CysE and CysK, the last two enzymes of the cysteine biosynthetic pathway, engage in a bienzyme complex, cysteine synthase, with yet incompletely characterized three-dimensional structure and regulatory function. Being absent in mammals, the two enzymes and their complex are attractive targets for antibacterial drugs. We have used hydrogen/deuterium exchange MS to unveil how complex formation affects the conformational dynamics of CysK and CysE. Our results support a model where CysE is present in solution as a dimer of trimers, and each trimer can bind one CysK homodimer. When CysK binds to one CysE monomer, intratrimer allosteric communication ensures conformational and dynamic symmetry within the trimer. Furthermore, a long-range allosteric signal propagates through CysE to induce stabilization of the interface between the two CysE trimers, preparing the second trimer for binding the second CysK with a nonrandom orientation. These results provide new molecular insights into the allosteric formation of the cysteine synthase complex and could help guide antibacterial drug design.  •HDX-MS reveals complex formation impact on conformational dynamics of CysK and CysE.•CysK binding ensures conformational symmetry within the CysE trimer.•Long-range allostery propagates through CysE stabilizing the inter-trimer interface.•Insights into the allostery of CS complex could help guide antibacterial drug design. We have used hydrogen/deuterium exchange MS to unveil the allosteric changes occurring during complex formation of CysE and CysK, the last two enzymes of cysteine biosynthetic pathway in bacteria. Significant changes in conformation and dynamics occur in each protein upon complex formation, including long distance intraprotein and interprotein communication. Being absent in mammals, both CysE and CysK represent potential targets for new antibacterial drugs, and our results on the formation and allostery of the complex could help guide drug development. O-acetylation by the enzyme serine acetyltransferase, CysE (O-acetylserine (OAS) is the substrate for the next enzyme in the pathway, namely OAS sulfhydrylase, isoform A (CysK) (l-Cys and acetate (1OAS), inhibited (PDB code: 1FCJ), and closed (PDB code: 1D6S) forms of the enzyme  . CysK ca acetate . CysK ise enzyme , 5. The e enzyme . The B-ie enzyme . CysK futivation  and has tivation . CysK activation  through tivation . The namtivation , 12. Thetivation , 13. Howtivation , 16, 17,out 6 nM , and theout 6 nM , 20, 21.out 6 nM . Cysteinout 6 nM , 24, 25.out 6 nM  likely bOur previous work has suggested that CysE binds to the closed conformation of CysK. There is also strong experimental indication from structural  and funcHydrogen/deuterium exchange MS (HDX-MS) provides a valuable approach to investigate protein dynamics in solution , 27. In et al.  and acetonitrile (Biosolve). Materials were used as received.E. coli were a kind gift of Professor Christopher Hayes, University of California, Santa Barbara , at 20 °C. It corresponded to 83 U/mg  at 20 ± 0.5 °C. All samples were equilibrated 5 min to the experimental temperature prior to spectra acquisition. The stoichiometric binding of CysE to CysK was monitored by measuring pyridoxal 5′-phosphate fluorescence emission at 500 nm, following excitation at 412 nm , 35, 38.Prior to HDX labeling, CysK and CysE proteins were diluted to 5 μM in 5 μl of equilibration solution . For CS complex formation, proteins were diluted to 5 μM CysK and 7.5 μM CysE in 5 μl total volume of equilibration buffer and incubated for 30 min at room temperature. The relative concentration of the proteins in the complex was chosen according to the known binding stoichiometry of 2:3 . The HDXE and data-dependent acquisition (DDA) mode.Frozen quenched samples were quickly thawed in a tabletop centrifuge and injected into a refrigerated (0 °C) UPLC system . The samples were subjected to online pepsin digestion at 20 °C through a home-packed column  containing pepsin immobilized on agarose beads . The resulting peptides were trapped on a trap column  and desalted for 3 min at a flow rate of 200 μl/min with solvent A . Subsequently, the peptides were separated over an analytical column  at a flow rate of 40 μl/min, with a 9 min linear gradient rising from 8% to 40% solvent B (0.23% formic acid in acetonitrile). Following the chromatographic separation, the peptides were analyzed using a hybrid electrospray ionization-quadrupole-TOF mass spectrometer . The MS was operated in positive ionization mode, and the peptides were further separated by ion mobility to enhance peak capacity. Glu-fibrinopeptide B was used for lock mass correction of all spectra. For peptide identification, nondeuterated samples were injected and subjected to two different chromatographic separation conditions: a short gradient, identical to deuterated samples, and a long gradient . The chromatographic separation was performed using the same setup as the deuterated samples. MS–MS analyses were performed using a combination of data-independent acquisition/MSE runs. Analysis of deuterium uptake of all identified peptides was manually verified. Back exchange (BE) for individual peptides was calculated using the average