SFTP SNPs with idiopathic pulmonary fibrosis (IPF) by studying novel computational models where the epistatic effects  of SNP-SNP interactions could be evaluated, and then compared the results with a previously published hypersensitivity pneumonitis (HP) study where the same novel models were used. Mexican Hispanic patients (IPF=84 & HP=75) and 194 healthy control individuals were evaluated. The goal was to identify SP SNPs and SNP-SNP interactions that associate with IPF as well as SNPs and interactions that may be unique to each of these interstitial diseases or common between them. We observed: 1) in terms of IPF, i) three single SFTPA1 SNPs to associate with decreased IPF risk, ii) three SFTPA1 haplotypes to associate with increased IPF risk, and iii) a number of three-SNP interactions to associate with IPF susceptibility. 2) Comparison of IPF and HP, i) three SFTPA1 and one SFTPB SNP associated with decreased risk in IPF but increased risk in HP, and one SFTPA1 SNP associated with decreased risk in both IPF and HP, ii) a number of three-SNP interactions with the same or different effect pattern associated with IPF and/or HP susceptibility, iii) one of the three-SNP interactions that involved SNPs of SFTPA1, SFTPA2, and SFTPD, with the same effect pattern, was associated with a disease-specific outcome, a decreased and increased risk in HP and IPF, respectively. This is the first study that compares the SP gene variants in these two phenotypically similar diseases. Our findings indicate that SNPs of all SFTPs may play an important role in the genetic susceptibility to IPF and HP. Importantly, IPF and HP share some SP genetic variants, suggesting common pathophysiological mechanisms and pathways regarding surfactant biogenesis, but also some differences, highlighting the diverse underlying pathogenic mechanisms between an inflammatory-driven fibrosis (HP) and an epithelial-driven fibrosis (IPF). Alternatively, the significant SNPs identified here, along with SNPs of other genes, could serve as markers to distinguish these two devastating diseases.Surfactant proteins (SPs) are important for normal lung function and innate immunity of the lungs and their genes have been identified with significant genetic variability. Changes in quantity or quality of SPs due to genetic mutations or natural genetic variability may alter their functions and contribute to the host susceptibility for particular diseases. Alternatively, SP single nucleotide polymorphisms (SNPs) can serve as markers to identify disease risk or response to therapies, as shown for other genes in a number of other studies. In the current study, we evaluated associations of  Idiopathic pulmonary fibrosis (IPF) is one of the most common interstitial diseases of unknown etiology and poor prognosis , 2. It iHypersensitivity pneumonitis (HP) is another type of interstitial lung disease caused by an exaggerated immune response to environmental antigens, such as fugal, bacterial or bird proteins . AlthougIPF and HP are different diseases with different etiologies. Validated risk factors for IPF include mainly aging and smoking; exposure to metal dust, wood dust, pesticide, and occupational history of farming or agriculture also increased the risk of IPF. Likewise, the risk of HP is associated mainly to the exposure to organic particles and varies with regional disparities in climate, occupational exposures, and environmental exposures, but not ethnicity. Respiratory viral infections, and high pesticide exposure, have been revealed as risk factors. Paradoxically, cigarette smoke reduces the risk of HP, but when smokers develop HP, they often follow a chronic fibro-proliferative course. However, there is a considerable overlap in pathophysiology and clinical presentation , 12–14. Pulmonary surfactant and surfactant proteins (SPs), have been shown to play roles in host-defense functions, i.e. regulation of pro-inflammatory cytokine production, chemotaxis, and tissue repair –20, and SFTPA1 and SFTPA2, located on chromosome 10  with IPF in a Mexican population . In addiIn the present study, we used a statistical approach  where noThe IPF and HP study population are the same as the ones described before , 22. BriSFTPA1, four from SFTPA2, four from SFTPB, two from SFTPC, and two from SFTPD.We evaluated, as shown in As mentioned previously , we usedThis SNP-SNP interaction approach  has beenIn the present study, we observed significant differences in the studied groups with the single- and the three-SNP interaction model. We did not observe any significant SNP-SNP interactions in the two-SNP interaction model.SFTPA1, were each associated with decreased risk of IPF   Table 3.As previously described, each SNP can have additive, dominant or recessive effect on the disease phenotype and these are noted as a, d, and r, respectively. In our analysis, each SNP had dominant or additive effects, and no recessive effect was observed  alone, 14 were among hydrophobic SPs  alone, and the others were among SNPs of both the hydrophilic and hydrophobic SPs. Third, most interactions (n=196) were associated with increased risk of IPF  and the remaining (n=81) were associated with decreased risk of IPF . Among the interactions with increased risk of IPF, 7 were in the same SP gene (intragenic). Of these, 6 were in SFTPA1  and 1 in SFTPB (with dxaxd interaction effect). Among the interactions with decreased risk of IPF, 2 were intragenic in the SFTPB with dxdxa interactions. No significant interactions were observed with recessive (r x r x r) or additive effects (a x a x a) only.We found a total of 277 significant SNP-SNP interactions associated with IPF in the three-SNP model. The interactions are shown in detail in SFTPA (4 SFTPA1 and 2 SFTPA2), 4 of SFTPB, 2 of SFTPC and 2 of SFTPD. Although all of these SNPs were frequently present in the significant SNP-SNP interactions, the rs1059046 of SFTPA2 encoding amino acid 9 ((AA9), Asn>Thr) was the most frequently present followed by SFTPC SNPs. The frequency of each of the 14 SNPs found in significant SNP-SNP interactions associated IPF are shown in Overall, out of the 17 SNPs studied, 14 were found in SNP-SNP interactions shown to significantly associate with IPF in the three-SNP model. Of the 14 SNPs, six were SNPs of SFTPB SNPs  and twelve interactions had two-SNPs with additive and one with dominant effect. In all but one, the SFTPA1 SNP , leu>val) was the one with the dominant effect.Thirteen interactions had OR greater than 5 indicating a strong association with increased risk of IPF Table 5.SFTPA1 were associated with increased risk of IPF  and all exhibited a dominant effect , GA (rs1136450 x rs1136451) and GG (rs1136451 x rs1059057) of the t effect Figure 1SFTPA1 was associated with a decreased risk for both diseases. The rs1059047 and the rs1059057 of the SFTPA1 were associated with decreased risk of IPF, whereas the rs1136451 of the SFTPA1 was associated with increased risk of HP. The rs1130866 of the SFTPB was associated with decreased risk of HP.As shown in We studied the common SNP-SNP interactions in the three SNP model between the 277 interactions resulting from the comparison of the IPF group vs the control group (present study) and the 97 interactions resulting from the comparison of the HP group vs the control group in the three SNP model from our previous study . Of the SFTPA2, SFTPA1, SFTPD, respectively), noted as #4 in We observed 28 interactions that involved the same SNPs (n=28) that exhibited the same effect pattern (n=29); Interaction #4 Table 7 The interactions with the same SNPs (n=37) but with different pattern effects exhibited altered susceptibility in the two diseases and are shown in Of note, rs1059057 and rs7316 were not present in any of the common SNP-SNP interactions.SFTP SNPs with IPF using a novel statistical method and compared the results of the current study with a previously published HP study  three SFTPA1 haplotypes to associate with increased IPF risk, and iii) a number of three-SNP interactions to associate with IPF susceptibility. 2) After comparison of IPF and HP, i) three SFTPA1 and one SFTPB SNP were found to associate with decreased or increased risk in IPF and HP and one SFTPA1 SNP to associate with decreased risk in both IPF and HP, ii) a number of three-SNP interactions with the same or different effect pattern associated with IPF and/or HP susceptibility; iii) one of the three-SNP interactions that involved SNPs of SFTPA2, SFTPA1, and SFTPD, with the same effect pattern, was associated with a disease-specific outcome, a decreased and increased risk in HP and IPF, respectively. The findings of the current study may provide an example to start differentiating these two diseases based on their genetic background.Surfactant proteins (SPs) are important in normal lung function and also in innate immunity of the lungs. Changes in quantity or quality of SPs due to genetic alterations may alter their functions, whether in host defense and/or surfactant-related processes, and contribute to the host susceptibility for particular diseases. SP-A, for example, plays an important role in innate host defense against various pathogens, irritants, and other  and its HP study . The goaFor the current study, we took advantage of the same ethnic background of cases for both diseases (IPF and HP) and controls, i.e. All study subjects were Mexican Hispanic patients and all of them were enrolled from the same center. We hoped that this will help identify genetic patterns that in turn may enable distinguishing these two diseases or at the very least provide a paradigm for further work where genetic models could be used to find disease-specific markers.SFTPA1 gene is shown in the present study, via different analyses, including the use of a single SNP model, haplotype analysis and SNP-SNP interactions, to associate with IPF susceptibility. One of its SNPs, rs1136450, was the most frequently observed SFTPA1 SNP in the 3-SNP interactions. This SNP was found to be significant either by itself, as part of significant haplotypes, or part of significant 3-SNP interactions and has been found previously to associate with susceptibility with other pulmonary diseases including community acquired pneumonia  have a leucine at AA50 except the 6A2 variant that has a valine. On the other hand, all frequently found and studied SP-A2 variants have a valine , rs1136450 (AA50_C), and rs1136451 (AA62_G) with increased risk of IPF  and two other SFTPA1 SNPs  were shown to associate with decreased risk but haplotypes that included the rs1136450 and/or the other two SNPs were associated with increased risk. Moreover, a number of 3-SNP interactions, where the rs1136450 had a dominant effect and any other two SNPs had an additive effect, exhibited a high odds ratio indicating risk. However, when the rs1136450 in 3-SNP interactions was found with different effect patterns, the interactions were associated with either increased or decreased risk. An example to demonstrate this is depicted in the 3-SNP interactions, #9 and #28 in SFTPA2 rs1059046 , was found to associate with decreased risk in both diseases, other SFTPA1 SNPs were associated with IPF or HP disease-specific susceptibility. Thus, these point to a potential use of these SNPs as markers to distinguish between these two diseases. The SFTPA1 significant SNPs that change the encoded amino acid may affect functional aspects of the protein variant. The significance of the rs1136450 has been discussed above under IPF. The rs1059047 of SFTPA1 