Argania spinosa L. populations were aggregated into 2 genetic groups. To detect outlier, baysecan software was used and 21 were detected  presenting posterior probability higher than 0.79. The current results can be explored in the design of management programs and to comprehend the adaptation mechanism of Argan tree.The Argania is an endemic genetic resource in Morocco holding an important ecological and socio-economical benefit. However, overgrazing and overharvesting lead to a serious downturn in the number of trees. To characterize genetic diversity within and among 24 populations, represented by 240 argan trees, four combinations of SRAP primers and eight combinations of REMAP primers were used. A total of 338 REMAP and 146 SRAP markers were amplified with a polymorphism of 100%. The average polymorphism information content value was 0.20 and 0.17 for SRAP and REMAP markers, respectively. The analysis of molecular variance showed that 26% of the genetic variation was partitioned among populations. The coefficient of gene differentiation was 0.2875 and gene flow was 1.2391. The average parameter diversity was: observed number of alleles (Na)=0.729, effective number of alleles (Ne)=1.131, Shannon’s information index (I)=1.143; Nei’s gene diversity (H)=0.093 and Percentage of Polymorphic Loci=35.68. The STRUCTURE and principal coordinate analysis revealed that the  Argania spinosa L.) is the unique representative of the Sapotaceae family in Morocco, it is an endemic species of the country where it occupies the second place after the holm oak. It is widely distributed in the southwestern region of Morocco with an area of more than 900,000 ha [The argan tree  and Retrotransposon-microsatellite amplified polymorphism (REMAP), based on the transposable elements, since they constitute a major component of plant genomes , 7. SRAPCollection of plant materials and genomic DNA extraction: 240 genotypes were selected from 24 parts of Morocco for the REMAP and SRAP analysis . Amplification was carried out in a Veriti 96-Well Thermal Cycler. The PCR reaction program consisted of initial denaturation at 94°C for 3 min, followed by 5 cycles of denaturation at 94°C for 1 min, annealing at 35 °C for 1 min and extension at 72°C for 1 min, followed by 35 cycles of denaturation at 94°C for 1 min, annealing at 50°C for 1 min and extension at 72°C for 1 min and a final extension at 72°C for 10 min. nd Beiki . The reaA total of 20 SRAP primer combinations were tested of which 4 primer combinations showed reproducible and distinct amplification of the loci were selected. PCR products were electrophoresed on 2% agarose gel (UltraPure-Invitrogen) for 2-3 h at 90 volts, stained with ethidium bromide and photographed under UV light using EnduroTM GDS . The SRAP images were transferred to the Gelcompar II software. Only the clear fragments in the size range of 50 bp to 2050 bp bases were marked as present. The binary data was exported and verified for further statistical analyses.Molecular analysis of REMAP: Eight REMAP primer combinations were selected for further analysis. The REMAP-PCR was performed in 25 µl reaction mixtures containing: 8ng/µl of DNA, 2 µM of each primer, and 13 µl MyTaq HS Mix (BIOLINE). PCR cycles started with an initial denaturation step at 94 °C for 1 min followed by 35 cycles of denaturation at 95 °C for 15s, annealing at the specific annealing temperature for 15 s and extension at 72 °C for 10 min. Gel electrophoresis and notation bands were performed as described for the SRAP. The fragments in the size range of 50 bp to 1500 bp bases were marked as present.Data analysis: Genotypic data was used to evaluate the efficacy of each primer used in each marker system. The polymorphic information content (PIC) was determined according to Roldán-Ruiz et al., [A. spinosa L.  et al., , the mar et al., , while t et al.,  based onGenetic diversity and population structure analyses: The combined binary data matrix of markers SRAP and REMAP was used to estimate genetic differentiation (Gst) and gene flow (Nm) using POPGENE v.1.32 [E v.1.32 . The genE v.1.32 . The samThe population structure was carried out based on the REMAP and SRAP genotypes using the Bayesian clustering model implanted in STRUCTURE software version 2.3 . The numThe candidate loci in the selection was identified using a Bayesian approach based on Fst described by Beaumont and Balding  implemenTo reveal the genetic diversity and outlier markers for 240 individuals of argan tree two markers (SRAP and REMAP) were used in this study. Four SRAP out of 20 primers and 8 REMAP gave polymorphism and were selected for data analysis. Four selected SRAP markers amplified a total of 147 amplicons ranged from maximum 45 (ME-1/EM-4) to minimum 32 (ME-2/EM-4) with an average of 36.75 bands displaying an overall polymorphism of a 100%. The polymorphism information content (PIC) showed an average of 0.20, the highest PIC was 0.21 showed by ME-2/EM-4 and ME-4/EM-4. The mean of resolving power (Rp) and markers index (MI) was 10.74 and 7.33 respectively while the highest value Rp (12.51) was generated by ME-2/EM-6 and by ME-1/EM-4 for MI (11.53). The eight REMAP primer combinations also showed a high polymorphism (100%) amplifying 338 polymorphic bands with an average of 42.25. The REMAP primer combinations IRAP3/ISSR2 and IRAP1/ISSR2 represent the lowest (34) and the highest (52) values, respectively, of the labeled alleles. The PIC of the REMAP markers varied from 0.20 for the combination of primers IRAP3/ISSR2 and IRAP2/ISSR2 to 0.14 for the primer combination IRAP4/ISSR1. The highest value of the resolving power (10.20) and the marker index (8.30) were obtained with primer combination IRAP1/ISSR2. A summary of the number of bands, %P, PIC, Rp and MI reproduced by the 4 SRAP and the 8 REMAP is shown in The average number of alleles observed (Na), effective number of alleles (Ne), Shannon's information index (I) and Nei's genetic diversity (H) in the argan tree populations were 0.729, 1.131, 0.143 and 0.088, respectively. The highest values of diversity parameters were observed in Mramer population  . The resTo visualize the relationships inter populations and elucidate the genetic structure of 24 populations of argan tree analysis PCOA and STRUCTURE were used. The three coordinates of PCoA analysis displayed 51.49 % of total variation. The first axis explained 10.95 % of the variance, while the second and the third ones displayed 18.48% and 22.51% of the variance respectively .A bayesian analysis was performed with K value (possible cluster number) ranging from 1 to 15. The second order statistics (ΔK) developed by Evanno et al.,  showed aThe efficiency of genetic diversity analysis depends largely on the polymorphism detected by molecular markers. In this study, SRAP and REMAP markers were used to assess genetic diversity among 240 argan genotypes representing 24 natural ecosystems. These markers are highly polymorphic due to their abundance in plants genomes and their dynamic nature , 7. TheiDespite the fact that the mean number of polymorphic bands amplified by REMAP was higher to that observed using the SRAP, the two markers have revealed a high level of polymorphism (100%). In addition, evaluation of informativeness and discriminatory power of the two marker systems by calculating the PIC, Rp and MI has shown higher mean values for SRAP compared to REMAP. The result found in this study is comparable to other studies suggesting that SRAP is the most efficient technique to reveal informative bands , 39. However, the combined use of different approaches could give more reliable information about genetic diversity , 41. In Consequently, the combined data will enable good genome coverage. Thus, the results of the two molecular techniques were combined and the data of 484 loci was obtained. Based on these data, the analyses of the molecular variance (AMOVA) was used to evaluate the genetic variability in different populations and revealed that most of the variance was attributed to the divergence within populations. This has been confirmed by the coefficient of genetic differentiation (Gst = 0.2875). These results are consistent with those found in other research studies focusing on genetic diversity of argan tree using IRAP-ISSR and AFLP markers , 18 and The parameters of genetic diversity were also calculated from the combined data of the two markers and the highest values were found by Mramer population. This population should have priority for conservation. In general, the revealed genetic diversity was higher than the values found in endangered or endemic forest species. However, the values found in this study were higher than those found by Pakhrou et al.,  using coThe combined data has been also the subject to detect outlier. Although retrotransposon-based molecular markers are assumed to be neutral markers. These markers generate a good number of polymorphic loci, which also can match gene encoding specific proteins. Recently, many dominants markers have been used to detect outlier such as SRAP and ISSR -50. In tArgania spinosa L. using REMAP and SRAP markers. A total of 240 tree of argan trees were collected from 24 regions representing its natural distribution. The results found in the present study indicate that high genetic differentiation was found mainly within population and showed a clear genetic structure which grouped the 24 populations into two genetic groups. this study demonstrated that SRAP and REMAP markers provide appropriate information for genetic structure of argan tree and could be used as an efficient tool for the detection the molecular relationships of trees. The data can be explored to study adaptation mechanisms of argan tree.The study of genetic diversity is one of the crucial and essential steps for effective conservation and preservation of argan forest. This is the first report of genetic diversity study of