of the maximum deuterated controls, according to the following equation:mmax is the theoretical maximum deuterium uptake of the peptide , m0% corresponds to the mass of the nondeuterated peptide, N is the number of amide hydrogens of the peptide, and Dfrac is the fraction of deuterium in the HDX-labeling buffer. BE was calculated to validate HDX-MS system performance and support the assignment and analysis of CysK and CysE peptides. The plotted deuterium uptake profiles were not corrected for BE.MS–MS data were processed with ProteinLynx Global SERVER, version 3.0 (Waters) for peptide identification. Peptides identified by DDA MS–MS data had to have ProteinLynx Global SERVER Ladder score above 1.0 and a mass error below 15 ppm for the precursor ion. Importantly, manual inspection and quality control of the fragment spectrum for each selected peptide was also done. To increase sequence coverage, peptides similarly identified in DDA MS–MS data acquired using an extended chromatographic gradient (35 min) were added to the final peptide list if their retention time and precursor mass could be in addition identified and verified in data acquired using the same gradient used for the actual HDX-MS experiment. DynamX, version 3.0 (Waters) was used to filter peptides identified by data-independent acquisition, based on the following parameters: minimum two product ions, minimum 0.2 product ions per amino acid, and maximum 10 ppm mass error on precursor ion. Furthermore, the peptides were filtered by identification in a minimum of three of four consecutive MSSDpool) was calculated, using the equation:SDA and SDB are the states being compared . The SDpool was then used to calculate the 99% CI, using the equation:tn−1 is the table value for the two-tailed 99% CI with two degrees of freedom  and n is the number of replicates (n = 3). The 99% CI, which was calculated as a threshold for significance of changes in dynamics, corresponded to 0.46 D for CysK and 0.49 D for CysE . The SD of individual peptides n = 3) was averaged, and a pooled (root-mean-square) SD  was included to ensure maximal sampling of the HDX profile of each protein component alone and in complex .Proteolysis with pepsin allowed the identification of 79 peptides covering 98.5% of CysK sequence  and 72 pA and B (PDB codes: 1D6S and 1OAS). Overall, it is noteworthy that all ΔHDX values that exceed the ±0.46 D significance threshold range show a positive value , an indication that local regions of CysK are significantly more dynamic when unbound than within the complex. Decreased HDX upon complex formation was observed for the region encompassing residues 66 to 78, located in proximity to the active site. Representative mass spectra for CysK peptide 65 to 77, covering this region, are shown in Figure 4C. A difference in HDX was observed at the earliest measured time point (2 s) and extended to 1.67 min. Moreover, changes in dynamics located at that region of the protein are in very good agreement with previous site-directed mutagenesis experiments and functional studies . Our HDX results thus support that this region is an important part of the binding interface with CysE within CS complex.Multiple regions of CysK showed significant changes in HDX upon binding to CysE. An overall comparison of the HDX between the unbound and bound states of CysK is illustrated in  studies , 40, supzae CysK  (which cB) and belong to a flexible subdomain of the N-terminal domain that undergoes major conformational changes upon substrate binding  is apparent at the time point of 1.67 min, whereas for the latter residues (118–129), the difference in HDX started at 1.67 min and extended to the longer time points. This finding is indeed relevant, since this region undergoes the largest conformational changes that accompany the open to close transition induced by ligand binding to the protein, as demonstrated on Salmonella Typhimurium CysK -protein painting study showed that two lysine residues (K87 and K102) belonging to the flexible subdomain exhibit different exposure to the solvent upon CS complex assembly , the residue Gln143 was found to be involved in hydrogen bond formation with CysE C-terminal Ile267. Indeed, a decreased HDX indicative of a stabilization of this region was observed in peptide 142 to 154 and neighboring residues  was spotted as part of the interaction surface between CysK and CysE upon complex formation , indeed, disrupts CS complex.Decreased HDX also occurred starting from the end of helix 10 (residues 214–216), encompassing the β-loop up to residue 239. This HDX decrease was observed at all the time points and most pronounced for time points 1.67, 16.67, and 60 min. The HDX of a representative peptide of this region is plotted as a function of labeling time (0.03–720 min) in Figure 4ormation . Furtherormation  indicatet tests of the time points for which replicate data were obtained showed that the changes in HDX at the 1.67 min time point were significant for several overlapping peptides in this region.Reduced HDX indicative of structural stabilization upon CysK assembly with CysE could also be noticed in the C-terminal region of CysK, starting from residue 300 (around peptide number 