearby all-male band. These monkeys were attracted by human feeding in 2017, so their pedigree records were incomplete and some kinships needed confirmation. The fecal samples were used to determine the identity and paternity of these monkeys, as well as the genetic diversity of this population. Eight of the samples were acurrately assigned to known individuals, because they were collected immediately after individual defecation was observed. The rest, 22 samples, were collected randomly from multiple locations within a week without any background information. In order to avoid repeated sampling of the same individual, we tried not to take multiple samples in one place, and each sample was collected at a certain interval.23. Search mode was set to search for perfect STRs. The minimum repeat number from mono- to hexa-nucleotide were set to 12, 7, 5, 4, 4 and 4, respectively. The flank sequence was set to 100 bp. Other parameters were set to default. The repetitive units with circular permutations and on the complementary chains were treated as the same repetition. For example, the AGT stands for AGT, GTA, TAG, TCA, CAT and ATC.The assembled genome of golden snub-nosed monkey (NCBI accession: GCA_000769185.1) was analyzed by Krait24 was used to screen for polymorphic tetranucleotide in the 12 resequencing genomes25  and 0.5 ~ 1 μl template DNA (about 2 U). The amplification protocols were carried out as follows: initial denaturation 3 min at 95 ℃, 40 cycles , final elongation of 3 min at 72℃. PCR products were visualized on a 3% agarose gel and further capillary electrophoresis on ABI 3,100 genetic analyzer. Genotyping data were obtained by GeneMapper 4.0 .Genomic DNA was extracted using TIANamp Stool DNA Kit and TIANamp Genomic DNA Kit  for fecal samples and blood/tissue samples, respectively. The 20 μl PCR reaction system included 10 μl Mix , 8 μl dd Hhttps://www.premierbiosoft.com/). We compared the published STR sequences for the golden snub-nosed monkey in NCBI with the output sequences of our program to ensure that our STR sequences did not repeat any published sequences. The length of primers designed in the present study ranged from 18 to 22 bp, the annealing temperature was set to around 51℃, and the expected size of products ranged from 100 to 300 bp. We designed similar annealing temperatures for all the primers, so the amplification conditions of STR loci are basically the same. We did this to make the operation of the system easier to share and extend to other researchers and less professional staff.Polymorphic STRs were extracted from the program output and primer sets were designed according to their flanking regions by Primer Premier 6.0 (https://genome.ucsc.edu/cgi-bin/hgPcr) was used to predict the size of the product based on the genomic data (Oct. 2014 Rrox_v1/rhiRox1) and whether there was only a single PCR product. Then, 15 samples  were used to test the repeatable amplification by using 51 ℃ annealing temperature under standard PCR conditions. For primer pairs with inefficient or failed amplification, we tested whether adding more mix, template DNA or adjusting annealing temperature could increase the amplification rate. The results showed that doubling the DNA template and/or increasing 0.5 µl of PCR mix was usually enough to amplify the samples which failed in the first amplification.In-silico PCR (We synthesized 42 of the 69 primer pairs and used them to amplify target STRs in DNA of both blood/tissue (n = 8) and fecal (n = 7) samples. After amplification, 31 primer pairs showed a single band of the expected product with fluorescent signals on their forward primer 5′ terminal (FAM or HEX). These were tested for polymorphism by using all of 34 samples collected from Chengdu Zoo. If these primers in the tests, especially in fecal sample tests, showed that (1) the success rate was less than 70% (n = 3), (2) a lack of polymorphism (n = 2), (3) more than 30% of the samples were multiple peaks (n = 8), and (4) not an integer multiple of 4 (n = 2), they were excluded from subsequent trials. In the end, 16 primer pairs had polymorphism  in their loci and amplified well (100%) on both fecal and blood/tissue DNA.Cervus 3.0.7 was used to check for possible null alleles. All individuals of our samples were included in this test . F(Null) frequency of all 16 loci were calculated. In