that associates with decreased risk in IPF, changes amino acid 19 . This amino acid may or may not be part of all the mature SP-A1 molecules  was associated specifically with decreased risk in HP. The SP-B protein plays a crucial role in surfactant function and some mutations are not compatible with life (SFTPB SNP noted above is responsible for a missense codon (ACT/ATT) that changes amino acid 131 from a Threonine (ACT) to Isoleucine (ATT) and eliminates an N-linked glycosylation site (Asp129-Gln-Thr131)  . Althoug-Thr131) . Whether-Thr131) .SFTPs, with two of these (interactions #9 and 10) containing SNPs only from the hydrophobic surfactant proteins (SFTPB and SFTPC), one (interaction #4) contained SNPs only from the hydrophilic proteins  and one (interaction #8) contained SNPs from both groups . Collectively, these indicate a role of all the surfactant proteins in the susceptibility of these diseases. Furthermore, the disease-specific lung microenvironment may alter the susceptibility of the host  the use of a newer statistical analysis to study SNP-SNP interactions with adjustment of important variables such as age, sex, and smoking status, b) enrollment of a patient population and control study groups with a similar ethnic background from the same center; therefore, the population structure of the studied groups may not be a major issue. Although, the second strength maybe a limitation , to our current knowledge ethnicity is not a significant risk factor as both diseases occur similarly in different ethnic groups as reported worldwide. However, there is limited information to determine whether differences in the frequency of the surfactant protein genetic variants, epigenetics, or differences in the SNP-SNP effect patterns studied here exist among different groups that could potentially point to different underlying processes in the pathogenesis of these disease. Thus, it is prudent to replicate the present findings in a larger sample size by case control studies with clinically confirmed cases of IPF and HP of other groups of heterogeneous non-Hispanic patients from various ethnicities in order to validate and strengthen the differential diagnostic potential of the identified SNPs and SNP interactions.SFTPs appear to play an important role in identifying disease susceptibility in IPF and HP interstitial lung diseases. Similarities between these two diseases with regards to the surfactant protein genes variants were observed in haplotypes or in 3-SNP interactions, as well as differences highlighting the different underlying pathogenic mechanisms between an inflammatory-driven fibrosis (HP) and an epithelial-driven fibrosis (IPF). In addition, the disease-specific associations of the SP polymorphisms hold the potential for these SNPs to be used as markers to distinguish between these two diseases. The information obtained in the current study was enabled via the use of newer/novel statistical methods to study models of single SNPs as well as SNP-SNP interactions where epistasis could be addressed. SFTPA1 and SFTPB SNPs might be of particular interest for future studies, where these could be used as markers either individually or together with other biomarkers in an attempt to distinguish between these two similar diseases. This is of great importance as it could help downstream decision-making of diagnosis and disease-specific therapies of these two devastating diseases.In conclusion, SNPs of all The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below:dbSNP, accession number: 1063345.The studies involving human participants were reviewed and approved by National Institute of Respiratory Diseases in Mexico City. The patients/participants provided their written informed consent to participate in this study.AA analyzed the data and wrote the original draft of the manuscript. CC performed the statistical analysis. CG contributed to the manuscript writing. MS and AP were responsible for sample collection and patient screening as noted in previous publications and contributed in manuscript writing. RW worked closely with CC and guided the statistical analysis. JF supervised the entire project and worked closely with all co-authors and especially with AA to ensure quality of data analysis and finalize the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by NIH HL34788 to JF.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.


Rickettsia is a maternally transmitted endosymbiotic bacterium that infects most insect species. In the current study, we investigated the biological and physiological effects of Rickettsia infection on whitefly, Bemisia tabaci. Our results revealed that infection with Rickettsia increased the fertility, survivorship, and shortened the nymphal developmental duration of whitefly Bemisia tabaci. Rickettsia infected B. tabaci had significantly higher glycogen, soluble sugar and trehalose contents than those of Rickettsia negative B. tabaci individuals. When exposed to the entomopathogenic fungus Akanthomyces attenuatus and the insecticides imidacloprid and spirotetramat, Rickettsia infested B. tabaci had lower mortality rates and higher semi-lethal concentrations (LC50). The parasitism by Encarsia formosa was also reduced by Rickettsia infection.Bemisia tabaci, are infected with the facultative endosymbiont Rickettsia. However, the mutualism between Rickettsia and its whitefly host remains unclear. This study investigated the biological and physiological benefits of Rickettsia infection to B. tabaci. Results revealed that infection of Rickettsia increased the fertility, the survival rate from nymph to adult and the number of female whiteflies. In addition, this facilitation caused a significant reduction in nymphal developmental duration but did not affect percentage rate of egg hatching. Rickettsia infected B. tabaci had significantly higher glycogen, soluble sugar and trehalose contents than Rickettsia negative B. tabaci individuals. Rickettsia also improved the immunity of its whitefly hosts. Rickettsia infested B. tabaci had lower mortality rates and higher semi-lethal concentrations (LC50) when exposed to the fungus Akanthomyces attenuatus and the insecticides imidacloprid and spirotetramat. The percentage of parasitism by Encarsia formosa was also reduced by Rickettsia infection. Overall, Rickettsia infection benefits B. tabaci by improving the nutritional composition of its host, and also protects B. tabaci by enhancing its resistance towards insecticides (imidacloprid and spirotetramat), entomopathogenic fungi (A. attenuatus) and its main parasitoid (E. formosa); all of which could significantly impact on current management strategies.Endosymbionts play an essential role in the biology, physiology and immunity of insects. Many insects, including the whitefly  Endosymbiotic bacteria are prevalent within invertebrates. Some of them supply diet limited nutrients to their insect hosts ,2, some Bemisia tabaci is a destructive pest containing more than 40 cryptic species including two invasive populations, the Middle East-Asia Minor 1  and the Mediterranean  [B. tabaci MEAM1 and MED are well distributed across 31 Provinces and have caused significant economic losses since the mid-1990s and early 2000s, respectively. Whitefly is the major pest of many glasshouse vegetables, ornamentals and field crops in China [Whitefly biotype) ,10. Aparbiotype) . In Chinin China ,13. Variin China .B. tabaci, in addition to the primary symbiont Portiera, several genera of facultative symbionts, such as Arsenophonus, Cardinium, Hamiltonella, Hemipteriphilus, Rickettsia and Wolbachia have been recorded within various cryptic species of the B. tabaci complex [Rickettsia is abundant in many insects including whitefly pests in nature with stable and high frequencies of infection [B. tabaci, it can modify the adaptability of its whitefly hosts to their environment, such as enhancement in stress resistance to temperature [Rickettsia infection may vary between different B. tabaci cryptic species, or even within the same cryptic species but from different geographical populations. Some studies have revealed the impact of infection of Rickettsia on nutrition changes of B. tabaci [Rickettsia associated defense against fungi, parasitoids and insecticides into one study [Rickettsia-whitefly interaction and the development of subsequent management strategies.Regarding the endosymbionts of  complex ,18,19,20nfection ,22,23,24nfection ,26,27. Iperature , and altperature . However. tabaci . Howeverne study ,32,33,34Rickettsia on the biology of its whitefly host B. tabaci MEAM1, characterizing how the Rickettsia infection affects the biology of its host by altering its nutrition. Secondly, this study assessed the contribution of Rickettsia infection to the immunity of B. tabaci against entomopathogenic fungi, insecticides and parasitism. The study aimed to reveal the specific undescribed interactions of Rickettsia and B. tabaci and give further insight and understanding in the continual development of management strategies against B. tabaci.This study firstly investigated the impact of Gossypium hirsutum L. var. Lumianyan no. 32) were used in the current study to rear B. tabaci populations. Cotton seeds were sown in plastic pots (12 cm diameter × 15 cm height) containing a soil–sand mixture . Plants were reared in a glasshouse  in a pest- and pesticide-free environment and watered as required. Plants were used for experiments at their 6–8 expanded leaf stage.Cotton plants  grown at the training farm of South China Agricultural University (SCAU) in Guangzhou, China in 2016. Populations were then reared on cotton plants under standard laboratory conditions at 26 ± 1 °C, 60% relative humidity (RH) and a photoperiod of 16:8 h (L:D). Mitochondrial CO1 gene sequencing was used to check and maintain the purity of the B. tabaci populations [B. tabaci MEAM1 populations, Rickettsia positive (+R MEAM1) and Rickettsia negative (−R MEAM1) were set up and maintained according to the methods of Liu et al. [Rickettsia using the Rickettsia-specific primers  [B. tabaci MEAM1 until the B. tabaci MEAM1 glasshouse population was numerous enough for experimental trials. To ensure the purity of each population, approximately 100 adult whiteflies were selected and checked for the presence/absence of Rickettsia respectively every month.ulations . Two B. u et al. . In brieand Pgt) ,37. The Encarsia formosa was first collected from parasitized B. tabaci nymphs on tomato plants at Beijing Academy of Agriculture and Forestry Sciences in 2008. Subsequent offspring were reared on cotton plants infested by Rickettsia positive B. tabaci in a separate glasshouse.The parasitoid Akanthomyces attenuatus (previously Lecanicillium attenuatus) SCAUDCL53 strain (NCBI accession No. MH558279) was provided by the Engineering Research Center of Biocontrol, Ministry of Education in SCAU, which was initially collected from Fujian Province in 2016. The A. attenuatus was inoculated on a Potato Dextrose Agar (PDA) medium in 9 cm diameter Petri dishes and sealed with parafilm. Plates were incubated for eight days under the conditions outlined by Khan et al. [8, 1 × 107, 1 × 106, 1 × 105 and 1 × 104 conidia/mL.n et al. . FollowiRickettsia infection on the chemical resistance of B. tabaci MEAM1.The two insecticides, imidacloprid  and spirotetramat  were used to assess the effect of Rickettsia positive (+R) and Rickettsia negative (−R) B. tabaci adults (2–4 days old) were separately released into a leaf cage to allow egg-laying for five