70 in A). The measured HDX values for CysE alone and complex bound are summarized for each peptide as deuterium uptake plots in The effects of CS complex formation on the conformation and dynamics of CysE were also investigated. The interaction with CysK significantly impacted the HDX of different regions of CysE as shown in the difference plot comparing the two states of the protein  in Fig. 6A decrease in HDX was induced in the C-terminal tail of CysE (residues 260–275) as well as in the N-terminal part of the protein (residues 9–17). Oppositely, a significant increase in HDX was noticed for four distinct segments of the protein, including residues 87 to 105, 159 to 163, 216, and 228 to 256.i.e., 0.03–720 min) is illustrated in The HDX of a representative peptide of the C-terminal tail of CysE (residues 260–275) plotted as a function of labeling time , located at the interface between the two trimers of the hexamer, also showed reduced HDX upon CysE interaction with CysK. The effect started to appear at 1.67 min, extending also to the time point 16.67 min, as it can be observed in the HDX as a function of labeling time (0.03–720 min) for the representative peptide 8 to 17, illustrated in Oppositely, an HDX increase upon CysE binding to CysK, that is, an increased structural flexibility, was noticed in different segments of the protein sequence, involving residues 87 to 105, 159 to 163, 216, and in the region 228 to 256 that extend toward the C-terminus. This effect generally started to appear at the longer time points studied, as it can be observed from the HDX plots reported in i.e., reduced HDX) in the trimer interface and the observed widespread destabilization  of regions of the CysE hexamer placed in between the C-terminus and the trimer interface .Based on the detection of these localized changes in the HDX of CysE, we propose a binding model in which a concerted reorganization of CysE three-dimensional structure occurs upon CysK binding . HallmarB) proposes that binding of CysK to one CysE subunit triggers an intratrimer allosteric communication leading the C-termini of CysE subunits not involved in binding to CysK (via insertion into the active site of CysK) to fold back into the CysE active site. In this manner, the C-terminal sequence of bound and unbound CysE subunits is largely similar in terms of conformational flexibility and HDX.The structural basis underlying the apparently nonrandom binding of the second CysK dimer to only one subunit of each CysE trimer in the observed 2:3 complex stoichiometry is not known. As already mentioned, all the C-termini of the unbound CysE hexamer appear to be highly disordered in available crystallographic structures. Docking of just one (or two) of three CysE termini per trimer inside the CysK active site would result in dynamic and or conformational heterogeneity, and we would thus expect peak broadening in mass spectra to be observed during the HDX time course . Since nFig. 6In good agreement, evidence that CysE is able to bind part of its C-terminal sequence in its internal active site comes from structural studies that showed how the C-terminal sequence 241 to 257 is able to fold back into the active site and occupy the acetyl-CoA binding pocket with residues 254 to 257  on how CysK is impacted upon forming the CS complex. Several regions of CysK showed significant changes in HDX upon binding to CysE. Residues located next to CysK active site were confirmed to interact with the CysE C-terminal sequence. Peptides belonging to a flexible subdomain of the CysK N-terminus, that undergoes a conformational transition to a closed state upon binding of the substrate, appeared to be stabilized in the CS complex. The same effect was observed for a conserved loop of CysK, containing residues that are known to be crucial for complex formation.As for CysE, our HDX-MS results are particularly relevant in light of the limited amount of data about CysE structure and dynamics within the CS complex. We observed HDX decrease upon complex formation in agreement with the reported interaction mode with CysK, encompassing the insertion of the CysE C-terminal region into CysK ligand-binding site. Complex formation also led to increased dynamics of many segments of the protein sequence, demonstrating significant structural reorganization. This spans all the way from the region interacting with CysK to the N-terminal part of CysE on the opposite side of the protein, where an allosteric stabilization at the interface between the two CysE trimers is observed.By HDX-MS, we thus obtained a comprehensive view on how CS complex formation modulates the dynamics of CysK and CysE in solution. Our data allow us to propose a refined model for how the mature 2:3 CysK–CysE complex is formed through allosteric signaling and reorganization of CysE. Overall, our findings provide important new molecular insights into how cysteine biosynthesis is regulated in bacteria and may prove useful for the design of novel antibacterial drugs.via the PRIDE (The MS proteomics data files including processed DynamX files and an overview of the HDX-MS data  have beehe PRIDE  partner This article contains The authors declare no competing interests.