Rattus norvegicus) population which invaded Xinjiang Province, China in the late 1970s.Invasive species bring a serious effect on local biodiversity, ecosystems, and even human health and safety. Although the genetic signatures of historical range expansions have been explored in an array of species, the genetic consequences of contemporary range expansions have received little attention, especially in mammal species. In this study, we used whole-genome sequencing to explore the rapid genetic change and introduction history of a newly invasive brown rat . Demographic analysis indicated that a severe bottleneck occurred in XJ population after the split off from the source population, and the divergence of XJ population might have started before the invasion of XJ. Moreover, we detected 42 protein-coding genes with allele frequency shifts throughout the genome for XJ rats and they were mainly associated with lipid metabolism and immunity, which could be seen as a prelude to future selection analyses in the novel environment of XJ.This study presents the first genomic evidence on genetic differentiation which developed rapidly, and deepens the understanding of invasion history and evolutionary processes of this newly introduced rat population. This would add to our understanding of how invasive species become established and aid strategies aimed at the management of this notorious pest that have spread around the world with humans.The online version contains supplementary material available at 10.1186/s12983-021-00387-z. Invasive species are not only a major threat for native biodiversity (such as species decline or extinction) and ecosystems , 2, but Rattus norvegicus) is one of the most successful mammalian invaders due to its remarkable migration and adaptation abilities [The brown rat , and phylogenetic assessments using whole-genome SNPs Fig. .Fig. 2PClustering analyses by ADMIXTURE showed that brown rats were separated into XJ and non-XJ populations when the number of presumed ancestral populations (K) was set to 2 which is the best supported number of clusters  models in δaδi . Divergeion Fig. a. We furion Fig. b, providFST scan to identify genes with allele-frequency shifts in XJ rats, as a prelude to future selection analyses in the novel environment of XJ. We identified 42 regions with high Z (FST) between XJ and other native rats  , 32–34. With the low nucleotide diversity (π), the effective population of XJ might undergo a more recent reduction than other native ones . This reR. norvegicus was differentiated into clades  corresponding mostly to geographic locations in China. Tree topology inferred from TreeMix showed that the introduced XJ population was closely related to the native NW population, indicating that the introduced rats were derived from NW, a geographic region neighboring to XJ. In this study, our sampling range covered main distribution areas of all the four subspecies of brown rats in China [Previous studies revealed that geography and environmental heterogeneity shaped genetic structure of brown rats , 54. We in China , 23. Tibin China , 23. Altin China , most ofin China . Given tFST outlier regions and they were mainly associated with lipid metabolism and immunity. One unique climatic characteristics of XJ is the dramatic diurnal and seasonal temperature differences [Gasterosteus aculeatus) [Ostrea lurida) [In a population with such a recent bottleneck and expansion, disentangling positive selection from neutral forces is challenging. However, we identified genes throughout the genome with significant allele frequency shifts in XJ rats, as a prelude to future selection analyses in the novel environment of XJ; A total of 42 genes were detected in ferences . The varferences , consequuleatus)  or the O lurida) , indicat lurida)  recentlyThis work highlights that rapid genetic change can occur after such a short period of invasion in brown rats, and the successful invasion could come from a small size of founder population. Geography and environmental heterogeneity shaped genetic structure of brown rats, and the adjacent NW population was the source of XJ population. Invasive species can rapidly adapt to the changed conditions by means of genetic changes through the process of evolution , 59, 60.A total of 50 adult brown rats were sampled across China including Xinjiang and other 14 provinces, which cover the main distribution area of brown rats in China , 23  was used to remove PCR duplicates. Reads mapped to two or more locations were filtered out.Whole-genomic DNA of 38 individuals was extracted from small pieces of tail tissue using a TailGen DNA extraction kit . The quality and integrity of the extracted DNA was checked by measuring the A260/A280 ratio using a NanoDrop ND-1000 spectrophotometer  and by agarose gel electrophoresis. Library preparation, Illumina sequencing, read alignments, and variant calling were performed by Annoroad Gene Technology (Beijing) Co. Ltd. For each individual, 100 ng genomic DNA was used to construct PCR-based libraries with a 350 base pair (bp) insertion size and sequenced on an Illumina HiSeq X Ten instrument with 150 bp paired-end reads. Our previously generated 12 whole genome sequences of wild-caught brown rat individuals  were rea RGSC5.0  using BW RGSC5.0 . SAMtool RGSC5.0  was perfThe Genome Analysis Toolkit (GATK)  HaplotypR. rattus [We used ADMIXTURE v1.3.0  to inves. rattus  was usedFST (−weir-fst) and π (−site-pi) with a 100 kb sliding window, respectively. Linkage disequilibrium (LD) decay was calculated with PopLDdecay [Pairwise genetic differentiation and nucleotide diversity among rat populations were calculated using VCFtools v0.1.16  by meanspLDdecay  with theaδi to analyze two-dimensional joint site frequency spectra (2D-JSFS) [− 9 [To investigate alternative divergence scenarios for XJ population, we used the diffusion approximation method of δ2D-JSFS) . We used2D-JSFS)  to condu2D-JSFS) . For eac2D-JSFS)  and Choi2D-JSFS)  to conveFS) [− 9 , 32.Population tree topology was estimated using the maximum likelihood method implemented in TreeMix . TreeMixFST (XJ/others) values for each window using VCFtools v0.1.16 , with a window size of 100 kb and a step size of 50 kb. Next, we Z-transformed FST values and then identified regions with Z (FST) that were greater than 5 standard deviations from the mean [P-value was corrected using the Benjamini-Hochberg false discovery rate (FDR).We estimated the the mean , 76, 77.the mean , where tAdditional file 1: Table S1. Sample information and sequencing statistics. Table S2. Cross-validation errors for different K values. Table S3. Best replicate of each of the optimized demographic models using ∂a∂i. Table S4. 42 genes in outlier regions between XJ and other native populations. Table S5. Functional enrichment of genes with allele frequency shifts throughout the genome for XJ rats.Additional file 2: Figure S1. Tree topology inferred from TreeMix with m = 1 (a) and m = 2 (b). Group IDs correspond to those in Fig. Figure S2. Detection of genetic mixture across all subgroups. Significance of 3 Population Test (Z) represents whether the corresponding subgroup (on Y axis) is of mixed ancestry of other subgroups. Each dot indicates the Z score of a test between the target subgroup and every pair of other subgroups. Positive value suggests a result of unadmixed. All the groups were showed with only positive values, suggesting a relatively unadmixed relationship to other subgroups. Group IDs correspond to those in Fig.