days. After five days, the number of eggs produced by the mating pairs were counted under a stereomicroscope (Zeiss SteREO Discovery). This experiment investigating fecundity was repeated in nine parallel replications for both +R and −R whiteflies.Healthy and fully expanded cotton leaves were marked on the cotton plants and covered with leaf cages . Five pairs of +R and − BR. tabaci adults (2–4 days old) were separately released into a leaf cage to allow egg-laying for 24 h. After 24 h the adult whiteflies were removed. The development and survival of the B. tabaci nymphs were then observed every 24 h. Following the emergence of adult whiteflies, sex identification was made under a stereomicroscope . The treatments were repeated in three parallel replications.In addition, 20–30 pairs of B. tabaci were determined by using 100 pairs of +R and − BR. tabaci adults respectively. A total of ten cotton leaves were caged to introduce whiteflies of each Rickettsia status for oviposition for 24 h. After the subsequent emergence of +R and −R whitefly adults (2 h old), specimens were collected in an Eppendorf tube, weighed 10 mg per sample and frozen in liquid nitrogen. Frozen samples were then ground and homogenized in PBS (pH 7.4). This crude homogenate was centrifuged at 10,000 rpm at 4 °C for 10 min and stored at −80 °C for further experimentation.The nutritional contents of +R and − BR. tabaci adults were measured according to the protocol provided by the manufacturer Beyotime Biotechnology. The absorbance was read in a Microplate Spectrophotometer . Bicinchoninic acid (BCA) was used to determine Cu+ at a wavelength of 562 nm [The protein contents of f 562 nm .The anthrone method was used to estimate the soluble sugar and glycogen content as outlined by Halhoul and Kleinberg  and treh+R and − BR. tabaci adults that were separately released into a leaf cage of different plants, respectively. After 48 h of egg-laying, the whiteflies were removed. Emerged nymphs were reared up to the 4th instar on the respective leaf. A total of one hundred nymphs were randomly selected per instar, with excess nymphs removed from the leaves via a fine camel hairbrush. Leaves with whitefly nymphs were plucked from the plants and immersed in the conidia suspension with concentrations mentioned above for 15s and then allowed to air-dry at room temperature as outlined in Cuthbertson et al. [A total of ten healthy cotton plants were taken, and three fully expanded cotton leaves were selected from each plant and covered with individual leaf cages. There were forty pairs of n et al. . Leaves +R and − BR. tabaci adults were separately released into the leaf cages. Following egg-laying for 24 h, the whiteflies were removed. Approximately 160 nymphs were randomly selected per instar, with excess nymphs removed using a fine camel hairbrush. Eight females of E. formosa (5 days old) were introduced into the leaf cage for 24 h before being removed. All the treatments were repeated five times. The parasitism rate, developmental duration, and emergence rate (%) of E. formosa were subsequently recorded.As outlined above, three healthy and expanded cotton leaves were selected from one cotton plant and covered with leaf cages. Fifty pairs of +R and − BR. tabaci. When the nymphs developed to second instar, 100 nymphs on one leaf were randomly selected and plucked from the plant, immersed entirely in the different pesticide concentrations of imidacloprid and spirotetramat for 10s, then dried at room temperature, again following method of Cuthbertson et al. [2O. Treated leaves were again placed in Petri dishes as outlined above. The data for survival of +R and − BR. tabaci nymphs were collected daily over the following five days.For the toxicity assay, seven geometrically progressive concentrations ranging from 3.125 mg/L, 6.25 mg/L, 12.5 mg/L, 25 mg/L, 50 mg/L, 100 mg/L and 200 mg/L of imidacloprid and spirotetramat were diluted in water. The dip impregnation method was used to determine the toxicity of imidacloprid and spirotetramat to second instar nymphs of n et al. . For con+R and − BR. tabaci adults. Plants and B. tabaci adults were obtained as outlined above. In a 20 mL tube, 0.5 mL of each concentration of imidacloprid and spirotetramat were added separately; the tubes were then physically shaken well to apply the pesticide to the wall of the tube evenly. Following 1 min of shaking, the remaining pesticide was discarded, and the tubes air-dried. Again, tubes washed in ddH2O were used as controls. A total of fifteen pairs of +R and − BR. tabaci adults were then placed into each tube, respectively, for 30 min before being released into the new leaf cages. All the treatment and control experiments were repeated in three parallel replications. Whitefly mortality was recorded after six hours.The residual method was used to determine the toxicity of imidacloprid and spirotetramat to t-test. The cumulative corrected mortality rate (%) of whiteflies caused by the entomopathogenic fungus and insecticides respectively were compared among treatments using two-way ANOVA. Tukey’s post-hoc test assessed the mean difference between and among the treatments at p < 0.05. Significant differences between treatments were estimated at p < 0.05, p < 0.01, and p < 0.001 significance levels. Graphical work was done via GraphPad Prism 5 .Statistical analyses were performed by using SAS software (v.8.01). Data were tested for normality (Shapiro–Wilks test) and homogeneity of variance (Levene’s test) before using parametric tests. Egg hatch ability, the mortality rate of whitefly, the parasitism rate and the emergence rate of parasitoids among different treatments were arcsine transformed wherever the data did not conform to a normal distribution. The biological data, nutrition contents and parasitism were compared among treatments using a + BR. tabaci are higher than that of − BR. tabaci, with the difference in fecundity being significant , soluble sugar  and trehalose  were all significantly elevated in the + BR. tabaci compared to that of −R individuals   d.A. attenuatus SCAUDCL53 isolate has high pathogenicity to all instar nymphs of +R and − BR. tabaci  is required for + BR. tabaci than R− B. tabaci to get 50% mortality. This indicates that the Rickettsia negative MEAM1 nymphs were more susceptible to A. attenuatus infection  of imidacloprid to + BR. tabaci second instar nymphs and adults were higher than those of − BR. tabaci second instar nymphs and adults  of spirotetramat to + BR. tabaci second instar nymphs and adults were higher than those of − BR. tabaci second instar nymphs and adults  or by inducing parthenogenesis [+ BR. tabaci produced more female offspring than the −R population. It has been reported that, Rickettsia can raise the fitness of infected female indirectly by manipulating host reproduction, either by killing male offspring as embryos  or by inducing parthenogenesis. The result of nucleotide sequencing of the 16S rRNA gene in Hagimori et al. [Neochrysocharis formosa (Westwood) is infected with a Rickettsia bacterium, which appears to be causative of the thelytokous parthenogenesis . This is the first finding of parthenogenesis-induction by Rickettsia among insects. Moreover, Neochrysocharis formosa (Westwood) (Hymenoptera: Eulophidae) males infected with Rickettsia produced by antibiotic treatment exhibited the same courtship behaviors as the arrhenotokous males, but at a lower rate, and did not produce fertilized progeny [Endosymbionts are also known as male-killers or to be female-biased  , among wogenesis . Our resi et al.  indicate progeny .Rickettsia infestation also affects the physiology of B. tabaci. Endosymbionts can promote insect fitness by contributing to nutrition [Buchnera aphidicola helps the pea aphid Acyrthosiphon pisum to overcome the nutritional deficiency of a plant-based diet. In our study, due to increased egg-laying, B. tabaci produces more energy reserves to support reproduction and other daily metabolic activities.Endosymbionts have been reported to affect the nutritional contents of insect hosts . For insutrition , they plutrition ,60. Lv eutrition  reportedRickettsia enhanced resistance of B. tabaci to imidacloprid, spirotetramat, it has been found that insecticide resistance was increased in hosts infected with some symbionts, but we speculate that the enhancement or decrease of insecticide resistance may depend on the endosymbiont-insecticide association, for example, Rickettsia increased the resistance of whiteflies to acetamiprid and spiromesifen, but not diafenthiuron [Rickettsia coexisting with another symbiont, Arsenophonus, was shown to confer insecticide resistance to acetamiprid in B. tabaci, but did not affect susceptibility to diafenthiuron [B. tabaci harbored more Portiera and Hamiltonella than the thiamethoxam-resistant population, whereas the thiamethoxam-resistant population of B. tabaci harbored more Rickettsia than the thiamethoxam-susceptible population.Endosymbionts also play an important role in the enhancement or detraction of the defense system of the pest host against different management strategies, for example, insecticides , entomopnthiuron ; Rickettnthiuron . In addinthiuron  reportedDrosophila melanogaster infected with Wolbachia were more resistant to the fungus Beauveria bassiana (an insect pathogen) than uninfected females; infected females also exhibited changes in oviposition substrate preference. Hendry et al. [Rickettsia infected B. tabaci exhibited a decreased mortality rate due to the entomopathogenic bacteria Pseudomonas syringae compared to Rickettsia negative B. tabaci. Our results revealed that R+ B. tabaci individuals showed a significant mortality reduction when A. attenuates was applied, and to each specific stage of B. tabaci, a higher concentration was necessary to manage R+ individuals compared to the −R individuals. Endosymbionts also protect their host against parasitoids. The endosymbiont Buchnera aphidicola protects Acyrthosiphon pisum against the hymenopteran parasitoid Aphidius ervi by causing high mortality in developing parasitoid larvae [Regiella insecticola was also reported to protect its aphid hosts against the parasitoids Aphidius colmani and Aphidius asychis [Hamiltonella did not reduce the susceptibility of aphid to two species of parasitoids (A. ervi and Ephedrus plagiator) and did not affect the fitness of wasps that successfully completed development, but it may reduce the risk of parasitism in its aphid hosts by making them less attractive to searching parasitoids [We reached a consensus currently that non-chemical control measures became the alternative and best choice for the management of insect pests, due to increasing resistance to chemical pesticides . Some sty et al.  also repd larvae . Regiell asychis ,72. Hamiasitoids . All theRickettsia infestation benefits B. tabaci by aiding in enhanced reproduction, higher survival and faster development by improving its host’s nutritional composition. Rickettsia infection improved its host’s fitness by enhancing its resistance towards insecticides (imidacloprid and spirotetramat), entomopathogenic fungus (A. attenuatus) and parasitoid (E. formosa). This study is useful in understanding the role of endosymbionts within an insect host. Endosymbionts can affect the fitness of their host and they play important roles in protecting their host from environmental stress, such as natural enemies and toxins. However, there are still several unanswered questions that need to be addressed: (1) bacterial endosymbionts are common in insects, so potentially symbiont-mediated protection exists in many insect species, thus, how common is this phenomenon in nature and is this effect the same in different insects? (2) Endosymbionts can enhance their resistance towards insecticides, entomopathogenic fungi and parasitoids, but the breadth of mechanisms that underlie how the symbionts provide protection is still largely unknown. (3) How should we adjust subsequent pest control strategies in response to these characteristics of symbiotic bacteria? All these aspects should be further investigated in the future, to support development of novel strategies of pest biological control.In conclusion, results from this study and those of previous studies suggest that