We compared testing decision, satisfaction, regret, and decision cognitions across decision frames and between scenarios. Participants randomized to ‘choice’ were least likely to opt for genetic testing compared with default and enhanced choice frames . Neither satisfaction nor regret differed across frames. Perceived autonomy  predicted satisfaction  while lack of control predicted regret . Opting for genetic testing did not differ between disease scenarios (p = 0.23). Results suggest framing can nudge individuals towards opting for genetic testing. These findings have important implications for individual self-determination in the genomic era. Similarities between scenarios with disparate disease trajectories point to possible modular approaches for web-based decisional support.Genetic testing is increasingly part of routine clinical care. However, testing decisions may be characterized by regret as findings also implicate blood relatives. It is not known if genetic testing decisions are affected by the way information is presented . We employed a randomized factorial design to examine framing effects on hypothetical genetic testing scenarios . Participants ( Technologic advances and falling costs have led to increasing use of next-generation sequencing  in routine clinical care . GeneticGenetic counselors have long played an important role in supporting patients and families to make informed testing decisions . BroadlyChoice architecture refers to the variety of ways that choices can be presented to consumers and the impact that a particular presentation has on decision-making . For exaStudies of framing effects on health information messages has shown mixed results . A CochrWe sought to determine the role of framing effects on genetic testing decision-making to inform clinical practices for pre-test genetic counseling. The Theory of Planned Behavior (TPB)  has beenclinicaltrials.gov (NCT04372888). This study was conducted in accordance with the Declaration of Helsinki and all participants provided opt-in electronic consent prior to study participation. Results are reported using the CONSORT-SPI 2018 extension for randomized social & psychological interventions [This study was reviewed and approved by the Boston College Institutional Review Board (protocol 20.205.01) and the randomized trial was registered with The study employed a randomized factorial design with two factors. The first factor was disease type . The second factor was decision frame (six levels). Participants were allocated in a 1:1 ratio. After being randomized to a hypothetical genetic testing scenario , participants were randomized to receive one of six frames for decision-making —yielding 12 groups in total . No chanA national sample of diverse, English-speaking adults (18+ years) living in North America were recruited (24–31 March 2020). Participants were users of Amazon’s Mechanical Turk (AMT) platform . BrieflyFollowing opt-in informed consent, participants provided sociodemographic information, including personal experience with breast cancer or a rare disease, and were randomized to view either the HBOC or CHH clinical scenario. Each scenario includes: (i) contextual information ; (ii) clinical information ), (iii) diagnostic information including approach to diagnosis  as well as possible results  .Participants were then randomized to one of six frames and asked to make a decision about genetic testing. The wording/phrasing for each frame is provided in n = 6) using a qualitative “think aloud” method [The other three frames (enhanced choice) were derived from the Theory of Planned Behavior (TPB) . The TPB” method . Brieflyn = 3), subjective norms (n = 2) assessing norms of dyadic relationships for genetic testing (family and physician respectively), and the perceived voluntariness and ability to make a testing decision . Additionally, perceived risk (and consequences) of the condition (common vs. rare) were measured. Questions derived from the TPB had an internal consistency of (α 0.71)—generally internal consistency >0.70 is considered ‘good’. We considered that health/genetic literacy could be an important variable. As such, participants completed subjective and objective measures of health literacy. The subjective measure of health literacy [Primary outcome measures included choosing to have genetic testing (yes/no), decision satisfaction, and regret. The Satisfaction with Decision Scale (SWD) is an easy to read, validated measure of patient satisfaction with a healthcare decision across a range of conditions and patient populations ,28. It hliteracy  has