Many studies detect associations between parent behaviour and child symptoms of anxiety and depression. Despite knowledge that anxiety and depression are influenced by a complex interplay of genetic and environmental risk factors, most studies do not account for shared familial genetic risk. Quantitative genetic designs provide a means of controlling for shared genetics, but rely on observed putative exposure variables, and require data from highly specific family structures.The intergenerational genomic method, Relatedness Disequilibrium Regression (RDR), indexes environmental effects of parents on child traits using measured genotypes. RDR estimates how much the parent genome influences the child indirectly via the environment, over and above effects of genetic factors acting directly in the child. This ‘genetic nurture’ effect is agnostic to parent phenotype and captures unmeasured heritable parent behaviours. We applied RDR in a sample of 11,598 parent-offspring trios from the Norwegian Mother, Father and Child Cohort Study (MoBa) to estimate parental genetic nurture separately from direct child genetic effects on anxiety and depression symptoms at age 8. We tested for mediation of genetic nurture via maternal anxiety and depression symptoms. Results were compared to a complementary non-genomic pedigree model.Parental genetic nurture explained 14% of the variance in depression symptoms at age 8. Subsequent analyses suggested that maternal anxiety and depression partially mediated this effect. The genetic nurture effect was mirrored by the finding of family environmental influence in our pedigree model. In contrast, variance in anxiety symptoms was not significantly influenced by common genetic variation in children or parents, despite a moderate pedigree heritability.Genomic methods like RDR represent new opportunities for genetically sensitive family research on complex human traits, which until now has been largely confined to adoption, twin and other pedigree designs. Our results are relevant to debates about the role of parents in the development of anxiety and depression in children, and possibly where to intervene to reduce problems. Estimating how much parental behaviour influences children’s symptoms of anxiety and depression is important for understanding causes and designing interventions, but this is challenging. It cannot be assumed that associations between parental factors, such as control and hostility, and child outcomes, such as anxiety and depression –3, repreTwin and pedigree studies help to separate genetic and environmental influences, and results suggest that environmental effects of parents on child traits, including anxiety and depression, are weak . SpecifiAdoption and children of twins (CoT) designs provide stronger tests for environmental effects of parents on children than twin studies do, since they combine data on parents and children to correct for shared genetics. Intergenerational genetically sensitive research on child anxiety is scarce, but two studies suggest that parent-child associations for anxiety remain after controlling for genetic relatedness , 12. TheWhile adoption- and CoT-based parenting studies are valuable, their utility is limited in three ways. First, they focus on how specific measured parent phenotypes relate to child outcomes. This is useful for identifying or disqualifying specific causes. For instance, maternal depression after but not during pregnancy influences offspring emotional problems above genetic confounds , 21. HowNovel intergenerational genomic designs present opportunities to address these limitations and extend insights from twin and adoption research. The Relatedness Disequilibrium Regression (RDR) method was introduced as a technique for estimating genetic influence without bias from the family environment . A less Here, we apply RDR to 11,598 parent-offspring trios in the Norwegian Mother Father and Child Cohort Study (MoBa) to index environmental effects of parents on children’s anxiety and depression symptoms using the parental genome. Alongside parental genetic nurture, RDR estimates direct child genetic effects and the covariance between direct and nurturing effects. We use available maternal trait measures to test whether genetic nurture is mediated by self-reported maternal depression and anxiety. Additionally, we directly compare RDR results against traditional pedigree estimates, using 27,010 pairs of relatives  from the child generation of MoBa.The Norwegian Mother, Father and Child Cohort Study (MoBa ) is a prRDR and pedigree analyses required slightly different subsamples of MoBa families. For RDR, we used genotyped trios with available child anxiety and depression data. Siblings in the child generation were removed so that trios were independent families. For pedigree analyses, we retained all available cousins, siblings, half-siblings and twins in the child generation with anxiety and depression data, without requiring the presence of genotype data. Since only a subset of the families in MoBa was genotyped, all individuals included in genomic analyses were also within the sample used for pedigree analyses.Our two outcome variables are well-validated and reliable quantitative measures of childhood anxiety and depression symptoms at age 8. Anxiety was measured using the 5-item version of the Screen for Child Anxiety Related Disorders (SCARED) . DepressTo test whether measured parent anxiety and depression symptoms explained any genetic nurture effects, we used mother-rated Hopkins Symptoms Checklist (SCL-8) . The SCLP value < 1 × 10–6. Population stratification was assessed, using the HapMap phase 3 release 3 as a reference, by principal component analysis using EIGENSTRAT version 6.1.4. Visual inspection identified a homogenous population and individuals of non-European ancestries were removed based on principal component analysis of markers overlapping with available HapMap markers. The parent and offspring datasets were then merged into one dataset per genotyping batch, keeping only the SNPs that passed quality control in both datasets. Phasing was conducted using Shapeit 2 release 837 and the duoHMM approach was used to account for the pedigree structure. Imputation was conducted using the Haplotype reference consortium (HRC) release 1–1 as the genetic reference panel. The Sanger Imputation Server was used to perform the imputation with the Positional Burrows-Wheeler Transform (PBWT). The phasing and imputation were conducted separately for each genotyping batch. Additional file https://github.com/folkehelseinstituttet/mobagen.The current MoBa genomic dataset comprises imputed genetic data for 98,110 individuals , derived from nine batches of participants, who make up four study cohorts. Within each batch, parent and offspring genetic data were quality controlled separately. Quality control exclusion criteria for individuals were genotyping call rate < 95% or autosomal heterozygosity > 4 standard deviations from the sample mean. Quality control exclusion criteria for SNPs (single nucleotide polymorphisms) were ambiguous (A/T and C/G), genotyping call rate < 98%, minor allele frequency < 1%, or Hardy-Weinberg equilibrium p > 1 × 10–6, non-multiallelic, and non-duplicated.We conducted post-imputation quality control, selecting SNPs meeting the following criteria: high imputation confidence scores (INFO > 0.8 on average across batches), minor allele frequency > 0.05, Hardy-Weinberg equilibrium r2 threshold of 0.5 .Before calculating relatedness matrices for RDR, we removed individuals who were not part of a complete genotyped trio, restricted to one child per family so that pairs of focal individuals did not share a home environment and pruned down to 451,442 variants in approximate linkage equilibrium using an After data management, a final sample of 25,828 genotyped parent-child trios was identified. Almost 11,600 of these trios also had child anxiety and depression symptom data.The RDR method  allows tdirect effect of children’s own genetic variation on their trait. This is independent of the effect of being reared by biological parents. Importantly, a direct genetic effect is only direct in the sense that it does not stem from another individual’s genotype. Notably, mechanisms by which individuals evoke and select environments based on their genotype are essential in how genes lead to phenotypes [There are two versions of RDR: one uses identity-by-descent (IBD) relatedness, which distinguishes parts of the genome that are inherited from common ancestors, and the other uses common SNP-based relatedness. We used the SNP version since it has similar properties to the IBD version but has greater statistical power . Rather enotypes , and theindirect genetic effect, where parents’ genetics affect child traits by influencing parent behaviours and the rearing environment they provide. Notably, it is assumed that genetic nurture effects are from parents (not siblings) and that mating in the population is random. To the extent that these assumptions do not hold, the genetic nurture variance will be biased. Non-random mating would magnify the genetic nurture variance because it induces correlations between causal alleles across the genome, most importantly between transmitted and non-transmitted parts of the parental genomes [The second variance component estimates the effect of parent genetics on the child trait, controlling for child genetic effects: ‘genetic nurture’. Any parent genetic effect over and above child-driven direct effects must be an  genomes .The third component captures variance in the offspring phenotype attributable to covariance between the direct and nurturing genetic effects. This somewhat abstract variance component is easier to understand when considering the conditions for the estimate to be zero. Specifically, the direct-nurturing genetic covariance would not explain any phenotypic variation if only one generation contributes genetic effects to the child trait, or if different SNPs contribute to child and parent genetic influences, such that loci have only either direct or indirect effects. Covariance between direct and nurturing genetic effects can be thought of as a ‘passive gene-environment correlation’. This refers to a magnification of the environmental effect of genetically influenced parent behaviour, which happens because children passively inherit