After transcriptomic analysis, quantitative real-time PCR, and haplotype analysis, we found 13 genes within this reliable region as important candidate genes. Our study results will be beneficial to molecular marker-assisted selection of rice lines with high outcrossing rate, thereby improving the efficiency of hybrid seed production.The commercialization of hybrid rice has greatly contributed to the increase in rice yield, with the improvement of its seed production capacity having played an important role. The stigma exsertion rate (SER) is a key factor for improving the outcrossing of the sterile line and the hybrid rice seed production. We used the Zhenshan 97B × IRAT109 recombinant inbred population comprising 163 lines and a natural population of 138 accessions to decipher the genetic foundation of SER over 2 years in three environments. Additionally, we detected eight QTLs for SER on chromosomes 1, 2, and 8 via linkage mapping. We also identified seven and 19 significant associations for SER using genome-wide association study in 2016 and 2017, respectively. Interestingly, we located two lead SNPs (sf0803343504 and sf083344610) on chromosome 8 in the  Oryza sativa L.) as a primary source of nutrition, with the demand set to increase with the growing population. To match the current population growth rate, rice production needs to increase by at least 40 percent by 2030 , demarcating them into precise regions on chromosomes 11 and 7, respectively. Another QTL (qSER7) was fine-mapped to a ~28 kb region on chromosome 7  and IRAT109 (low SER japonica rice) . Collection 1, which was used for traditional linkage-based QTL mapping, encompassed 163 FBoth rice collections were field-grown using conventional rice cultivation methods and staged sowing at the Shanghai Agrobiological Gene Center field stations in Hainan and Shanghai, China. The field sites were arranged in triplicates based on a randomized block design. Rice was sown seven plants per row in five rows, with a spacing of 18 x 16 cm between and within rows. Collection 1 was analyzed during the summer of 2016 in Shanghai, while in spring of 2017 and 2018 in Hainan. Collection 2 was analyzed during the summer of 2016 in Shanghai and spring 2017 in Hainan.Eight panicles from each rice line were sampled 5–7 days post spikelet flowering. For analysis, we subdivided SER into three separate traits: total stigma exsertion rate (TSE), single stigma exsertion rate (SSE), and dual stigma exsertion rate (DSE). The TSE, SSE, and DSE were determined as a percentage of rice spikelets displaying these traits.https://www.ncbi.nlm.nih.gov/Traces/index.html?view=run_browser&acc=SRR1239601&display=metadata and http://www.ncbi.nlm.nih.gov/bioproject/PRJNA260762. Clean reads were used to identify single nucleotide polymorphisms (SNPs) using a combination of BCFtools . The local LD-based interval of reliable significant SNPs was considered the candidate region, where the LD between nearly SNPs and lead SNP  reduced to r2 = 0.6  was utilized to extract total RNA. Using SeqPrep (https://github.com/najoshi/sickle), the single reads were created using overlapping paired reads, with the adaptors being stripped. The library was constructed according to the TruSeq® RNA Sample Preparation v2 Guide (Illumina) using qualified RNA. Cufflinks and Tophat were utilized to map clean data to the Nipponbare (MSU6.0) reference genome (http://rice.plantbiology.msu.edu/), allowing two or less alignment mismatches  method was utilized to determine the gene expression levels by using the Cuffdiff software  of Zhenshan 97B and IRAT109 at the pre-heading stage using TRNzol-A+ Total RNA Reagent . The qRT-PCR method was described by a previous study  and Collection 2 across 3 years are shown in qTSE8, flanked by RM38 and RM25, had the largest additive effect and explained 10.01% of the phenotypic variation. Both alleles, i.e., qTSE1 and qTSE8 were inherited from Zhenshan 97B, whereas the alleles qTSE2 was derived from IRAT109. For SSE, we found three QTLs on chromosomes 1, 2 and 8  derived from the parent Zhenshan 97B, were discovered on chromosomes 1 and 8 , we found two, one, and four significant associations for TSE, SSE, and DSE, respectively , with a minority located within coding sequences (13.2%). Utilizing the phenotypic information of 138 Collection 2 accessions, a GWAS was performed using GAPIT (MAF > 5%), with -log(P) ≥ 6.0 as the threshold at a significance level of ectively . We idenn 2017HN . The assn 2017HN .qTSE8 on chromosome 8  was associated with TSE , and found there were 20 genes within this region, showing significantly different gene expression levels between Zhenshan 97B and IRAT109 based the transcriptome data  exhibited no significant differences regarding the SER between different haplotypes. Two haplotypes were found for LOC_Os08g05530, LOC_Os08g05690, LOC_Os08g06610, and LOC_Os08g06800. Three haplotypes were found for LOC_Os08g05670 and LOC_Os08g06130. The other genes were divided into four or five haplotypes. Combined with these analysis results, we finally obtained 13 rice SER-related genes in the candidate interval, which should be focused on in subsequent research.According to the colocalization results, ome data . Further IRAT109 . Accordi IRAT109 . The FPK IRAT109 . The exp IRAT109 . The othOne crucial trait for the improvement of hybrid rice seed production is SER, a trait linked to the female parent. Research on SER indicates that stigma exsertion is not only regulated by QTLs, but also potentially affected by environmental conditions. Although multiple SER-associated QTLs have been characterized to date, few were placed within a 500 kb interval on the chromosomes . Previous research indicated that the GS3 gene controled stigma exsertion  and Open Funding Project of the State Key Laboratory of Biocatalysis and Enzyme Engineering (SKLBEE2021023).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.


Bemisia tabaci MED is an invasive pest that had caused considerable economic damage in the past decades. Its successful colonization is closely related to heat-shock proteins (HSPs), which are related to heat resistance. In this study, 33 BtaHsps were identified based on the sequenced genome of B. tabaci MED belonging to six HSP families, among which 22 BtaHsps were newly identified. Analysis of the secondary structure and evolutionary relationship showed that they were all closely related. In addition, BtaHsp90A3 of the HSP90 family was screened by analyzing the expression level changes of these genes under 42 °C heat shock and RNAi was performed on the BtaHsp90A3. The results showed that the silencing of BtaHsp90A3 is closely related to the heat resistance of B. tabaci MED. Taken together, this study conducted an in-depth identification of BtaHsps that clarifies their evolutionary relationships and their response to thermal stress in B. tabaci MED.Bemisia tabaci MED, an invasive whitefly species with worldwide distribution, plays an important role in its ecological adaptation during the invasion process. Heat-shock proteins (HSPs) are closely related to heat resistance. In this study, 33 Hsps (BtaHsps) were identified based on sequenced genome of B. tabaci MED belonging to six HSP families, among which 22 Hsps were newly identified. The secondary structures of a further 22 BtaHsps were also predicted. The results of RT-qPCR showed that heat shock could affect the expression of 14 of the 22 Hsps newly identified in this study. Among them, the expression level of six Hsps increased under 42 °C treatment. As the unstudied gene, BtaHsp90A3 had the highest increase rate. Therefore, BtaHsp90A3 was chosen for the RNAi test, and silencing BtaHsp90A3 by RNAi decreased the survival rate of adult B. tabaci at 42 °C. The results indicated that only a few Hsps were involved in the thermal tolerance of host whitefly although many Hsps would response under heat stress. This study conducted a more in-depth and comprehensive identification that demonstrates the evolutionary relationship of BtaHsps and illustrates the response of BtaHsps under the influence of thermal stress in B. tabaci MED.The thermal tolerance of  In many insects, heat-shock proteins (HSPs) can overexpress in response to a variety of environmental stresses such as heat , cold 22, dehydrBemisia tabaci (Gennadius) species complex, transmits more than 320 plant viruses [B. tabaci MED has invaded many countries, including China, and has caused considerable economic damage to many important crops [B. tabaci MED in many locations [B. tabaci MED [B. tabaci MED is more tolerant to short temperature stress than the indigenous B. tabaci ZHJ1. Meanwhile, the Hsp expression of B. tabaci MED was higher than in the indigenous species under maximal temperature, and the onset and maximal temperature induction of Hsp expression was generally 2–4 °C higher than in the indigenous species ZHJ1 [Hsps and the distribution changes of B. tabaci MED under global climate warming. In addition, Hsp expression of viruliferous B. tabaci was more easily upregulated by temperature stress [Hsps based on the genome of B. tabaci MEAM1 [Hsp70s and three sHsps in B. tabaci MED [B. tabaci MED still remains poorly understood.The sweet potato whitefly,  viruses . One memnt crops . It has ocations ,18,19. Ties ZHJ1 , which ie stress . Previouci MEAM1 , and alsbaci MED . HoweverHsps in B. tabaci MED and the responses of Hsps to temperature stresses, 22 Hsps were identified from B. tabaci, including 11 HSP70 genes, four HSP90 genes, one HSP60 gene, one HSP100 gene, four HSP40 genes, and one sHSP gene. By constructing a phylogenetic tree with all these B. tabaci MED Hsps and Hsps from outgroup insects, the phylogenetic relationships of Hsps were explored. The expression pattern of BtaHsps was examined by RT-qPCR by determining the expression level of BtaHsps under treatment at 42 °C. In addition, the functions of HSPs were further clarified by silencing the Hsps whose expression increased under heat treatment. The present results could improve understanding of the mechanisms of thermotolerance in B. tabaci at the molecular level.To reveal the evolutionary characteristics of B. tabaci population in this study was collected from Lingshui, Hainan, China in 2017, and was determined as cryptic species MED using the mtDNA COI gene (GenBank accession no. GQ371165) [Nicotiana tabacum L.) (breed: NC89 cultivar) in a thermostatic chamber at 27 ± 1 °C with a 16L:8D photoperiod and 60% relative humidity (RH). Before this experiment, the B. tabaci MED population had been reared in the laboratory for more than 40 generations.The Q371165) . The whiB. tabaci MED, based on the third generation sequencing technology, was generated with the PacBio Sequel Sequencing technology platform . Three hundred male and female adult pairs of the B. tabaci MED population collected from Lingshui, Hainan, China in 2017 were used as the sequencing samples. Sequenced genes with Hsp functions were selected as candidate genes based on the genome annotation library. Afterwards, sequences of all candidate genes were subjected to the National Center for Biotechnology Information (NCBI) BlastP and BlastN and Conserved Domain Database [https://web.expasy.org/compute_pi/ (accessed on 20 October 2021)) [Hsps in this study, and subcellular localization was predicted by CELLOv2.5 (http://cello.life.nctu.edu.tw/ (accessed on 20 October 2021)) [The genome of Database  to screer 2021))  was usedr 2021)) .Hsps identified and named in previous studies of B. tabaci. The sequences of these genes were also obtained in these studies [Hsp70, Hsp90, Hsp60, and sHsp families of Athalia rosae, Drosophila ananassae, Nilaparvata lugens, Plutella xylostella, and Tribolium castaneum [B. tabaci HSP families, BlastP in NCBI was used to find gene sequences of Hsp40, Hsp100, and other families (except for the HSP genes that had been found previously) [A. rosae, D. ananassae, and N. lugens. Then, protein sequences of candidate Hsps in this study and previously studied Hsps were aligned by Muscle [Hsps in MEGA7 [Hsps screened were classified and further named according to their molecular weight [Hsc70 and Hsp70 according to constitutive and inducible types, respectively [There were 31  studies ,23,24. Tviously) ,23,24. Ty Muscle  of MEGA7in MEGA7  with ther weight ,31. The r weight . The genectively . The HSPectively . Other fHsps were detected by Multiple Em for Motif Elicitation (MEME) an online program [http://gsds.gao−lab.org/ (accessed on 23 October 2021)) [B. tabaci genome. In addition, Clustalw (Multiple Sequence Alignment—CLUSTALW (genome.jp) (accessed on 23 October 2021)), ExPASy (https://swissmodel.expasy.org/interactive (accessed on 23 October 2021)) [https://espript.ibcp.fr/ESPript/cgi-bin/ESPript.cgi (accessed on 23 October 2021)) were used to predict the secondary structures (α-helixs and β-sheets) of candidate genes. ALN format file and PDB format file were separately obtained using Clustalw and ExPASy, respectively, and then, the two files of each superfamily were separately put into ESPript.The conserved motifs of 22  program  with the program . Comparir 2021))  was usedr 2021)) , and ESPFor each experiment replicate, 30 female adults were collected into one ventilated plastic pipette, and were maintained at 42 °C for 3.5 h in a constant-temperature incubator. Thirty adults exposed to 27 °C were included as a control replicate. Each treatment included four biological replicates. Once the experiment finished, treated adults were frozen in liquid nitrogen and stored at −80 °C. Then, the total RNA of 20 surviving adults was extracted for each experiment replicate, using TRIzol Reagent  according to the manufacturer’s protocol. The concentration and purity of extracted RNA (A260/280 and A260/230) were detected by using NanoDrop. RNA samples were stored at −80 °C until needed. PrimeScript RT reagent Kit with gDNA Eraser   was used to reverse transcribe RNA into cDNA, and RT primer mix of random 6-mers and oligo-dT primer was used to uniformly synthesize all types of cDNA in the sample.−1) to obtain the melting curves by promoting denaturation of the double-stranded DNA. The gene-specific primers were designed by primer premier 6, and all primers are listed in EF-1α  [β-actin  [The obtained cDNA concentrate was then diluted 30 times and used as a template for RT-qPCR. RT-qPCR reaction system (20 μL): 10 μL TBGreen , 7.2μL DEPC water, 0.8 μL primer (10 μM), 2 μL cDNA (30-fold dilution). The RT-qPCR experiment was performed on the JENA qTOWER 2.2 system . The reaction procedure was as follows: 95 °C for 30 s, followed by 40 cycles (95 °C for 10 s and 60 °C for 30 s). After the cycling procedure, the temperature was increased from 60 to 95 °C (0.6 °C sACCGTCC)  and whitCTGCATT)  were useT7 RNAi Transcription Kit  was used to synthesize double-stranded RNA (dsRNA) with specific primers. Adults were fed with 20% sucrose with 500 ng/μL dsRNA dilution. A sucrose diet containing 500 ng/μL dsHSP and dsGFP was used for the treatment group and control group, respectively. First, 150 adults were fed on a 20% sucrose diet with dsRNA for 2 days, then 30 adults per replicate were randomly selected for RT-qPCR to detect the interference efficiency, and 80 adults were subjected to 42 °C treatment for 2 h. The same approaches were performed on the negative control. Each treatment was assayed in three replicates. The mortality of adults was counted after high-temperature treatment. After recovery at 25 °C for 1 h, the survival number of adults was counted to ensure that there was no false death among these individuals.−ΔΔCt [Relative expression of double parameters was measured and geometrically averaged , and RT-−ΔΔCt . The datHsps (BtaHsps) were identified based on sequenced genome of B. tabaci MED  and verified by BlastP, BlastN, and CDD search. Of the 33 Hsps, 22 were newly identified through a method of establishing an unrooted phylogenetic tree and comparing their common motif regions, molecular weight, and other details. Subsequently the newly founded 22 HSP genes were classified into six superfamilies, including sHSP, HSP40, HSP60, HSP70, HSP90, and HSP100, including one sHSP gene, four HSP40 genes, one HSP60 gene, 11 HSP70 genes, four HSP90 genes, and one HSP100 gene. The B. tabaci HSP genes were named as BtaHSP; the family name was behind it, and then the individual numbers were signed at the end. The detailed information on the Hsp such as CDS, molecular weight, isoelectric point, and subcellular localization is shown in Thirty three Hsps of B. tabaci and other outgroup insects, HSP genes of different insects were put together for unrooted phylogenetic trees to further identify our classification result. As shown in sHsp, Hsp40, Hsp60, Hsp70, Hsp90, and Hsp100, and they were clustered together to include the HSP family. Since the sHSP family gene sequence is short and the difference is too large compared with other HSP family genes, the phylogenetic tree of sHsp was constructed alone  to 12 (BtaHsc70-2) introns. In addition, there were also great differences in genetic structure among members of the HSP90 family and HSP40 family; 1, 14, 2, and 4 introns were contained in BtaHsp90A1, BtaHsp90A2, BtaHsp90A3, and BtaHsp90A4, respectively, and 3, 2, 2, and 8 introns were contained in BtaHsp40-1, BtaHsp40-2, BtaHsp40-3, and BtaHsp40-4, respectively. The Gene Structure Display Server (GSDS) was used to portray the gene structure information and this was compared based on the phylogenetic classification. As shown in BtaHSP genes. Motifs are shown in The motif and secondary structure were analyzed to obtain the BtaHSP superfamily genes’ structural diversity. Firstly, MEME was used to search 20 motifs in each HSP family of 22 candidate BtasHsp, BtaHsp40, BtaHsp60, BtaHsp70, and BtaHsp90 families is displayed in α-crystalline domain with chaperone function located in the N-terminal, one in the C-terminal region, and six β-sheet sandwich structures in each member of B. tabaci sHSP family whole region. HSP40s include the C-terminal Zn-finger domain, one highly conserved J domain on N-terminal, and substrate recognition domain on C-terminal. Among them, the J domain contains four α-helices, whose ring regions contain highly conserved histidine, proline, and aspartic acid residues. There are two GroEL-like equatorial domains and one GroEL-like apical domain in the BtaHSP60. The HSP70 family has two characteristic domains, one is an ATPase functional domain located at N-terminal, and the other is the C-terminal polypeptide-binding functional domain. The N-terminal ATPase domain consists of two subdomains connected by two α-helices with a gap between them. These two subdomains are a tight structure of a β-sandwich containing eight β-folded chains. The C terminal is an α-helical relaxation structure. Like HSP70 chaperones, BtaHsp105/110s have an N-terminal nucleotide-binding domain (NBD) and a C-terminal substrate-binding domain (SBD). The BtaHsp90s contained a histidine-kinase-like adenosine triphosphatase (ATPase) domain and chaperone motifs in the N-terminal domain and the C-terminal domain, respectively. Furthermore, in order to compare the secondary structure more accurately, four gene families of 29 genes obtained by predecessors were added to each gene family obtained in this study for analysis and comparison. The secondary structure of B. tabaci HSP genes including 29 HSP genes identified by predecessors and 22 HSP genes obtained in this study . In particular, the expression of BtaHsp70-1 had the highest increase rate , and the expression of BtaHsp90A3 had the second highest increase rate .The investigation of the expression changes of different HSP genes at high temperature was revealed by RT-qPCR of all the is study . AlthougBtaHsp90A3 was selected as a candidate gene for RNA interference to further determine the role of BtaHsp in B. tabaci high-temperature stress. Changes in gene expression showed that BtaHsp90A3 could be the gene that responded positively to heat stress, which implies it has a vital function. The BtaHsp90A3 expression level of B. tabaci fed dsBtaHsp90A3 (0.54 ± 0.049) was significantly lower than that of those fed dsgfp (1.00 ± 0.025)  (B. tabaci fed on dsBtaHsp90A3 (70.67% ± 5.25%) was significantly higher than that of those fed on dsgfp (14.93% ± 1.17%)  (In this study  t-test) A. Furthe t-test) B.B. tabaci MEAM1 genome [B. tabaci MED samples [Hsps reported by Bai et al. (2021) [B. tabaci MED genome , but there were also 22 HSP genes of our genome that were different from these 31 genes. The main differences may be associated with the different source of the genome.Previously, 26 HSP superfamily genes have been identified based on the 1 genome  and five samples ,24. The . (2021)  was not BtaHsps were screened by genome annotation library and comparative genomics. The 22 Hsp genes encoding six insect HSP families were identified in the B. tabaci genome by integrated bioinformatics methods. These results indicate that the number of HSP genes is extended in B. tabaci. The results show that Hsp70 is the largest clade of B. tabaci Hsp, which is consistent with the previous reports that the HSP70 family is one of the main and most abundant HSP families [Hsps of three species, A. rosae, D. ananassae, and N. lugens, as the outgroup of the phylogenetic tree and used B. tabaci Hsp40, Hsp100, Hsp67B2, and Hsp105/110 for genomic gene blast. Based on the phylogenetic tree, Hsp105/110 and Hsp67B2 were found to cluster with HSP70 family genes, which was consistent with Hsp105/110 belonging to the divergent subgroup of the HSP70 family [Hsp67B2 belongs to the HSP70 family. Moreover, the results indicate that Hsp40 in large numbers exists in the above-mentioned three insect species, while the other three HSP genes are rare and the number is small. This may be caused by gene loss events in the evolution of different species [In this study, 22 newly found families . In addi0 family , suggest species . This ph species  and that species . B. tabaci has already occurred.In general, HSPs from the same family have a relatively high structural identity. The prediction results of the secondary structure showed that HSPs in the same family have similar motifs. Different types of HSPs have different domains, which