beenliteracy . The objliteracy . The NVSpost hoc t-tests adjusted for multiple comparisons using Tukey’s HSD. We assumed a significance level of 0.05. For a Cohen effect size = 0.25 (error standard deviation assumed to be 1.0). We estimated 85 subjects would be needed per treatment level combination  to achieve a power level of 0.80. We set target recruitment at 1000 participants . Interim analysis was not performed and there were no stopping guidelines.A power calculation was based on  multivariate analyses testing for pairwise differences using Mechanical Turk users interested in participating were linked to a Qualtrics™ survey to review the informed consent. After providing consent, the Qualtrics™ program randomized participants in blocks of 12. Participants were blinded to randomization and data were not reviewed by investigators until data collection was completed.post hoc tests were used as appropriate for between-group comparisons. Student’s t-tests were employed to assess relationships between subjective and objective health literacy (NVS), respectively, and testing decision. Linear regression was used to assess relationships between health literacy and education (collapsed into less than college education vs. college education or more). Logistic regression was used to examine if personal family experience with breast cancer or a rare disease affected genetic testing decision. Similarly, logistic regression was used to compare genetic test decision between and across groups. Multiple linear regression was utilized to explore the relationship between TPB responses and satisfaction (SWD) and regret (DRS), respectively. Significant standardized coefficients were compared to identify the largest effect satisfaction and regret, respectively. A p value of < 0.05 was considered statistically significant.We used ANOVA to assess the relationship between frames and satisfaction (SWD) and regret (DRS), respectively. One-way ANOVA was applied to detect relationships between TPB responses and frames. Scheffe and Games–Howell n = 507) or a rare, life altering genetic condition . After reviewing structured information (see Methods), participants were randomized to one of six frames for decision-making  and completed the study. Briefly, participants were randomized to one of two scenarios: either a common, life-threatening genetic condition  were least likely to opt for testing compared with all other frames  (p = 0.048). The enhanced choice frames, derived from the TPB, increased the likelihood of choosing to have genetic testing . We hypothesized that objective health literacy (NVS) could play a role in genetic testing decisions. However, we did not observe any association between NVS and overall decision to opt for genetic testing  regardless of frame. Among frames, there was no association observed between objective health literacy and decision to opt for genetic testing. In terms of disease scenario, framing neither had an effect on satisfaction  nor regret . We considered that framing could affect decision cognitions—yet no significant differences were observed across frames. Specifically, decision cognitions relating to “norms” (n = 3) did not differ between active choice, opt-out, and enhanced choice . Similarly, decision cognitions relating to “consequences” (n = 3) did not differ between the enhanced choice (consequences) frame and active choice .Examining choice architecture in the overall group, participants randomized to the ‘choice’ frame ( < 0.05) . Using cp = 0.24; F = 0.875, p = 0.49, respectively) (p < 0.001). Conversely, feeling one lacked behavioral control  predicted decisional regret. Considering genetic testing as being beneficial for family members predicted satisfaction with decision yet TPB elements relating to consequences  had little effect on satisfaction. Several TPB factors predicted decision regret including perceiving that the condition would affect one personally, have physical consequences, or social  consequences. Interestingly, perceiving the decision as being “easy” was associated with both satisfaction and regret.Neither satisfaction nor regret differed across the six frames  . As satictively) . First, p = 0.23). Framing neither had an effect on satisfaction  nor regret . We hypothesized that having experience  with either breast cancer or a rare disease could affect testing decisions. Groups did not differ in terms of the rates of having prior experience (HBOC: 93/507 (18%), CHH: 87/505 (17%), p = 0.42; CHH: OR = 0.60, 95%CI: 0.39–0.92, p = 0.21). Similarly, no significant differences were observed according