and are directly influenced by that same genetic material , and measurement error.In practice, the variance components are estimated by regressing phenotypic resemblance on three genomic relatedness matrices simultaneously. The first is similar to the matrix used in standard GREML: the genome-wide genetic relatedness of the children in the sample. The second and third represent the genetic relatedness of the parents and the genetic covariance between children and parents.both parents. We calculated parental genotypes by summing the unnormalised maternal and paternal genotype matrices. We then standardised parental genotypes to have a mean zero and variance two. In an outbred random-mating population, the variance for the parental genotypes is twice that of the offspring genotype as it is the sum of maternal and paternal genotypes [Notably, the genotypes of mothers and fathers are combined to allow estimation of the effect of enotypes . Notablyenotypes , which dAll RDR analyses included 10 ancestry principal components and genotyping batch, both derived from the child generation, as covariates. Analyses were performed in the GCTA software. We used the --reml-no-constrain flag to allow components to take negative as well as positive values, given the theoretical and empirical evidence for negative covariance between direct and indirect genetic effects on complex traits. This can happen if a proportion of parental genetic variants associated with lower child trait scores are associated with higher child trait scores when present in the child genome. For example, studies have identified loci exert opposing maternal and fetal effects on human birth weight , 37.To test whether any genetic nurture effect was partially explained by parent anxiety and depression symptoms, we re-ran the RDR models adding a measure of stable maternal anxiety and depression symptoms as a covariate. As mentioned above, this longitudinally-derived measure is preferable to time-specific measures as it captures a more reliable core trait that children are consistently exposed to. In addition, the measure maximises sample size and minimises bias in maternal reporting due to contemporaneous collection of maternal self- and child-report. We also tested the individual time-specific maternal measures as covariates.To test whether any of the variance components were biased because some children were genotyped in a different batch to their parents, we re-ran the RDR models using only individuals who were genotyped as a complete trio .To test the sensitivity of the genetic nurture estimate to a more stringent exclusion of relatives, we restricted all GRMs to relatedness < 0.1 and re-ran the RDR models.Finally, to estimate standard SNP heritability, we ran single component GREML models using unrelated child genotypes. This is equivalent to running RDR with the genetic nurture and direct-nurturing genetic covariance components set to zero.To compare RDR results to a traditional quantitative genetic (non-genomic) design, we implemented a univariate pedigree model . As in tbeyond parent behaviours, and effects of any correlation between the shared environment and genetic components (passive gene-environment correlation). Third, whereas pedigree and twin models assume passive gene-environment correlation is absent , RDR can directly estimate it as the covariance between genetic and environmental (genetic nurturing) effects.Before comparing RDR and pedigree results, it is essential to note the differences between variance components derived from the models. First, with respect to child genetic effects, RDR only captures additive effects tagged by measured common variants, but the pedigree genetic component also includes non-additive genetic effects, and the effects of rare variants not tagged by the common variants included on the SNP array. Second, regarding family environmental effects, the shared environment component in the pedigree model is broader than the genetic nurture estimate using RDR. The shared environment captures at least three sources of variance that genetic nurture does not parent behaviours not tagged by common SNPs, shared environments Additional file Genome-wide relatedness matrices were constructed using python, and RDR models were run using GCTA . PedigreResults from our RDR analyses using genomic data to disentangle child and parent genetic effects on anxiety and depression symptoms at age 8 are shown in Fig. See Additional file Our results were robust to any effects of children being genotyped in a different batch to their parents. Variance components were unchanged after restricting the sample to trios who were genotyped together. Our results were also robust to more stringent exclusion of relatives: the genetic nurture variance for child depression remained 14% (se = 0.07) when all GRMs were computed using a relatedness cut-off of 0.1  resulted in SNP heritabilities of 4% (se = 0.05) and 10% (se = 0.05) for anxiety and depression, respectively. These results are equivalent to the following calculation based on the RDR estimates: direct genetic effect + 1/2 genetic nurturing effect + covariance effect . The genOur key finding of genetic nurture for child depression but not anxiety was supported by our pedigree analysis Fig. . Shared We used genomic data from parent-offspring trios to estimate indirect parent genetic effects (genetic nurture) separately from direct child genetic effects on anxiety and depression symptoms at age 8. Results from the RDR model suggested that depressive symptoms were influenced by both genetic nurture and direct genetic effects. Genetic nurture is an environmentally mediated effect of genetic origin, indexing behaviours of both parents that are influenced by their common genetic variation and that influence child depression, over and above direct child genetic effects. We found that the genetic nurture effect was partially mediated via an observed measure of maternal anxiety and depression, which explained 64% of the original genetic nurture effect ). In contrast, individual differences in anxiety symptoms were not significantly influenced by parental genetic nurture, and direct effects of common genetic variants explained just 5% (se = 0.07) of the phenotypic variance.Our genomic evidence of an environmental effect of parents on child depression, but not anxiety, was supported by pedigree-based evidence for shared environmental influence on depression, but not anxiety. This aligns well with findings from epidemiological and twin studies. Unlike anxiety, depressive symptoms are uncommon in pre-pubertal children, but when they do occur, are typically a response to psychosocial risks, such as perinatal issues, abuse and bullying , 41. TwiOur analysis adjusting for a longitudinal measure of stable maternal anxiety and depression suggested that these symptoms partially mediate the genetic nurture effect on childhood depression. This is compatible with adoption- and CoT-based evidence for phenotypic effects of maternal depression . This enreducing child depression risk) when present in the parents. On the face of it, this result is difficult to explain and we suggest that it should be interpreted with caution. Notably, negative covariance components have been reported in previous RDR analyses of multiple phenotypes including creatinine levels and age of the first child in men [This negative component suggests that genetic variation that is associated with higher depression risk when present in children, has an opposing effect (d in men , and in d in men . Negativd in men . One hypFor child anxiety, the pedigree heritability estimate was moderate, despite the small genomic signal from RDR. This is compatible with findings from other samples . HoweverWe acknowledge potential sources of bias affecting the RDR results. First, although supportive of the notion of parental influence on child depressive symptoms, the genetic nurture estimate may also capture residual population stratification, assortative mating and indirect genetic effects from siblings . PopulatSecond, the genetic nurture effect, and the mediation effect, could be partly generated by the use of maternal ratings of child outcomes. Maternal reports of child depression symptoms may reflect their own anxiety and depression symptoms. As a result, an apparent parental genetic nurture effect may in fact be a direct genetic effect on parents’ own traits. This phenomenon has been evidenced in developmental twin studies, in which rater bias may cause shared environmental variance to be overestimated . HoweverThird, selective participation, genotyping and attrition might have reduced coverage of families experiencing more severe anxiety and depression symptoms. Depression-linked attrition has been demonstrated in the Norwegian Twin Panel . StrongeFuture studies could seek to identify phenotypes other than maternal anxiety and depression symptoms that explain why the parent genome independently influences child depression. To aid the discovery of specific mechanisms, it will be important to jointly estimate maternal and paternal genetic nurture , the relThe RDR method could be broadened to address multivariate and longitudinal questions, as has been done with twin designs . For exaOur genomic approach strengthens the evidence base regarding parent effects on child emotional development, by directly accounting for shared genetics, and by indexing the child’s environment using the parental genome. Quantifying the contribution of parents is crucial for the understanding of how anxiety and depression develop in childhood, and potentially how to target modifiable causes. Our results are supportive of parent effects on depressive symptoms at age 8. The genetic nurture effect on depressive symptoms was partially mediated by maternal anxiety and depression. Though the effect size is modest, this suggests that efforts to alleviate maternal anxiety and depression could help to prevent child depression.Additional file 1 : Table S1. MoBa genotyping and imputation information. Table S2. Full RDR results. Figure S1. Comparison of related concepts: passive gene-environment correlation, genetic nurture, and the shared environment. Figure S2. Simplified path diagram for RDR results. Figure S3. Simplified path diagram for pedigree results.Additional file 2. Code for running the Relatedness Disequilibrium Regression model.