play important roles in their function. As the earliest family to extend from the evolutionary branch , the HSPWangBtHsp70-1 and WangBtHsp70-3 are isolated from other Hsp70 in the phylogenetic tree due to the absence of any known specific motif in the C-terminal [BtaHsp105/110, BtaHsp67B2, and BtaHsp70-7 were also found to be isolated from other HSP70 due to the absence of any known specific motifs at the C-terminus. HSP40 consists of a J domain, G/F domain, zinc-finger domain, and hydroxyl terminal region. HSP40 forms a heterogeneous family whose members have at least a conserved J-domain [B. tabaci HSP superfamily. From the above information, we can propose that the differentiation and conservation of gene structure are closely related to the evolution and expansion of the B. tabaci HSP gene family.HSP70 contains one highly conserved 44 kDa ATPase domain at the N-terminal and one 25 kDa domain at the C-terminal . Furtherterminal . When obJ-domain ,49. The J-domain ,51. The J-domain . HSP40 wJ-domain . Taken tB. tabaci under heat stress by RT-qPCR. HSP70 is a highly conserved protein that acts as a molecular chaperone, and it is a strong indicator of the response of B. tabaci to heat shock [Hsp70 and Hsp40 are highly conserved, and have high homology in different species [B. tabaci. Our results showed that most HSP40 genes of B. tabaci were induced by heat stress. Although the specific regulatory role of B. tabaci HSP40 on HSP70 is still unclear, in the current study most HSP40s and HSP70 was induced by high temperature. However, members of the Hsc70 family have been reported not to respond to heat stress [Hsc70 in the current study.Previous studies have demonstrated that HSPs contribute to temperature tolerance, and our study obtained 22 BtaHSPs. Therefore, we obtained the expression pattern of the HSP gene superfamily of at shock ,53. The at shock . As a heat shock . It is s species , so sucht stress , which iBtaHsp70-1 was highest among the candidate genes . The function of BtaHsp70-1 had been well-studied previously [BtaHsp90A3  was chosen for the RNA interference test to further study the role of BtaHSP in B. tabaci under high-temperature stress. After silencing of BtaHsp90A3, the heat tolerance of B. tabaci decreased with the decrease of the expression level of the gene, which indicated that BtaHsp90A3 contributes to temperature tolerance.The expression of eviously . TherefoB. tabaci MED have been reported. Therefore, this study provides a new idea for the prevention and control of B. tabaci MED by targeting the RNAi of the HSP90 family gene.As the most conserved gene in the HSP family, HSP70 has been extensively studied . StudiesHsps identified in this study were verified by phylogenetic tree construction and secondary structure prediction analysis. Furthermore, we have confirmed that the secondary structure of the genes is closely related to their evolutionary relationships. In this study, we linked the response of these genes, especially BtaHsp90A3 of the HSP90 family, to heat stress. Therefore, it can be inferred that searching for genes related to Hsp70 function from the above-mentioned members of the HSP family is feasible. It can provide new ideas about the regulation mechanism of HSP gene expression in B. tabaci.The 22


Aspergillus fumigatus, opening up for the first time the possibility of using techniques reliant on sexual crossing for genetic analysis. The present study was undertaken to evaluate whether the technique ‘bulk segregant analysis’ (BSA), which involves detection of differences between pools of progeny varying in a particular trait, could be applied in conjunction with next-generation sequencing to investigate the underlying basis of monogenic traits in A. fumigatus. Resistance to the azole antifungal itraconazole was chosen as a model, with a dedicated bioinformatic pipeline developed to allow identification of SNPs that differed between the resistant progeny pool and resistant parent compared to the sensitive progeny pool and parent. A clinical isolate exhibiting monogenic resistance to itraconazole of unknown basis was crossed to a sensitive parent and F1 progeny used in BSA. In addition, the use of backcrossing and increasing the number in progeny pools was evaluated as ways to enhance the efficiency of BSA. Use of F1 pools of 40 progeny led to the identification of 123 candidate genes with SNPs distributed over several contigs when aligned to an A1163 reference genome. Successive rounds of backcrossing enhanced the ability to identify specific genes and a genomic region, with BSA of progeny (using 40 per pool) from a third backcross identifying 46 genes with SNPs, and BSA of progeny from a sixth backcross identifying 20 genes with SNPs in a single 292 kb region of the genome. The use of an increased number of 80 progeny per pool also increased the resolution of BSA, with 29 genes demonstrating SNPs between the different sensitive and resistant groupings detected using progeny from just the second backcross with the majority of variants located on the same 292 kb region. Further bioinformatic analysis of the 292 kb region identified the presence of a cyp51A gene variant resulting in a methionine to lysine (M220K) change in the CYP51A protein, which was concluded to be the causal basis of the observed resistance to itraconazole. The future use of BSA in genetic analysis of A. fumigatus is discussed.A sexual cycle was described in 2009 for the opportunistic fungal pathogen  Aspergillus fumigatus is a ubiquitous fungus in the environment where it is primarily saprotrophic in nature, breaking down organic matter found in soil and compost. However, as a result of the inhalation and growth of airborne conidia produced by the fungus, A. fumigatus can also act as an opportunistic pathogen in immunocompromised individuals where infection can lead to mortality rates as high as 90% , the echinocandins (targeting chitin synthesis), and the azoles (targeting membrane biosynthesis). All these therapeutics have fungal-specific cellular targets   showed that approximately 50% of resistant isolates had no mutation in cyp51A or its promoter  e.g. . Althougpromoter . Indeed,f cyp51A , mutatiol levels , and altl levels . Howeverl levels . It remaA. fumigatus following the identification of a heterothallic (obligate outbreeding) sexual cycle by MAT1-1 or MAT1-2. This has meant that several experimental opportunities are now possible. First, it means that where a particular phenotypic trait, such as azole resistance, has been identified in an isolate of A. fumigatus, it is possible to determine the Mendelian basis of this phenotype by setting up sexual crosses with a suitable partner (lacking the phenotype) and analysing the progeny for the phenotype. Thus, it is possible to determine if the trait observed is monogenic or polygenic in nature from the segregation patterns in the sexual progeny  segregant analysis (BSA) can be employed to identify the region of the genome in which a novel mutation(s) is contained and thereby identify candidate genes of interest  that had been shown to exhibit monogenic resistance to itraconazole in previous crossing work, which was both stable and of a relatively high level, and did not exhibit any known mutation in the cyp51A gene ; and 47-51 , a highly fertile azole sensitive isolate from air sampling in Dublin, Ireland  azole sensitive parental isolate. To ensure crossing success, matings with at least four different MAT1-2 azole resistant progeny were set up with the 47-51 parent at each backcross .For comprehensive details of methods used for sexual crossing, ascospore isolation and mating-type analysis of progeny please see the protocols paper of AT assay . Serial A. fumigatus isolates and subsequent progeny were determined using the ETEST® method in accordance with manufacturer’s instructions (Biomerieux). Spore suspensions of each isolate to be tested were made and adjusted to a concentration of 1x106 spores ml-1 in 0.05% Tween 80 (Sigma-Aldrich) and spread using a cotton swab onto RPMI 1640 (Sigma-Aldrich) supplemented with 2% glucose (Fischer Scientific) and adjusted to a final pH of 7.0 with morpholinepropanesulphonic acid (MOPS) buffer (Sigma-Aldrich). Once dried, an itraconazole ETEST strip was placed at the center of the Petri dish and incubated at 35 °C for 48 h. The minimum inhibitory concentration (MIC) was determined as the maximum point on the ETEST strip that the fungal culture grew to.Azole sensitivity or resistance of parental -1.To prepare for each round of bulk segregant analysis, progeny were separated into two discrete groups (pools): the first showing the resistance profile of interest  and the second showing itraconazole sensitivity . Separate rounds of BSA were undertaken with progeny from the initial sexual cross (i.e. F1 progeny from 47-51 x 47-308) and the 3rd backcross and the 6th backcross , with 40 resistant progeny and 40 sensitive progeny being isolated and used for subsequent DNA pool analysis. DNA was extracted using a Qiagen Plant DNA extraction kit following the manufacturer’s instructions for adaptation for filamentous fungi (Qiagen). DNA quality and quantity for genome sequencing was then assessed by gel electrophoresis, Nanodrop and Qubit methodologies (Thermo Fisher), respectively In addition, BSA was later undertaken with progeny from the 2nd backcross (BC2), but this time 80 resistant and 80 sensitive progeny were isolated and used for subsequent DNA pool analysis. For each round of BSA, DNA was extracted from progeny and DNA pooled together based on resistance or sensitivity phenotype. For each DNA pool, 2.5 µl  or 1.25 µl (for BC2) of each appropriate progeny DNA sample was added together to form a final pool of 100 µl at a concentration of 50 ng µlWhole genome sequencing was performed by DeepSeq at the Queen’s Medical Centre . Libraries were prepared from 100 ng to 1 ug of input DNA using the NEBNext Ultra kit  following the manufacturer’s standard protocol. Libraries were then pooled and sequenced using the MiSeq instrument with the MiSeq Reagent Kit v3 (600 cycles)  to generate 2 x 300bp paired end reads, with three replicates used per parent or progeny pool and a target of ca. 120-fold sequencing depth. As indicated above, different rounds of BSA were undertaken after one round of sexual crossing (F1) and then after the 2nd, 3rd and 6th round of backcrossing . Rules were applied to the arising sequence data following the principles of BSA i.e. that any marker linked to the phenotype of interest should only be present in the resistant pool and resistant parent, and be absent from the sensitive pool and the sensitive parent. Any marker should also be absent from the (sensitive) wild-type reference genomes  and JGI  databases were used to align sequence reads. However, due to only minor differences observed between sequence data from both reference databases, for the subsequent BSA of progeny from the 2nd backcross and 6th backcross, only the JGI A1163 reference database was used for alignment (https://mycocosm.jgi.doe.gov/Aspfu_A1163_1/Aspfu_A1163_1.home.html).For the first two rounds of BSA, using progeny from the F1 and the 3rd backcross, reference genomes of A. fumigatus genomes independently, and subsequently calling SNP variants from the reference genomes. Third, the variant information for each group of three sample replicates was compared, and the homozygous variants common between the replicates were determined. This was achieved by processing the variant VCF files using the