to individual frame. Thus, individuals with prior experience of the conditions (and presumably strong views about genetic testing) do not appear to be more influenced by the frames. We compared decision cognitions (based on the TPB) between the common and rare scenarios. Within-group scores did not differ across frames and scores were similar in 11/13 decision cognition questions (p = 0.012) and norms  vs. 5.72 ± 1.32 (95%CI: 5.61–5.84), p = 0.012). While the differences reached statistical significance, it is not clear that the magnitude of difference on a seven-point Likert-type scale would be clinically meaningful.Participants were randomized to make a genetic testing decision for genetic conditions with disparate consequences—either a common/life-threatening condition  or a rare, life-altering condition . A secondary aim of the study was to examine if differences were noted in genetic testing decisions between conditions with divergent frequencies that are at opposing ends of the lethality spectrum. In this hypothetical setting, the decision to opt for genetic testing did not differ between HBOC and CHH . Traditionally, genetic counseling employs a non-directive approach  to support patients and families in making testing decisions that are informed and aligned with values and preferences . We obseGenomic medicine is relevant throughout the lifespan from pre-conception  to the newborn period , to childhood/young adulthood , and into adult life  . Few stuFindings from the present study raise important questions about self-determination in genetic testing decisions. Importantly, autonomy in genetic testing may relate to the individual  as well as blood relatives . For exaThe American College of Medical Genetics has designated 73 genes as medically actionable . ActionaThe enhanced choice frame relating to norms  was observed to be effective for nudging individuals to opt for genetic testing. Subjective norms refer to an individual’s perception of social pressures to adopt a specific behavior . InteresIt is worthwhile to note that not all genetic conditions have the same impact on health and quality of life. We compared genetic testing decision-making between two conditions with disparate prevalence (common vs. rare) and divergent disease trajectories . Participants opting for genetic testing did not differ between the Tier 1 condition HBOC  and the Findings from the present study are relevant to healthcare professionals  as well as for direct-to-consumer genetic testing. First, a key tenet of genetic counseling is a non-directive approach  that involves providing information and eliciting values and preferences to support high-quality decisions. Our observations of framing effects indicate that in hypothetical testing scenarios, testing decisions can be influenced by the way information is presented. Thus, a non-directive approach remains central for supporting patient autonomy. Moreover, our findings should caution clinicians that the way they present genetic testing information can nudge and bias patients towards testing. Similarly, study findings may be useful for informing guidelines for direct-to-consumer testing. For example, it is conceivable that marketing strategies could employ behavioral economics. Such framing of genetic testing decisions could undermine individuals’ agency and possibly be considered coercive.A relative strength of this study is the large, relatively diverse sample that mirrors the age of individuals who are typically presented with genetic testing decisions. It merits mention that while the mean sample age reflects typical timing of HBOC testing, it is less representative of CHH (as testing often occurs between 18–20 years of age). We also utilized recommendations from the International Patient Decision Aid Standards, i.e., presenting balanced information in a side-by-side format , to helpIn conclusion, we found framing genetic testing decisions increases the likelihood of individuals opting for genetic testing. We believe these findings have implications for non-directive genetic counseling as framing that differs from ‘choice’ may nudge individuals to have genetic testing. Findings also raise important questions about patient autonomy and self-determination in making genetic testing decisions. Examining decision cognitions revealed that perceived behavioral control is important for increasing satisfaction and minimizing regret. We neither identified differences based on disease prevalence (common/rare) nor lethality , raising the possibility of a modular approach to decisional support for genetic testing.