Forensic haplotype analysis of the male Y chromosome is currently used to establish the number of male donors in sexual assaults, the number of male bleeders in blood pattern analysis, and for ancestry correlation to genetic founder populations in biogeographic studies. In forensic laboratory applications, its primary use is for DNA profile generation with trace amounts of male DNA in the presence of excess female DNA . Our study supports the potential use of the Y chromosome in a “dragnet” approach (most haplotypes are unique) similar to that described by Kayser in 2017 for solving a cold case sex assault and homicide in The Netherlands. Our study also researched the potential for the identification of an ancestral Irish genetic “footprint” linked to surname O’Brien and identified multiple founder group origins in Ireland and England as well as three samples with the Dal Riata (a Gaelic overkingdom) ancestral haplotype. This study indicates correlation to ancestral Irish ancestry by haplotype but not conclusively to the O’Brien surname. Genetic markers are used routinely for forensic applications and DNA databases . Y-STRs https://www.familytreedna.com/groups/ireland-heritage/about, accessed May 9, 2019). A second project researches the history of the Irish clans to identify founder populations and associated relatives many generations later. The goals of the Irish clan Y-DNA project are to connect genetic relatives and verify paternity and county of origin. Over 60 Irish clans are listed . A third project has easily accessible haplotype data for identification of an O’Brien genetic footprint or common haplotype. The O’Brien surname project is available at website https://www.familytreedna.com/groups/obrien/about/background, accessed October 10, 2018). This website consists of sampled individuals correlated by geography, Y-chromosome haplotype and single nucleotide polymorphisms (SNPs).There are several Irish ancestry projects related to biogeographical ancestry. Three major ones are described here. The Ireland Y-DNA Project has 8 580 number break noted and offers both Y-chromosome  testing and mitochondrial DNA  testing to add to verification of historical information regarding ancestry. One hundred and eighty-one samples with surname O’Brien are included in this project  following the buccal swab spin protocol [® Yfiler® PCR Amplification kit (ThermoFisher Scientific) manufacturer’s protocol on an Applied Biosystems PCR GeneAmp 9700 thermocycler (ThermoFisher Scientific). After PCR amplification, sample fragment separation and detection was performed on an Applied Biosystems 3130xl Prism® Genetic Analyzer (ThermoFisher Scientific). The results were then analyzed using GeneMarker software  to score alleles at each genetic locus. The haplotypes were transferred to Excel software for data analysis. A pair-wise analysis was performed on all the samples within each population. The resulting data were assessed for a common genetic footprint between specific populations. When reporting new match criteria with Y-chromosome polymorphisms, the DNA Commission of the International Society of Forensic Genetics (ISFG) recommends three methods: counting method, likelihood ratio and Bayesian statistic [Participants in our study were selected based on surname and ancestry and were asked to fill out a questionnaire (Appendix I) to gather background information (with informed consent). Buccal samples were collected and processed for male DNA haplotypes. Sample collection was performed according to University of New Haven guidelines and after Institutional Review Board (IRB) approval. Following human sampling, DNA from cotton swabs was extracted using the QIAampprotocol . DNA exttatistic . Our stuTen O’Brien’s of Irish descent were able to be successfully sampled and analyzed . From thAfter the pair-wise analysis of the randomly sampled O’Brien population was completed, trends were reviewed to determine if there were any similarities in males with varying locations of paternal origins and locations of origins of birth . In the https://www.familytreedna.com/groups/obrien/about/background. This is a large Irish population database that is being genotyped for common genetics based on a surname and is a larger dataset of independently collected and analyzed O’Brien samples. The O’Brien surname project has a common “genetic footprint” of 13-24-29-17-14-(11-14)-13-11-11-13-11-15-12-19 (DYS389I-DYS390-DYS389II-DYS458-DYS19-DYS385-DYS393-DYS391-DYS439-DYS392-YGATAH-DYS437-DYS438-DYS448). Our samples represent Irish that have emigrated out of Ireland to the US. Our 10 samples did not share this exact O’Brien surname “genetic footprint”, but remnants of the footprint remained within the haplotype. Percent sharing of the O’Brien surname alleles for our samples was: DYS389I (40%), DYS390 (30%), DYS389II (40%), DYS458 (30%), DYS19 (90%), DYS385 (80%), DYS393 (90%), DYS391 (60%), DYS439 (20%), DYS392 (60%), YGATAH (10%), DYS437 (70%), DYS438 (80%), DYS448 (40%). This allele frequency was then compared to 10 randomly sampled Caucasian with no O’Brien surname connection. Percent sharing of the general Caucasian sampling with the O’Brien surname alleles was: DYS389I (60%), DYS390 (30%), DYS389II (40%), DYS458 (70%), DYS19 (90%), DYS385 (50%), DYS393 (70%), DYS391 (30%), DYS439 (40%), DYS392 (60%), YGATAH (50%), DYS437 (50%), DYS438 (60%), DYS448 (50%). This information suggests that the most common alleles  are more fixed in the overall population while the residual O’ Brien surname “genetic footprint” may be only loosely correlated after emigration.A potential relationship between surnames and Y-STR haplotype was demonstrated in a study conducted by Sykes and Irven . In thisOur best interpretation is that the Y-chromosome and O’Brien surname is evolving over generations and once geographically unrestricted to Irish birthplace, only portions of the O’Brien surname “genetic footprint” remain. In fact, this is the strategy used for determining genetic relationships by paternal ancestry and is used routinely in evolutionary studies and family tree analyses. When comparing our O’Brien surname samples to the Oxford Genetic Atlas Project (OGAP) data in the Campbell study for R1b haplotypes, three samples carry the Irish ancestral signature of the Dal Riata, two samples bear the Northern Isles signature, two samples are consistent with Northern England and one sample is consistent with Central England . The rem


Cucurbita moschata) are one of the most important economic crops in genus Cucurbita worldwide. They are a popular food resource and an important rootstock resource for various Cucurbitaceae. Especially, C. moschata is widely used as a rootstock for the commercial production of bloomless cucumbers in East Asia. Since the genetic diversity of the commercial rootstock varieties is narrow, there has been an increasing demand for the trait development of abiotic and biotic stress tolerance breeding. In this study, 2071 high-quality SNPs that were distributed evenly across 20 chromosomes of pumpkins were discovered through the genotyping-by-sequencing (GBS) analysis of 610 accessions of C. moschata germplasm with a global origin. Using these SNPs, various analyses of the genetic diversity and the population structure were performed. Three subgroups were clustered from the germplasm collection, which included East Asia, Africa, and America, and these areas were included the most in each subgroup. Among those groups, accessions from Africa and South Asia showed the highest genetic diversity, which was followed by the Mexico accessions. This result reflected that large gene pools that consist of various native landraces have been conserved in those of countries. Based on the genetic diversity, we finally constructed the C. moschata core collection, which included 67 representative accessions from the 610 germplasms. Five morphological traits that are important in commercial grafting and rootstock seed production, which include the cotyledon length, the cotyledon width, the hypocotyl length, the internode length, and the number of female flowers, were investigated for three years and used to confirm the validity of the core collection selection. The results are expected to provide valuable information about the genetic structure of the worldwide C. moschata germplasm and help to create new gene pools to develop genetically diverse rootstock breeding materials.Pumpkins ( Cucurbita (Cucurbitaceae) has five major domesticated species, which include C. argyrosperma, C. ficifolia, C. maxima, C. moschata, and C. pepo, which have been cultivated globally as an economic crop [C. moschata is considered as the second most diverse species of the genus after C. pepo, and is closely related to C. argyrosperma in genomic status [C. moschata exhibits remarkable morphological diversity in its fruit and seed types, and is cultivated and consumed in many parts of the world in forms of mature and immature fruit, seeds, young stems, tendrils, and flowers [C. moschata is a versatile food source, and it has also been used as rootstock for vegetable grafting, particularly in Asia [The genus mic crop ,2. Amongc status ,4,5. C.  flowers ,7. C. mo in Asia .Fusarium wilt, overcoming the increase of temperature stress tolerance, and contributing to the production of high-quality fruit [C. ficifolia), pumpkins (C. moschata), and Shintoza (C. maxima × C. moschata) are mainly used [C. moschata germplasm for this.In most of East Asian countries, grafted seedlings are used routinely for commercial cucumber production for the purpose of overcoming continuous cropping disorders, escaping ty fruit . As cucunly used . In Korenly used . BloomleC. moschata germplasm until now, but there are many studies on the domesticated Cucurbita germplasm available, especially with C. pepo [There have been few studies about the genetic diversity of wild  C. pepo ,12,13. E C. pepo ,14,15. O C. pepo . As suchC. moschata germplasm from various origins and assessed the diversity with high quality SNPs that were distributed evenly among the pumpkin genome, which had a purpose to understand the genetic diversity and the population structure. Furthermore, we selected the compact size of the representative entries as a core collection and validated the core collection using the morphological traits related to the grafting and the flowering. The C. moschata core collection constructed in this study is thought to be efficiently applied to generate new gene pools and the consequent practical rootstock breeding.In this study, we gathered a large number of C. moschata var. Rifu version 1 was used for a reference genome. Following Lee [Based on genotyping-by-sequencing (GBS) method, around 1.5 billion reads were generated among 610 accessions, and more than 2 million reads per an accession were considered for alignment. In order to gather the efficient SNPs, the wing Lee  methods,Using 2071 high-quality SNPs, the population structure analysis was performed among the 610 accessions. After determining the best K , we coulThe distribution of the germplasm origin showed that most of the accessions belonging to Africa were placed in cluster 2. The American accessions were mostly located in cluster 3, and more than 300 accessions from Asia were distributed in cluster 1. Only eight accessions were native to Europe, and seven of them were placed in cluster 3 . CompariThe genetic relatedness within the entire germplasm were shown in phylogenetic tree based on the UPGMA clustering method, resulting in seven subgroups a. ComparAmong them, group 7 was clearly distinguished from the other groups, which is similar to the results from the PCA b, and thF-statistics were calculated from the 595 accessions without miss identification. The binary allelic data per locus was used for the statistical analysis and more than 1.3 alleles were effective. As expected, the heterozygosity (HE) and the Shannon’s diversity index (I) are the basic tools that are used to see the differences among the three clusters, and the average genetic diversity of the C. moschata germplasm collection was estimated to be 0.281 and 0.434 in the HE and the I, respectively (E = 0.327 and I = 0.494), whereas cluster 1 showed