the absence of a null allele, the estimated frequency will be close to zero, and maybe slightly negative. If a locus showed a large positive frequency, it may imply that a null allele is present or an excess of homozygotes.Since the genome of the golden snub-nosed monkey was assembled only to scaffold and had not yet been annotated to the chromosome, it was not clear whether the 16 novel tetranucleotide STRs were on different chromosomes. However, we BLAST the sequences of 16 loci in GenBank and aligned them with homologous sequences of human and other primates in order to roughly analyze their chromosomal location. The results showed that GSM 31 and 32 were probably linked, due to their homologous sequences of human were both located on chromosome 17. We also used Genepop to test the linkage disequilibrium of these loci, and the results also showed GSM 31 and 32 were likely linked. Beyond that, no significant linkage disequilibrium between loci was found. Therefore, only one of the locus 31 and 32 should be included in the STR system.To make sure that the same allele calls would be made by different researchers and laboratories in the future, our genotyping was repeated and entrusted to two independent sequencing companies for genotyping. In our study, every PCR included a control sample . In genotyping analysis, this control sample was used to ensure standardized allele calling between machine runs. These steps were our efforts to avoid different genotyping data for the same locus due to machine differences.28 which had been used to identify the sex of primates successfully in the previous studies, all failed. Therefore, based on the genomic data, we designed a new primer pair target ZFX and ZFY gene to determine the sex of Golden snub-nosed monkey  the amplification success rate was less than 70%; (2) More than 30% of the samples showed multiple peaks in the genotyping results, and the stutter peaks appeared in more than two repeated tests.Four individuals were sampled for both fecal and blood/tissue samples. The results of genotyping in blood and feces of the same individual  were compared to evaluate the reliability and stability of STR markers. The markers would be excluded if the genotyping results of blood and fecal samples were inconsistent. In addition to test whether these STRs can be used to the fecal samples that were exposure to the wild environment, thirty fecal samples from the wild (1–7 days of wild exposure) were also used to test the amplification success rate and accuracy of these STRs.https://www.fieldgenetics.com) were used to analyze the Total HO, HE and PIC of this dataset. And then we tried three methods to arrange these markers, according to their HO, HE and PIC value from high to low respectively. The markers with the highest value were select one by one, and its PID and PIDsib values were calculated. When the accumulated PID and PIDsib reached less than 0.001 and 0.01 respectively, the minimum number of loci needed for individual recognition was obtained.Firstly, by using all 16 markers we identified 47 individuals in our 64 samples. Then the genotypes of the 47 individuals (25 from Chengdu Zoo and 22 from Pingwu) were used to establish a dataset. Cervus 3.0.7  were exact match. And they had the same allele on GSM25, but different allele on GSM75. If GSM25 is replaced by GSM75, the seven markers can also reach the threshold and discriminate individuals. Therefore, we ended up with seven markers that can effectively identify individual.After comparing these three methods, we found the best method was based on HIn addition, the novel STR markers were used to determine the paternity both in this captive and the wild populations. Cervus 3.0.7 were used to conduct offspring analysis. For each monkey in captivity, the genotype of the recorded father was compared with the genotypes of all potential sire candidates to verify the lineage record. In the wild population, all male samples, including the dominant male, were selected as candidate father to determine which one was the biological father of a 1-year old cub who lacked pedigree records.O), expected heterozygosity (HE), polymorphic information content (PIC), individual identification (PID and PIDsib) and paternity testing were calculated by Cervus 3.0.7 (https://www.fieldgenetics.com)10. Hardy–Weinberg equilibrium  were calculated by Genepop 4.2 (https://www.genepop.curtin.edu.au)29.We also analyzed the genetic diversity of golden snub-nosed monkey population both in captive and in wild. The observed heterozygosity . The ethical review of this study was approved by the ethics committee of the College of life sciences, Sichuan University.Supplementary file1 (DOCX 15 kb)Supplementary file2 (DOCX 12 kb)Supplementary file3 (XLSX 15 kb)Supplementary file4 (DOCX 55 kb)Supplementary file5 (DOCX 16 kb)Supplementary file6 (DOC 29 kb)