program BedTools . Raw reads were then either trimmed for adapters using Scythe  and then trimmed again for quality using Sickle  and separately to the Af293 genome sequence from Genbank (NCBI BioProject: PRJNA14003) using BWA-MEM .Reads were aligned to the genome sequences of https://gatk.broadinstitute.org/hc/en-us; http://github.com/samtools/bcftools; https://vcftools.github.io; http://vcftools.sourceforge.net/perl_module.html#vcf-isec; SNPs and InDels (insertions & deletions) were called using the GATK  tool GATK HaplotypeCaller , were then processed with SnpEff  and then with 80 progeny (BC2). For the initial BSA involving pools from the F1 and BC3 progeny the bioinformatic analysis used both the NCBI and JGI reference genomes for A. fumigatus  whereas later BC6 and BC2 BSA bioinformatic analyses used only the JGI A1163 reference database given that that only minor differences were observed between results drawing on sequence data from either reference database. Parental isolate 47-51 exhibited 48,882 SNP variants, whilst parental isolate 47-308 exhibited 9,554 variants, from the A1163 reference genome, respectively, with the two parents themselves differing by at least 39,814 SNPs based on alignment to the A1163 reference genome  of >32 mg Lhenotype Figure 1Bioinformatic analysis of genomic data from the 40 pooled resistant progeny in comparison to the sensitive parent, 40 pooled sensitive progeny and JGI reference genome A1163 revealed 123 genes demonstrating SNPs between the different sensitive and resistant groupings Table 1.rd and 6th backcrosses. Bioinformatic analysis of genomic data from the resistant progeny from the 3rd backcross (BC3) in comparison to the sensitive parent, sensitive progeny and the reference A1163 genome, revealed 46 genes demonstrating SNPs between the different sensitive and resistant groupings (th backcross (BC6) in comparison to the sensitive parent, sensitive progeny and the reference A1163 genome revealed 22 genes demonstrating SNPs between the different sensitive and resistant groupings  but this time pooling 80 resistant and 80 sensitive progeny. Bioinformatic analysis of genomic data from the resistant progeny in comparison to the sensitive parent, sensitive progeny and the reference A1163 genome, revealed 29 genes demonstrating SNPs between the different sensitive and resistant groupings  and the 2nd backcross  both identified a 292 kb region of the genome on contig DS_499598 containing 20 linked genes which showed consistent SNP variants between the resistant progeny compared to the sensitive progeny, sensitive parent and sensitive A1163 genome reference strain. This list of candidate genes with a role in resistance to itraconazole included genes with known functions based on BLAST homology and also a series of hypothetical genes of unknown function (cyp51A gene (AFUB_063960), which was present in the central third of the region (ca. 188 kb into the 292 kb region), and which contained a T to A variant that would result in an amino acid change of methionine to lysine (M220K) in the translated CYP51A protein. An M220K substitution in cyp51a has already been described by cyp51A greatly reduced susceptibility to all triazole antifungals. These substitutions resulted in A. fumigatus isolates with resistance to itraconazole with MICs >8 mg/L  increasing the efficiency of the BSA process as will now be described.The discovery that ulations , has impLactuca sativa  which were consistently present in the pool of resistant progeny and the resistant parent but absent from the pool of sensitive progeny and the sensitive parent . The useA. fumigatus  and sensitive (47-51) parents. It was hoped that this might allow sufficient resolution of a genomic region of interest that contained an SNP(s) responsible for the resistance phenotype. However, SNPs were detected over 8-11 contigs/chromosomes and between 123-150 candidate genes were identified  i.e. there was no clear single region or gene of interest. Therefore, a series of rounds of backcrosses were undertaken between resistant offspring and the sensitive parent in order to increase the isogenic nature of the offspring, which would then be expected to increasingly differ only in a region linked to the trait of interest, in this case azole resistance. Thus, backcrossing was used to drive the segregation of chromosomes without causal variation, as they will become parental, combined with backcrossing serving to increase the opportunity for cross over and recombination to reduce the size of the genomic region containing the trait of interest. The subsequent BSA of progeny pools after successive backcrosses did indeed show increased ability to identify a region and candidate genes of interest when using 40 progeny per resistant and sensitive pool. BSA and bioinformatic analysis using progeny from the third backcross identified a lower number of 46-60 genes which showed SNPs between the resistant and sensitive pools and parents , with a single region of the genome containing 41 of the variant genes, although there were still consistent SNPs present on some other regions of the genome . By contumigatus . This prcyp51A gene, with the presence of a T to A variant SNP in cyp51A within the resistant progeny and parent as compared to the sensitive pools and parent. This led to a methionine to lysine (M220K) change in the CYP51A protein. Given that an identical M220K substitution in cyp51a has already been reported and experimentally verified by A. fumigatus, it was clear that this mutation was mainly, if not solely, responsible for the itraconazole resistance seen in isolate 47-308. Therefore, no further experimental validation of the candidate genes was required.Subsequent bioinformatic analysis of the 292kb region identified the presence of four clustered genes which showed the highest variant ratios (i.e. homozygosity) within the region. These included the A. fumigatus to investigate the genetic basis of a trait showing monogenic inheritance but for which the causal gene/SNP is unknown. The results of the present study are also of great value in demonstrating that the efficiency of BSA can be improved both by employing successive rounds of backcrossing and also by increasing the number of progeny in the BSA pools. The latter is consistent with mathematical modelling of the predicted size of genomic blocks obtained versus number of progeny screened as hypothesized by A. fumigatus as part of a study on construction of isogenic mating strains. However, in a preliminary application many SNPs did not follow expected distribution patterns and it was cautioned that certain causal genes might be overlooked.The failure to detect a novel genetic form of resistance to itraconazole was perhaps disappointing and the fact that this SNP had not been identified during preliminary screening indicates a possible mixed source isolate. However, taken as a whole, results presented in the present study clearly illustrate that BSA in conjunction with the dedicated bioinformatic pipeline can be used as a very valuable tool in A. fumigatus genome which undergo relatively little crossover, leading to tightly linked regions as seen on contig DS_499598, with consistent segregation and preservation of this region during sexual recombination between isolates. However, this does not necessarily imply a low recombination rate in the genome of A. fumigatus as a whole. Indeed, the fact that most genes in the 292 kb region did not show total homozygosity within the resistant pool is consistent with very occasional cross over in this region in a subset of the progeny used to construct the pools. It was telling to note that only four genes from the BC2 analysis (including cyp51A) showed complete homozygosity for the SNP reads in the resistant parent and progeny pool. Furthermore, it has very recently been reported that one cross of A. fumigatus exhibited an exceptionally high rate of meiotic recombination with ca. 29 crossovers per chromosome, representing possibly the highest known crossover rate of any eukaryotic species  progeny per pool after a second backcross (BC2), that it was not possible to identify a single unique SNP or gene of interest by BSA. Instead the same 292 kb region containing 20 candidate genes, with a clustered subset of three-four genes with highest variant homozygosity, was identified by both approaches, with the only difference being that the BC2 pools included two additional small linked regions other than the 292 kb region; these extra regions were presumably broken up by cross over and recombination events between the second and sixth backcross. Indeed, this same linked region on contig DS_499598 was apparent even in the BSA of the F1 progeny, albeit with many additional candidate regions present elsewhere in the genome . Thus, t species . IntriguA. fumigatus will not be able to identify a single unique SNP or gene of interest unless a much increased number of progeny and/or backcrosses is used. Consistent with our results, A. fumigatus throughout the genome even after nine successive backcrosses, although differences were mainly limited to a small number of blocks. Nevertheless, the size of the genomic region that might be identified through BSA (e.g. 300 kb based on the present data) is argued to be small enough to identify a manageable number of candidate genes, particularly if a subset of genes with highest homozygosity can be focused on. However, it is cautioned that larger linked blocks might be encountered elsewhere in the genome, although there may also be more beneficial smaller linked blocks as indicated by the study of N. crassa using conventional sexual crosses cyp51A, which are an important causal reason of azole resistance in certain isolates of A. fumigatus  to pinpoint the gene involved and fully characterise the mechanism of resistance.Therefore, these results indicate that the BSA approach here described for umigatus . Once caA. fumigatus and fungal genetics more generally, the balance of whether to use an increased number of progeny in pools and/or to perform successive rounds of backcrossing may be influenced in part by time-considerations. In situations where a shorter time frame is required, using a larger number of progeny but fewer backcrosses might yield similar results as repeated backcrossing. Meanwhile, the bioinformatics pipeline developed for the current study may be widely applicable for BSA of conventional sexual crosses in other fungal species where a monogenic trait is being investigated. Finally, in the specific case of A. fumigatus other methods of genetic analysis such as those involving quantitative trait loci  , which have also recently been utilised to investigate virulence and disease progression   and QTL- (X-QTL)  have bee (X-QTL) . Both BSgression  and the umigatus .The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: NCBI, GSE193956.PSD, GDA, FS, and MB designed the study. GDA, NH and SM performed the experiments. MB, FS, and VW were involved with the bioinformatic analysis. PSD and GDA wrote the manuscript. SMTC, WJGM, PEV, and PSD contributed materials. VW and FS contributed to editing of the article. All authors contributed to the article and approved the submitted version.This work was supported by grants from the Natural Environment Research Council UK (NE/P000916/1), the Wellcome Trust (219551/Z/19/Z), and the Biotechnology and Biological Sciences Research Council (BB/M008770/1) through a DTP PhD studentship.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.