a lower genetic diversity than the others (HE = 0.202 and I = 0.328). According to the inbreeding coefficient (F), all three clusters were estimated over 0.7, which reflected the high inbreeding within the cluster. Comparing the value of the HO to the HE in each cluster, we could also expect that all the clusters were forced to inbreed, which support the F values . The calculated FST value of 0.48 indicated the largest difference between cluster 1 and cluster 3, whereas the smallest difference was found to be 0.21 between cluster 2 and cluster 3  was performed based on the pairwise genetic distances using GenAlEx 6.503. AMOVA revealed that 9.5 % of the total variation in the clusters . This coThe main purpose of this study is to select the core accessions, which are composed of reasonable sizes that could represent the genotypic diversity of the entire germplasm. Taking this into account, 67 accessions were selected from the 595 accessions based on the genetic variation that was calculated from the 2071 SNPs that were evenly distributed among the pumpkin genome . All theIn order to validate the unbiased selection, various phenotypic data was used to compare the entire germplasm and the core accessions among three survey years. The traits used for the validation were the cotyledon length, the cotyledon width, the hypocotyl length, the internode length, and the number of female flowers in ten nodes. The former three seedling traits are important to produce high-quality graft seedlings, and the latter two are considered as important traits in the cultivation and the seed production.The phenotypic range of the entire accessions for the cotyledon length was from 13.7 mm to 95.6 mm, which had an average 57.0 mm over the three survey years, whereas the core accessions ranged from 13.7 mm to 85.0 mm, which had an average of 52.4 mm over the three survey years . The ranCucurbita spp.) are one of the vegetables that have great socio-economic importance. Many of the Cucurbita germplasms have been cultivated over generations from family-based farmers in many countries. The selection of these germplasms has been practiced over time by these populations, which is associated with the exchange of seeds between them, and the natural occurrence of the hybridization in the germplasm of this species has contributed to its increased variability [Pumpkins  in Korea and the Agricultural Research Service (ARS) of United States Department of Agriculture (USDA). The scientific name and the origin of each accession were identified by referring to the passport data of the offering institute. However, some of them exhibited characteristics that differed from the general characteristics of the species. Additionally, in the genotype we identify genetic differences based on population structure, phylogenetic tree, and PCA. Therefore, it was excluded from the core collection construction. The number of SNPs and accessions used in each analysis were mentioned in the results section. The accession name, and the geographic locations are listed in The total of 610 Over a three-year period (2018–2020), the entire germplasm collection was planted in plastic houses at Anseong-si, Republic of Korea, and three traits of seedling and two traits related with the seed production were evaluated. Phenotypes related to the seedlings, which included the cotyledon length, the cotyledon width, and the hypocotyl length, were investigated from the 10th to the 12th day after sowing using calipers. The internode length and the number of female flowers in ten nodes were counted on the 40th day after transplanting. All the traits were investigated with two replicates in two plants per an accession.EcoRI/MseI; enzyme set with an EcoRI; adaptor. The libraries were pooled in seven tubes. The contents of the tubes were sequenced in separate lanes using the HiSeq 2000 platform  at Macrogen, which is located in Seoul, Republic of Korea. All the 101 bp reads were trimmed using 96 different barcode sequences as previous described [C. moschata var. Rifu (http://cucurbitgenomics.org/) as a reference genome sequence [The genomic DNA was extracted from the samples using the CTAB method , and theescribed . The filsequence . The reasequence . The rawad-hoc statistical method [In order to analyze the population structure of the entire germplasm (610 accessions) used in this study, we used a model based genetic clustering algorithm that is implemented in the STRUCTURE program ver. 2.3.4 . The numl method , which iThe phylogenetic trees were produced using genotyping data with 2071 SNP markers that used both the unweighted neighbor-joining method and the hierarchical clustering method based on the dissimilarity matrix calculated with the Manhattan index, which was implemented in the DARwin software (version 6.0.9). The entire germplasm was divided into subgroups based on the major nodes of the phylogenetic tree.F-statistics, which include the observed number of effective alleles (Ne), the heterozygosity (HO), the expected heterozygosity (HE), Shannon’s diversity index (I), the fixation index (F), and the genetic differentiation (FST), were used for the analysis and the comparison of the diversity. Indices Ne, HO, HE, I, F, and FST were calculated using GenAlEx 6.502. The analysis of the molecular variance (AMOVA) was conducted in order to detect the genetic variance within and among the population using GenAlEx ver 6.502.The In order to establish a core collection, the representative entries were selected based on the genotypic diversity analysis method of Lee . The rep


Debates surrounding genetic privacy have taken on different forms over the past 30 years. Taking genetic privacy to mean an interest that individuals, families, or even communities have with respect to genetic information, we examine the metaphors used in these debates to chronicle the development of genetic privacy. In 1990–2000, we examine claims for ownership and of ‘humanity’ spurred by the launch of the Human Genome Project and related endeavors. In 2000–2010, we analyze the interface of law and ethics with research infrastructures such as biobanks, for which notions of citizenship and ‘public goods’ were central. In 2010–2020, we detail the relational turn of genetic privacy in response of large international research consortia and big data. Although each decade had its leading conceptions of genetic privacy, the subject is neither strictly chronological nor static. We conclude with reflections on the nature of genetic privacy and the necessity to bring together the unique and private genetic self with the human other. In this retrospective, we have taken on the unenviable task of tracing the debates surrounding genetic privacy over the past 30 years or so. The task would surely be simpler if there were agreement about what this topic—privacy—is even about. Described as ‘exasperatingly vague and evanescent’, privacy frequently alludes precision, even with the best efforts . Its defWe will not, and indeed cannot, detail the myriad nuances of the field, and are even less able to ‘solve’ the privacy issues genomics and its applications bring about. That is a Sisyphean task for another decade and for other authors. What we will do is present the leading privacy debates in genetic privacy over the past three decades. Our contention is that each decade’s debates had its own metaphors to assist in understanding genomics and then in regulating the activities where genetic privacy was implicated. Although both authors are former students of literature, the use of metaphor within law and ethics, across time periods and traditions, is so essential to the disciplines that it is difficult to conceive of law or ethics without it . No decaBefore embarking, it is best to define what we understand genetic privacy to be. Genetic privacy is, at its core, an interest that individuals, families, or even communities have with respect to genetic information. These interests also ground claims with associated rights and obligations of ownership, of control, of exclusion, of non-interference, of protection, etc. We take an interest-based approach as it can encompass the breadth of the debates in the field over the past 30 years Genetic privacy may implicate an entire cast of actors—probands, their families, sequencing laboratories, researchers, clinicians, health system administrators, insurance companies and even public health agencies. The tricky issue for law and ethics is to determine which interests or claims should be recognized and reconciled among themselves. Central issues include: Do we give probands the sole prerogative to decide what happens with ‘their’ genetic information? Or do their families, or even communities, have a say? The metaphor used may give clues as to the intended outcome, a form of path dependency.The launch of the Human Genome Project in 1990 was a catalyst for increased attention and thinking about the ethical and legal consequences of genomics. It was clear that genetic data would play an increased role in the biosciences and within society more broadly. One scholar, for example, posed a portentous question—will genetic information ‘impel us to take privacy much more seriously in the genetic realm … or lead us to give up on maintaining personal privacy altogether’ ? In a waThere was early recognition that genetic data were different from other kinds of medical data . The datMore modestly, were genetic data ‘an individual’s probabilistic future diary’ ? Or perhHealth Insurance Portability and Accountability Act of 1996, at least eight states had legally recognized a genetic privacy interest  genetic testing brought about its own major shift in context—genetics was taken from the lab to the home. Genetic data became yet another medium through which relationships were expressed. Individuals’ genetic privacy fell into their own hands and challenged the largely paternalistic lens of biomedical ethics . With DTContinued reliance on consent suggests that proprietary understandings of genetic privacy, in some form, are here to stay . DespiteAfter some decades of ‘genetic privacy’ concerns, some have dismissed its distinctiveness entirely, instead underscoring that the issues genetic data pose are little different from ethical and legal inquiries regarding rights and obligations and of living together . Others The advent of big data has seen individuals constructed into groups of which they are unaware, much less self-identify . ConsideObligations may indeed be better suited to issues such as familial interests in genetic information—the proband has independent privacy rights but also, in certain circumstances, the responsibility to consult with relevant family members. Although ethics has little issue recognizing such obligations , the lawOur study of genetic privacy spanning the last 30 years reveals approaches that are neither strictly chronological nor static. With more facets of social life rooted in information flows, privacy, genetic or otherwise, finds itself interacting with other incommensurables. Indeed, the progressive realization of human rights, such as the human right to science, hinge upon the sharing of data . SocietiConflict of Interest statement. None declared.Today, when digitized and presented as subpopulations, as polygenic risk scores in common diseases, as predisposition, susceptibility or resistance to risk, or, as epigenetic lifestyle risks, the question becomes less one of individual genetic privacy than one of groups and relationships that demonstrate genomic equivalence in difference. As genetic testing becomes commonplace, formerly ‘private’ genetic information will be shared as any other type of health information in the clinical care of patients and their families. The success of precision medicine hinges on facilitating contributions to the healthcare system to promote the validation and interpretation of the health implications of individual variants. Such a systemic approach to ownership, citizenship and relationships must promote the right of everyone to benefit. In short, the future genetic self is necessarily linked to others. The unique and private genetic ‘me’ is discovered through the study and comprehension of the human ‘us’.