Understanding the genetic diversity present amongst crop genotypes is an efficient utilization of germplasm for genetic improvement. The present study was aimed at evaluating genetic diversity and population structure of 48 pigeonpea genotypes from four populations collected from diverse sources. The 48 pigeonpea entries were genotyped using 33 simple sequence repeat (SSR) markers that are polymorphic to assess molecular genetic diversity and genetic relatedness. The informative marker combinations revealed a total of 155 alleles at 33 loci, with an average of 4.78 alleles detected per marker with the mean polymorphic information content (PIC) value of 0.46. Population structure analysis using model based revealed that the germplasm was grouped into two subpopulations. The analysis of molecular variance (AMOVA) revealed that 53.3% of genetic variation existed within individuals. Relatively low population differentiation was recorded amongst the test populations indicated by the mean fixation index (Fst) value of 0.032. The Tanzanian pigeonpea germplasm collection was grouped into three major clusters. The clustering pattern revealed a lack of relationship between geographic origin and genetic diversity. This study provides a foundation for the selection of parental material for genetic improvement. Cajanus cajan [L.] Millsp) is an important legume crop widely cultivated in Africa and Asia in diverse environments [Leguminosae and sub-family Papilionoideae. Cajanus cajan is the only domesticated species among Cajanea family. The crop has the ability to produce an economic yield under low moisture condition making it an important crop in dry areas [Pigeonpea  in “Bt” cotton production [Pigeonpea is considered to be a valuable food and commercial crop with diverse uses. This crop improves soil physical properties and yield of associated intercropped crops while simultaneously yielding marketable grain. Their thick stems are mainly used as fuel food and roofing material ,6. Moreooduction . Furtheroduction . Pigeonpoduction .Genetic diversity analysis in pigeonpea is crucial for effective breeding and germplasm conservation. Previous studies examined the genetic diversity of the crop using morphological and agronomic traits ,12,13. AFusarium wilt and grain yield. The sample included the released pigeonpea varieties in Tanzania and most frequently used in breeding activities. The material used represent the collection from all major growing areas of pigeonpea in Tanzania. The detailed information about the material used in this study is given in The study material consisted of 48 pigeonpea genotypes representing farmers’ landraces, landraces from the National Plant Genetic Resources Centre (NPGRC)-Arusha, Tanzania, breeding lines collected from International Crops Research for Semi-Arid Tropics (ICRISAT)-Nairobi, Kenya and released cultivars obtained from the Tanzania Agricultural Research Institute (TARI)-Ilonga, Morogoro-Tanzania. The selection of the plant material used relied on farmers preference for plant growth habit, resistant to −1. For all samples, the DNA quality was determined by agarose gel electrophoresis (0.8% (w/v) stained with 5 µ/100 mL Gel® , while the quantity was determined by spectrophotometry . The DNA samples were analysed at ICRISAT-laboratory, Centre of Excellence in Genomics, India.The genomic DNA was extracted from fresh leaf material from 10- to 14 day-old-plants of each of the 48 pigeonpea entries and was ground to fine powder in liquid nitrogen, following the cetyl trimethyl ammonium bromide (CTAB) method as described by Mace et al. , with so2, 0.1 µM of respective forward and reverse primer and 40 ng of genomic DNA. The PCR amplification was carried out in a Bioer XP Thermal Cycler . The thermal cycling conditions were as follows: initial denaturation at 94 °C for 