Understanding the genetic architecture underpinning quantitative traits in wild populations is pivotal to understanding the processes behind trait evolution. The ‘animal model’ is a popular method for estimating quantitative genetic parameters such as heritability and genetic correlation and involves fitting an estimate of relatedness between individuals in the study population. Genotypes at genome‐wide markers can be used to estimate relatedness; however, relatedness estimates vary with marker density, potentially affecting results. Increasing density of markers is also expected to increase the power to detect quantitative trait loci (QTL). In order to understand how the density of genetic markers affects the results of quantitative genetic analyses, we estimated heritability and performed genome‐wide association studies (GWAS) on five body size traits in an unmanaged population of Soay sheep using two different SNP densities: a dataset of 37,037 genotyped SNPs and an imputed dataset of 417,373 SNPs. Heritability estimates did not differ between the two SNP densities, but the high‐density imputed SNP dataset revealed four new SNP‐trait associations that were not found with the lower density dataset, as well as confirming all previously‐found QTL. We also demonstrated that fitting fixed and random effects in the same step as performing GWAS is a more powerful approach than pre‐correcting for covariates in a separate model. We estimated heritability and performed genome‐wide association studies on body size traits in a wild population of Soay sheep using two different SNP densities (30 and 417 K). We found that while heritability estimates did not differ between SNP densities, the higher density SNP data revealed four new SNP‐trait associations not identified with the lower density data. If we know the number of loci influencing a trait and their effect size, we can better understand the evolutionary processes that underpin traits, improve inferences about trait evolution, and understand micro‐evolutionary dynamics that occur due to environmental change  with the causal variant. Increasing the density of genotyped markers means they are more likely to be in LD with causal variants for the trait of interest, either by being physically closer to the causal variants or by matching the allele frequency of the causal variants more accurately. However, increasing the number of genotyped markers means larger, denser genotyping arrays with costs increasing with density. For commonly studied species, high‐density arrays are more affordable due to high demand, but for more niche species, including wild populations, large genotyping arrays are often unaffordable. Genotyping‐by‐sequencing, for example, ddRAD  of St Kilda are a primitive, unmanaged breed of sheep that have been the focus of a longitudinal, individual‐based study since 1985  are live measures, recorded in April for neonates and in August for lambs and adults. The remaining two traits  are post‐mortem measures taken from skeletal material. Both birth and August weight are measured to the nearest 0.1 kg, while the remaining traits are all measured to the nearest mm. A detailed description of trait measurements can be found in Beraldi et al. .We defined neonates as individuals who were caught and weighed between 2 and 10 days after birth – birth weight was the only trait recorded for this age group. Lambs were classed as individuals who had phenotypic data recorded in the August of their birth year for the live traits, and as individuals who died before 14 months of age for the post‐mortem measures. Individuals were classed as adults if they had August phenotypic data recorded at least 2 years after birth, or if they died after 26 months of age for post‐mortem measures. We chose not to analyze yearling data due to the small sample sizes in comparison to the other age classes, which is due to high first winter mortality.2.2P > 1 e‐05) and individuals with a call rate < 0.95, 39,368 polymorphic variants remained for 7630 individuals . See Bérénos et al.  > 0.001, call rate > 0.99, deviation from Hardy–Weinberg Equilibrium s et al.  for infoOf these 7630 individuals, 188 have also been genotyped using the Ovine Infinium HD SNP BeadChip which targets 606,066 SNPs. This has allowed for the low‐density genotypes to be imputed to the higher density using AlphaImpute, which combines shared haplotype and pedigree information for phasing and genotype imputation , where σg2 is the additive genetic variance and M is the genomic relationship matrix (GRM). For each trait in each age class, we ran this model twice: first with M being a GRM calculated from the 50 K genotype data, and second with M being a GRM calculated from the imputed SNP genotypes. The GRMs were computed using DISSECT  by the total estimated phenotypic variance (the sum of the variance explained by the GRM and other fitted random effects after fitting fixed effects).In adults, there are multiple records for August weight, foreleg length, and hindleg length for the same individual due to individuals being caught across multiple years. For these traits, we used a repeatability model in order that uncertainty was correctly propagated through all estimations Mrode, . To implSample sizes and total number of phenotypic measurements for all traits are shown in Table 2.4Principal component analysis (PCA) using the GRM was performed prior to the genome‐wide association analyses (GWAS) using DISSECT , and gLOCO is the vector of additive genetic random effects excluding the chromosome on which the focal SNP resides.GWAS was also conducted using DISSECT  were added to the GWAS model as a fixed covariate and removed from the GRMs and genotype data. The GWAS analysis was re‐run accounting for those associations to try and reveal novel peaks either in the same regions or elsewhere in the genome.2.5For each trait × SNP association, we investigated the genes within a 0.5 Mb window either side of the top SNP to identify any genes which could be contributing to trait variation. We extracted a list of genes for each trait using the biomaRt package in R  both when using the 50 K SNPs to calculate relatedness and when using the imputed SNPs Figure . Given t3.1.2In lambs, the heritability estimates for the live August measures were lower than those for the post‐mortem measures Figure . Across 3.1.3As observed in lambs, heritability estimates for live measures in adults were lower than those of the post‐mortem measures. Across all traits, heritability estimates were higher in adults than in lambs. Estimates obtained using the 50 K SNPs and using the imputed SNPs were similar and were within one standard error of each other Figure , meaningEstimates for all variance components are listed in Table 3.23.2.1The top 20 principal components together explained 10.68% of the variance in the genetic data, with the top two principal components explaining 0.98% and 0.85% of the variance. We concluded that any population structure that was likely to affect the GWAS results would be corrected for by fitting a LOCO GRM in our GWAS model, as this will account for any structure caused by relationships.3.2.2−06 for the 50 K SNP data.To correct for multiple testing, we calculated the effective number of tests to be 20,082 using the SimpleM method  and lambs (August weight), no SNPs were found to have an association a Figure b,g. For For all three leg length measures in lambs, we found associations with the same region on chromosome 16. SNP s23172.1 was the SNP with the lowest p value for lamb foreleg and hindleg, explaining 0.52% and 0.69% of the genetic variance for each trait respectively Table c,d. For The two regions on chromosomes 16 and 19 that were associated with lamb metacarpal length variation were also significantly associated with all three leg length measures in adults, with SNP s22142.1 on chromosome 16 and SNP s74894.1 on chromosome 19 respectively explaining 0.80% and 2.04% of the genetic variation in adult foreleg, 0.88% and 1.32% of the genetic variation in adult hindleg, and 0.55% and 2.02% of the genetic variation in adult metacarpal length. There were other regions of the genome also associated with variation in the adult leg length traits; a region on chromosome 11 was significant across all three adult leg length traits, with the most significant SNP explaining 2.35%, 2.25%, and 1.13% of the genetic variance in adult foreleg, hindleg, and metacarpal respectively Figure h,j. For In lambs, there were no associations with jaw length found Figure f. In aduIn total, we identified 85 SNP‐trait associations with 39 unique SNPs.3.2.3−06.Using the SimpleM method .When performing GWAS using the imputed SNP data, we were able to recover significant SNPs in the same locations for all traits as those we found using the 50 K SNP data. Of the 85 SNP‐trait associations that we identified with the 50 K SNP data, 81 were significant using the imputed SNP data – the remaining four SNPs were no longer significant due to the increased multiple testing burden (which leads to a more stringent significance threshold) between the 50 K SNP data and the imputed SNP data , these were SNPs that were also significant in our original GWAS analysis but were not fitted in the conditional analysis due to being the only SNP that was significantly associated with the trait in that region Table . The rem3.2.5Given that all of the region‐trait associations that were found to be significant with the 50 K SNP data were also significant with the imputed SNP data, we chose to focus on top SNPs in the imputed dataset, including the two regions that were only significantly associated when performing the conditional analysis  gave an estimate 59% of Bérénos et al.'s pedigree‐based estimate , adult August weight and adult jaw length. For each trait, we simultaneously fitted the genotype for the SNP with the lowest p value for any chromosome that had at least two SNPs found to be associated with the trait (see Table CYP26B1 and EXOC6B) are associated with the same trait  and are located within 0.5 Mb of the same top SNP on chromosome 3. CYP26B1 is associated with skeletal abnormalities in humans and zebrafish  a very high density of genotyped SNPs and (ii) a large number of individuals that have been genotyped and phenotyped ; writing – review and editing . Pau Navarro: Supervision ; writing – review and editing . Sara Knott: Supervision ; writing – review and editing .This work was supported by a NERC Doctoral Training Partnership grant (NE/S007407/1). The long‐term field project on St Kilda has been largely funded by the UK Natural Environment Research Council. The SNP genotyping was funded by a European Research Council Advanced Grant. P. Navarro was supported by the Medical Research Council .https://github.com/CaelinnJames/Impact_of_SNPDensity_on_Soay_Sheep.This article has earned Open Data and Open Materials badges. Data and materials are available at Figure S1.Click here for additional data file.Figure S2.Click here for additional data file.Figure S3.Click here for additional data file.Appendix S1.Click here for additional data file.Table S1.Click here for additional data file.Table S2.Click here for additional data file.Table S3.Click here for additional data file.Table S4.Click here for additional data file.