OsS40 genes of Oryza sativa were identified in our previous work, but their functions remain unclear. In this study, 13 OsS40 members were knocked out using the CRISPR/cas9 gene-editing technology. After screening phenotype characterization of CRISPR/Cas9 mutants compared to WT, five oss40s mutants exhibited a stay-green phenotype at 30 days after heading. Moreover, increased grain size and grain weight occurred in the oss40-1, oss40-12, and oss40-14 lines, while declined grain weight appeared in the oss40-7 and oss40-13 mutants. The transcript levels of several senescence-associated genes (SAGs), chlorophyll degradation-related genes (CDGs), as well as WRKY members were differentially decreased in the five stay-green oss40s mutants compared to WT. Five oss40 mutants also exhibited a stay-green phenotype when the detached leaves were incubated under darkness for 4 days. OsSWEET4 and OsSWEET1b were significantly upregulated, while OsSWEET1a and OsSWEET13 were significantly downregulated in both oss40-7 and oss40-14 compared to WT. Furthermore, these five OsS40 displayed strong transcriptional activation activity and were located in the nucleus. Most of the OsS40 genes were downregulated in the oss40-1, oss40-7, and oss40-12 mutants, but upregulated in the oss40-13 and oss40-14 mutants, indicating coordinated regulation among OsS40 members. These results suggest that OsS40-1, OsS40-7, OsS40-12, OsS40-13, and OsS40-14 are senescence-associated genes, involved in the senescence and carbon allocation network by modulating other OsS40 members, SWEET member genes, and senescence-related gene expression.A total of 16  In the nyc1 mutant, chlorophyll b cannot be degraded because of the abnormal binding of light-harvesting chlorophyll  can induce the degradation of chlorophyll  knockdown in rice leads to accumulation of pheide a and prolongs the greenness of the leaf during dark incubation  mutants, which show a delayed leaf senescence phenotype -harboring proteins in Arabidopsis thaliana (L.) Heynh., Hordeum vulgare L., and Oryza sativa L. ssp. japonica  were mutated, and their edited mutants were used for systematic characterization of the OsS40s during natural senescence of rice leaves. Five OsS40 member mutants showed a delayed flag leaf senescence (stay-green) phenotype and dark-induced senescence of detached leaves and displayed a distinct effect on grain weight. These five senescence-related members were further characterized with regard to their transcriptional activity and subcellular localization. Meanwhile, genetic analysis revealed complex relationships among OsS40 members and a subgroup of OsS40 genes implicated in natural senescence and dark-induced senescence of rice leaves. These results provide important clues to the mechanism underlying rice leaf senescence.In this study, by using CRISPR/Cas9 gene-editing technology, 13 oss40 mutants and their parental WT Nipponbare (Oryza sativa L. ssp. japonica) and Oryza sativa cv. CO39 for rice protoplast were grown under 16 h light at 30°C/8 h night at 22°C greenhouse conditions. Seeds were germinated in wetted filter paper at 37°C for 2 days in darkness and then grown in a growth chamber condition after transplanting in small plastic pots filled with an equal amount of vermiculite and compost. For all the experiments, rice seedlings were grown in small pots of similar sizes (five plants per pot). For expression profiling analysis, same-germination-stage, 1-month-old plant leaf samples were collected from the WT and knockout mutants. Thirty-day-old seedlings were then transplanted, one plant per big plastic pot containing field soil. Fertilizer was applied (nitrogen–phosphorus–potassium) two times in the growth period during transplantation in a big pot and after the heading stage. After the heading initiation, the flag leaves were tagged to enable identification of the same stage leaf to compare visible phenotype and chlorophyll measurement between mutants and the wild type.The OsS40 genes CRISPR-edited plants were generated with the aid of Hangzhou Biogle Co., Ltd. , following a method described previously by Wang et al. . The first-strand cDNA was obtained from 1 μg of total RNA, using the Synthesis Kit (Thermo Fisher Scientific), eliminating the contaminant genomic DNA. qRT-PCR was performed to analyze the expression of genes in the CFX96 machine  in a whole volume of 15 μl, using SYBR Green Master (ROX)  as per the instructions of the manufacturer. The primer sequences used for expression analysis of the OsS40s were as described in Zheng et al. (OsACTIN gene (LOC_Os03g50885) was used as the reference gene. Relative expression levels of target genes were calculated using the 2−ΔΔCt method as mentioned  were used for RNA extraction. Young leaves, stems, and roots were collected from 2-week-old seedlings under greenhouse conditions. Mature leaves were obtained at the floral induction stage. For detection of senescence-associated gene expression in the g et al. . The endOsWRKY44 (LOC_Os03g21710) . The effectors, reporter, and internal control plasmid were co-transfected into protoplasts (about 2.5 × 106 cells/ml) isolated from rice primary leaves. After culturing for 12–16 h, luciferase assays were performed according to Fraiture et al.  as described previously by Zheng et al. . Chloropt-test was used for mean comparisons. All these were carried out using the GraphPad Prism software version 8 .The data in all figures were determined by at least three biological replicates. One-way ANOVA was performed to understand the differences in levels of gene expression among distinct rice tissues. The Student's Oryza sativa L. ssp. japonica), growing under optimum conditions, undergo natural senescence, which is controlled by various tissues in development. To gain insight into the potential functions of OsS40 genes during natural rice growth, qRT-PCR detected the expression changes of all 16 OsS40 members in rice young leaves, mature leaves, roots, stems, and seeds. Although the absolute mRNA levels of some OsS40 genes, such as OsS40-3 and OsS40-11, were extremely low, their transcript tendency in different tissues was still comparable. Among them, 12 members  displayed higher transcript levels in mature leaves, while their transcript level was lower in young leaves   at 4-week-old seedling under greenhouse conditions. However, when the detached primary leaves were incubated for 4–6 days under darkness treatment, the delayed leaf senescence occurred in the five OsS40 member knockout lines  relative to wild-type , at 30 days after heading (DAH). In comparison to NIP, greater plant height occurred in the oss40-1, oss40-13, and oss40-14 mutants, and more tillers appeared in the oss40-13 mutants at 7 DAH , oss40-7.1, oss40-12 , oss40-13 , and oss40-14.1 mutants at 30 DAH compared with NIP , such as glyoxylate aminotransferase (OsH36), seed imbibition protein (OsH69), and isocitrate lyase (Osl85). Various hormonal-signaling pathway-related genes such as ABA signaling-related OsNAP, ethylene signaling-related ETHYLENE INSENSITIVE 3 (OsEIN3), and SA signaling-related SALICYLIC ACID 3 HYDROXYLASE (OsS3H). The transcript levels of several SAGs and CDGs in senescing mature leaves (the first completely developed leaf from the bottom at the four-leaf stage) of oss40s knockout mutants and NIP were examined by qRT-PCR. The data indication by heatmap analysis revealed that most of the tested senescence-related marker genes were significantly downregulated in oss40-7, oss40-12, and oss40-13 mutants compared with NIP, while a few of them showed higher expression in oss40-8 and oss40-11 mutants. The transcript levels of these SAGs and CDGs showed a different but declining tendency in the remaining oss40 mutants, except for the transcript level of OsS3H, which exhibited clear upregulation in the oss40-5 mutants , such as Os mutants , suggestOsS40s, transcript levels of these senescence-related WRKY members, selected from the DEGs of oss40-14 /WT RNA-seq dataset  were downregulated in the oss40-1, oss40-12, and oss40-13 mutants. With the exception of WRKY19, the other WRKY genes showed decreased expression levels in the oss40-7 mutant. However, only WRKY46 displayed reduced transcript levels in the oss40-14 mutant . The expression levels of OsSWEET4, OsSWEET1a, OsSWEET13, and OsSWEET1b were altered in the 1-month-old fully expanded primary leaves of both oss40-7 and oss40-14 mutants compared with WT. OsSWEET4, OsSWEET13, and OsSWEET1b were upregulated in the oss40-7 mutant, while OsSWEET4, OsSWEET1a, and OsSWEET1b were upregulated in the oss40-14 mutant  activity assays in the rice protoplast system . With a threshold of p < 0.05, the generated hub network revealed that OsS40-7 and OsS40-12 presented most associations with other OsS40 members, which was reflected by the biggest size and darkest red in their nodes. It implied that OsS40-7 and OsS40-12 may act as the master members controlling the expression of other natural senescence-related OsS40 genes  mutants, showing a stay-green phenotype compared with wild type; a similar phenotype was noted in the A. thaliana T-DNA insertion mutant line of ats40-3  families in the Pfam database. Currently, there are 201 DUF584 domain-containing proteins listed  phenotype in developing rice grains and stay-green spikes , seed