5 min, followed by 35 cycles of denaturation (94 °C) for 1 min, annealing (56–72 °C) for 1 min, primer extension (72 °C) for 1 min, followed by an extension at 72 °C for 20 min. The amplification products were analysed by electrophoresis on a 2.8% agarose gel, stained with ethidium bromide and photographed under short wavelength ultraviolet (UV) light in a gel documentation system. A 100 bp DNA ladder  was used as a size fragment standard.Out of 35 SSR markers tested, only 33 SSR markers were polymorphic and used for this study . The marThe allelic size was estimated visually for all 48 genotypes of pigeonpea. The band size of amplified products was determined by comparing with 100 bp DNA ladder . The SSR bands scored in pigeonpea genotypes was subjected to GenAlex version 6.5  to assesThe population structure of the 48 pigeonpea was established using the Bayesian clustering method in STRUCTURE version 2.3.4 . The lenThe sizes of amplified polymorphic DNA fragments (bands) ranged from 127 to 280 bp . GeneticIS) ranged from 0.03 to 0.93 with a mean of 0.39. Two loci (CcM0698 and CcM2379) showed an FIS value of 1 suggesting the alleles at these loci are fixed i.e., reached 100% homozygosity and, therefore were excluded from the analysis. However, six loci  showed a very low FIS values signifying that the alleles at these loci are heterozygotes.The PIC value of the SSR markers, which is a measure of allele diversity at a locus, ranged from 0.04 to 0.84 with an average of 0.44. The observed variations in PIC value in this study could be attributed to genotypic differences in the pigeonpea material used. Eight SSR loci  exhibited PIC values higher than 0.70 indicating their usefulness in discriminating genotypes. The observed heterozygosity values ranged from 0.0 to 0.69 with an average of 0.26. The gene diversity ranged from 0.04 to 0.85, with a mean of 0.45 . MarkersThe genetic parameters of the population studied based on source of collection were presented in Based on the ∆K value, the population structure analysis of the 48 pigeonpea genotypes grouped the population into two subpopulations . SimilarThe UPGMA cluster analysis based on genetic dissimilarity using the neighbour-joining method in DARwin 5.0 grouped the 48 pigeonpea genotypes into three genetic clusters . Three gIS was and 0.449 and FIT was 0.466. Determination of mean fixation index (FST) for the polymorphic loci across all accessions indicated that FST was 0.0318 which implies low genetic variation across genetic subgroups. The haploid Nm was very high (7.6) indicating a high gene exchange among populations  recorded in the current study was similar to PIC value (0.49) reported by Sousa et al. , lower tGenetic improvement of crops depends on the amount of genetic variation among the breeding material. Previous studies of genetic diversity in Brazilian pigeonpea genotypes by Sousa et al.  and MalaHe), which is a measure of genetic diversity observed, in the present study, was low compared to most previous studies [The average gene diversity  than among populations (3.2%). The percentage variation within groups was as high as 53.3% of the given populations. The current study is in agreement with the findings of previous publications on pigeonpea ,41, whicThe dendrogram based on SSR markers revealed three major clusters. This indicates the existence of a high degree of genetic diversity in the germplasm evaluated in this study. Therefore, these germplasms would serve as a valuable source for the selection of diverse parents useful for plant breeders to improve the existing commercial cultivars. In this study distinct clustering was not observed according to geographical basis or on the basis of maturity duration. This was also reported by Petchiammal et al. , who recThis study deduces the presence of a considerable level of genetic diversity among pigeonpea genotypes in Tanzania. This will serve as basic information by providing options to breeders to develop, through selection and breeding, new and more productive varieties that are adapted to changing environments. This germplasm could also be used for mapping population studies, producing a core collection, and facilitates the identification of useful traits. Additionally, with the enlarged sampling area, the existing germplasm will allow us to search for additional rare alleles.