imbibition protein (OsH69), and isocitrate lyase (Osl85)  mutant lines, the stay-green phenotype did not appear in their senescencing flag leaves. However, after dark treatment, the detached leaves appear to delay senescence in the five mutants, which possibly hinder progression of natural senescence and improve vegetative growth, leading to delayed flag leaf yellowing or higher plant height or more tillers. For example, rice osein2/mhz7 mutant lines showed delayed dark-induced leaf senescence and higher plant height under field-grown conditions  through upregulation of CDGs, such as via a very complex regulatory network  can even control an entire cellular process  can be found in the article/XZ and YM conceived and designed the research. H, JX, AG, YL, CF, JU, and CH collected the data. H, JX, YZ, and XZ analyzed the data. H, XZ, and YM drafted and revised the manuscript. All authors read and approved the final 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Lightfield microscopy has raised growing interest in the last few years. Its ability to get three-dimensional information about the sample in a single shot makes it suitable for many applications in which time resolution is fundamental. In this paper we present a novel device, which is capable of converting any conventional microscope into a lightfield microscope. Based on the Fourier integral microscope concept, we designed the lightfield microscope eyepiece. This is coupled to the eyepiece port, to let the user exploit all the host microscope’s components  and get a 3D reconstruction of the sample. After the optical design, a proof-of-concept device was built with off-the-shelf optomechanical components. Here, its optical performances are demonstrated, which show good matching with the theoretical ones. Then, the pictures of different samples taken with the lightfield eyepiece are shown, along with the corresponding reconstructions. We demonstrated the functioning of the lightfield eyepiece and lay the foundation for the development of a commercial device that works with any microscope. Widefield microscopy is unsuitable for applications in which three-dimensional information of the sample is required, due to the small depth of field and the lack of optical sectioning. For this reason, many microscopy techniques have been developed to obtain 3D information. Many of them rely on capturing multiple images ,5,6,7, wThe lightfield technique proceeded from Integral Photography , and wascroscopy ,16,17,18The optical scheme of FiMic is presented in Here we demonstrate the design, construction, and functioning of this novel device. Then, we demonstrate that the experimental parameters agree with the theoretical ones and show some experimental images with different kinds of samples. For the experimental images, the device was attached to different microscopes, thus demonstrating its universality.For the construction of the proof-of-concept device, we used a Nikon TE2000-U as a host microscope. We designed the device to adapt it to two routine objectives in terms of magnification and numerical aperture: a 20x/0.50 (CFI Plan Fluor 20X from Nikon) and a 40x/0.75 objective (UPlanFl N 40X from Olympus). It is important to underline that the device works exclusively with infinity-corrected objectives.EPf), the pitch (MLAp), and focal length (MLAf) of the microlens array and the pixel size of the sensor . Moreover, we set a minimum pitch of 1 mm, because smaller microlenses would reduce too much the field of view . If we solve Equation λN2NANote that, in Equation , we consFor the eyepiece, we decided to use the Ramsden design. The decision to use a combination of lenses instead of a single lens is due to two reasons. The first one is to reduce aberrations, in fact, the Ramsden eyepiece reduces chromatic aberrations, spherical aberrations, distortion, astigmatism, and coma . The secIn the Ramsden design, the two lenses can be identical and their separation is equal to approximately two thirds of their focal length. The effective focal length of a two-lens system is:In our case, we chose In ormation . The supFor the mechanical construction of the device, we used both optomechanical components from Thorlabs and self-built mechanical parts. The device is shown in MLAf from the sensor.For coupling the device to the eyepiece port of the microscope, we used a cylindrical adapter whose outer diameter is equal to the inner diameter of the eyepiece port. From the international standard ISO 9345:2019(E), we know that the intermediate image of a microscope is formed inside the eyepiece port at a distance of 10 mm from the eyepiece locating surface of the viewing tube. So, we inserted a 3D-printed field stop into the eyepiece adapter, right at that distance. The MLA was inserted in a 3D-printed holder. This holder was inserted in a Z-axis translation mount with a micrometer knob for fine positioning of the MLA at a distance TLd < TLf, where TLd is the distance between the aperture stop of the microscope objective and the tube lens, and TLf is the focal length of the tube lens. This produces an axial displacement of the exit pupil from the back focal plane of the eyepiece, which depends on the distance between the objective and the tube lens:EPl’ is the distance from the back focal plane of the Ramsden eyepiece to the position of the exit pupil, and We had to adjust the distance of the MLA-sensor system to the second lens of the eyepiece. In fact, in the microscope, the objective and the tube lens are not in telecentric configuration, as First of all, we verified the resolution of the lightfield eyepiece itself (out of the microscope), which we call intrinsic resolution. To do so, we placed the USAF 1951 resolution chart (58–198 from Edmund Optics) at the object focal plane of the eyepiece and we measured the contrast at the highest resolution resolvable elements. We consider the frequency at which the MTF is equal to 10% as the limit, because the measurements show good linearity until that point.co,difu is the cut-off frequency of the optical system, u is the frequency in the object space of the eyepiece and osδ is the scaled pixel size The overall MTF is the product of two contributions, the diffraction MTF of the optical system and the detector footprint MTF. If we consider an ideal optical system (limited only by diffraction) and a perfect detector, we have an overall ideal MTF :(9)MTFidOnce the intrinsic resolution was validated, we verified the extrinsic resolution with the objectives cited above. To do so, we coupled the device to the host microscope and we placed the USAF chart at the object plane. In this case, the cut-off frequency is Subsequently, we evaluated the extrinsic depth of field (DOF) with both objectives. To do so, we imaged the USAF resolution chart and we shifted it from the object plane by a constant step. We fixed a frequency (an element of the USAF chart) and we measured the contrast at that frequency at every shifted plane. The DOF is defined as the interval in which the contrast loss is smaller than a factor of Substituting the data of both objectives in the equation, we obtain After having verified the 2D resolution of the device, we tested its ability to reconstruct three-dimensional samples. For this purpose, we imaged some thick samples in different host microscopes. The purpose of imaging different samples in different microscopes was to test the functioning of the device when inserted in multiple host microscopes as well as demonstrating its imaging capability. The performances of the device in the different setups depend mainly on the resolution obtained (Equation ) and theAs we mentioned in To reconstruct the sample volume, we used the shift and multiply (S&M) method , which iFirstly, we used the microscope described above to image cotton fibers with the 20x objective. The fibers were stained with a fluorescent highlighter so that the emission could be observed with a filter cube with these data: excitation filter EX510-560, dichroic mirror DM575, barrier filter BA590. The results are shown in Then, the device was tested in an Amscope microscope (T670Q-PL-FL). Living phytoplankton were imaged using darkfield illumination and a 20x/0.40 objective. We recorded a video of the moving sample and then reconstructed it in a volume of 201.4 µm of depth, with Finally, the device was tested in a Leica TCS LSI microscope. In this case, the sample was Arabidopsis Thaliana stained with Propidium Iodide. The sample was prepared as described in  and it wIn this paper, we presented the lightfield microscope eyepiece, which converts any optical microscope into a lightfield microscope. We detailed the choice of the optical and mechanical components and we demonstrated its functioning with multiple configurations, varying the host microscope, the objective, and the illumination technique. We demonstrated that the overall system achieves 1.99 µm lateral resolution at 10% contrast with a 40X objective and 4.20 µm lateral resolution at 10% contrast with a 20X objective, in line with the theoretical performances. Finally, we imaged different thick samples and demonstrated the ability of the system to reconstruct volumes of up to 300 µm of depth.The lightfield microscope eyepiece is a patented device (publication number WO/2020/ 030841)  and it i