Most indigenous pig resources are known to originate from China. Thus, establishing conservation priorities for these local breeds is very essential, especially in the case of limited conservation funds. Therefore, in this study, we analyzed 445 individuals belonging to six indigenous breeds from the Taihu Lake Region, using a total of 131,300 SNPs. In order to determine the long-term guidelines for the management of these breeds, we analyzed the level of diversity in the metapopulation following a partition of diversity within and between breed subpopulations, using both measures of genic and allelic diversity. From the study, we found that the middle Meishan (MMS) pig population contributes the most (22%) to the total gene diversity while the Jiaxing black (JX) pig population contributes the most (27%) to the gene diversity between subpopulations. Most importantly, when we consider one breed is removed from the meta-population, the first two breeds prioritized should be JX pig breed and Fengjing pig breed followed by small Meishan (SMS), Mizhu (MI), and Erhualian (EH) if we pay more attention to the gene diversity between subpopulations. However, if the priority focus is on the total gene diversity, then the first breed to be prioritized would be the Shawutou (SW) pig breed followed by JX, MI, EH, and Fengjing (FJ). Furthermore, we noted that if conservation priority is to be based on the allelic diversity between subpopulations, then the MI breed should be the most prioritized breed followed by SW, Erhuanlian, and MMS. Summarily, our data show that different breeds have different contributions to the gene and allelic diversity within subpopulations as well as between subpopulations. Our study provides a basis for setting conservation priorities for indigenous pig breeds with a focus on different priority criteria. Indigenous breeds are well adapted to their specific environmental conditions, and their interest in livestock is increasingly being recognized . HoweverThe Taihu pig breed, which originates from the Taihu Lake region, is regarded among the world’s most prolific breeds with many excellent characteristics such as desirable meat quality, high resistance to disease, and good adaptability to the local environment . They inA total of 445 unrelated pigs  from the seven Chinese indigenous populations in the Taihu Lake region were selected . Then, Dt-distributed stochastic neighbor embedding (t-SNE)  and  (t-SNE) . The eig (t-SNE) .S refers to the within-subpopulations genic diversity, and DG is the average Nei’s genetic distance between subpopulations. Furthermore, HS can be divided into two components: the genic diversity within individuals, and the genetic diversity between individuals.Total genic diversity We determined the contribution of every subpopulation to the total gene diversity, as well as its components by decomposing the two terms of the following expression for every subpopulation: ai is the expected number of different alleles taken at random in a sample of genes, and di,j is the average allelic distance of subpopulations i and j. The software Metapop2 v2.3  is reached, using a simulated annealing algorithm  and exhibited a certain degree of allelic differentiation. Another exception was the FJ breed, which contributed negatively to AT because of its low AS and positively to HT because of its high degree of genic differentiation. Of a note, among all the studied breeds, the MI subpopulation contributed the most to the total allelic diversity, leading to the largest reduction in diversity when removed (0.407%), especially due to its large contribution to AS (0.487%). Moreover, based on this priority, we found that the SW (0.332%), EH (0.319%), and MMS (0.301%) ranked next to MI, respectively. Further results showed that JX was still the most differentiated breed, with the highest contribution to the between-subpopulations allelic diversity component (0.586%), followed by FJ (0.543%), SMS (0.315%), and MMS (0.021%). Regarding allelic differentiation, it is worth mentioning that only the JX and MMS breeds retained private alleles, suggesting that gene flow has been more limited to and from these populations.Regarding allelic diversity, the contributions to total diversity generally ranked similarly between breeds as for genic diversity, with the notable exception of MMS, which ranked 4th among the breeds that contributed positively to allelic richness  and a private link (https://jbox.sjtu.edu.cn/l/XH2s6V).The data used and analyzed in the current study are available The animal study was reviewed and approved by Institutional Animal Care and Use Committee of Shanghai Jiao Tong University.YP and QW supported and supervised this study. QZ analyzed the data and wrote the manuscript. EL-C helped analyze the data and revised the manuscript. ZZ and PM gave some important suggestions. All authors read and approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Maintaining genetic diversity in dairy cattle breeds is essential to support good performance and avoid inbreeding depression. This diversity could be threatened, however, by the recent increase in the use of reproductive technologies and the limited number of bulls in dairy cattle breeds. This study aimed to investigate the effects of these practices by simulating 15 breeding schemes similar to those carried out in the main dairy cattle breeds in France. We found that intensive use of reproductive technologies resulted in improved genetic gain, but diminished genetic diversity. However, this detrimental effect could be mitigated by maintaining a sufficient number of bulls in the breeding scheme.In the management of dairy cattle breeds, two recent trends have arisen that pose potential threats to genetic diversity: the use of reproductive technologies (RT) and a reduction in the number of bulls in breeding schemes. The expected outcome of these changes, in terms of both genetic gain and genetic diversity, is not trivial to predict. Here, we simulated 15 breeding schemes similar to those carried out in large French dairy cattle breeds; breeding schemes differed with respect to their dimensions, the intensity of RT use, and the type of RT involved. We found that intensive use of RT resulted in improved genetic gain, but deteriorated genetic diversity. Specifically, a reduction in the interval between generations through the use of ovum pick-up and in vitro fertilization (OPU-IVF) resulted in a large increase in the inbreeding rate both per year and per generation, suggesting that OPU-IVF could have severe adverse effects on genetic diversity. To achieve a given level of genetic gain, the scenarios that best maintained genetic diversity were those with a higher number of sires/bulls and a medium intensity of RT use or those with a higher number of female donors to compensate for the increased intensity of RT. The degree of inbreeding and, more generally, the loss of genetic diversity in domestic animal populations have been the subject of particular attention since the first half of the last century . Low genOne of the main approaches to managing genetic diversity in a dairy cattle breed is through breeding schemes, particularly with respect to the number of animals considered at each of the selection steps ,8. One iIn dairy cattle breeds, breeding schemes are designed and implemented by breeding companies with the goal of producing elite bulls whose high-genetic-quality semen can be commercialized. The use of artificial insemination is widespread, with the result that genetic diversity in a breed is highly correlated with genetic diversity in breeding schemes . CurrentVARiabilité génétique des RUMinants et des Equidés, genetic variability in ruminants and equines, VARUME)  of In our simulations, intensification of RT use combined with a reduction in the number of sires and bulls had a detrimental impact on genetic diversity by increasing inbreeding rates. For a given genetic gain, the scenarios that best maintained genetic diversity were those with a medium intensity of RT use or those with a higher number of female donors to compensate for the increase in RT intensity.Our results were obtained from simulations of a breeding scheme that used random mating and that imposed constraints on the number of calves per bull and female donor that could become bulls or donors themselves. With this design, we might have overestimated genetic gains and inbreeding rates in comparison with breeding schemes that use avoidance mating  or optimInbreeding depression depends on both the inbreeding rate and the inbreeding load . In future studies, it would be interesting to identify the genomic regions carrying these variants and to incorporate this information into genomic evaluations. With this knowledge, genomic selection programs would be able to focus more on maintaining genetic diversity in the regions where it is truly important. Such a strategy could limit the impact of the loss of genetic diversity on the health and performance of dairy cattle breeds even with an intensification in the use of RT.Our simulations predicted that intensive use of reproductive technologies could lead to improved genetic gain, but this would be accompanied by a deterioration in genetic diversity. The larger genetic gain that we found in scenarios based on OPU-IVF compared to MOET appeared to be, in large part, the result of the significant reduction in the generation interval enabled by OPU-IVF. However, this shortened generation interval led to significant increases in the inbreeding rate, suggesting that using RT to drastically reduce the generation intervals between female donors could have severe detrimental effects on genetic diversity in dairy cattle breeds. In addition, reducing the number of sires of bulls and marketed bulls in the breeding scheme had a detrimental impact on both genetic gain and genetic diversity.These results led us to the conclusion that two of the major trends in dairy cattle breeding—the intensified use of RT and the cost-conscious reduction in the number of sires of bulls and marketed bulls used by breeding companies—pose serious risks to the genetic diversity of these breeds. In the context of genomic selection and according to the level of genetic gain breeding companies want to reach, avoiding OPU-IVF in favor of MOET, limiting the intensity of use of MOET while maintaining the number of sires and bulls are good practices to maintain genetic diversity. It is also possible to compensate (to a certain point) for an increase in the intensity of use of MOET by increasing the number of female donors and putting constraints on the number of bulls having the same mother, while still maintaining the number of sires and bulls.It is necessary to find solutions to the loss of genetic diversity, or, at a minimum, approaches that can mitigate the consequences of this loss . One approach that might be effective would involve managing genetic diversity at the genome level by locating the genetic load of deleterious mutations and focusing on the diversity of these regions in particular.