HumanNet v3 supports a three-tier model: HumanNet-PI , HumanNet-FN , and HumanNet-XC . Users can select a suitable tier of HumanNet for their study purpose. We showed that on disease gene predictions, HumanNet v3 outperforms both the previous HumanNet version and other integrated human gene networks. Furthermore, we demonstrated that HumanNet provides a feasible approach for selecting host genes likely to be associated with COVID-19.Network medicine has proven useful for dissecting genetic organization of complex human diseases. We have previously published HumanNet, an integrated network of human genes for disease studies. Since the release of the last version of HumanNet, many large-scale protein–protein interaction datasets have accumulated in public depositories. Additionally, the numbers of research papers and functional annotations for gene–phenotype associations have increased significantly. Therefore, updating HumanNet is a timely task for further improvement of network-based research into diseases. Here, we present HumanNet v3 ( Functional relations between highly wired genes underlie complex phenotypes of organisms. Hence, life scientists have tried to delineate interactions between genes and their products through diverse experimental and computational approaches. The integration of interactions inferred from various datasets and methods generally increases the reliability and coverage of a gene network . Many inhttps://www.inetbio.org/humannet/), which showed a significant performance improvement because of the inclusion of the new data and better network inference algorithms. HumanNet v3 supports a three-tier model: HumanNet-PI , HumanNet-FN , and HumanNet-XC . Users can select an appropriate tier of the network for their purpose of a study. Using multiple sources of disease gene annotations, we proved that HumanNet v3 outperforms HumanNet v2 and other integrated networks of human genes. In addition, we demonstrated that HumanNet-based prediction can prioritize human genes that are highly likely to be associated with COVID-19, suggesting its usefulness in COVID-19 research.Advanced high-throughput technologies accelerated data generation further and accumulated large amounts of functional 'omics data during the past few years. Therefore, updating HumanNet is a timely task for further improvement of network-based predictions of disease genes. Here, we present HumanNet v3 , domain profile association (DP), and GI were also improved by the enlarged data sources. Recently, the phylogenetic tree of prokaryotic species was expanded significantly by the addition of species identified by means of metagenome-assembled genomes ,21. HumaInterologs , proteinUsers may benefit from a network more appropriate for their research purpose. For example, a protein–protein physical interaction network will be more suitable for mode-of-action studies of disease mutations, and a network with no CC links may reduce over-evaluation of disease gene prediction by the literature bias toward disease studies. The previous HumanNet was based on four tiers including networks that contain interologs. As interologs are no longer incorporated into HumanNet, we offer a three-tier model for HumanNet v3: HumanNet-PI (protein-protein interaction network), HumanNet-FN , and HumanNet-XC (gene network extended by CC) Figure . HumanNeThe increases of each component network led to significant expansion of the integrated networks. The most inclusive network, HumanNet-XC, contains 1 125 494 links, which is more than twice the number of links for the largest HumanNet v2 (525 537 links). The coverage of the human protein coding genome also increased from 17 929 in HumanNet v2 to 18 462 genes in HumanNet v3, thereby covering 99.8% of protein coding genes of the consensus coding sequence (CCDS) r22 .Next, we systematically evaluated HumanNet v3 for disease gene predictions. We compared the previous HumanNet v2) with full size (XN)  and the  with fulWe first measured the percentage of links that shared the same disease annotations and the coverage for the disease gene set. For DisGeNET disease genes, among the three tiers of HumanNet v3, HumanNet-XC showed the highest precision, followed by HumanNet-FN and HumanNet-PI Figure . CompareP < 0.0001, two-tailed Mann–Whitney U test). Because network size also contributes to network-based gene prioritization, STRING may compensate for its lower network precision  analysis, and its results can be summarized as the area under the ROC curve (AUROC). Because we generally consider only the top hundreds of candidates for follow-up functional analysis, the AUROC for early retrieval is practically more important. Therefore, we assessed the disease predictions based on the AUROC up to a false positive rate of 1%. We found that HumanNet-XC and STRING share the first place in terms of performance among all the tested networks for the comparison with disease genes annotated by both DisGeNET and GWAS Catalog Figure , D. DiseThe HumanNet v3 web server largely inherited the user interface from the previous version. On the other hand, there are major improvements in network information. The most important update is the inclusion of literature data from PubMed that support PI and CC associations. In addition, all disease annotations were updated by means of the latest versions.We continue to offer two prediction modules on the HumanNet v3 web server: network-based disease gene prediction and network-based disease annotation prediction. In the network-based disease gene prediction, a user submits a known gene set, dubbed guide genes, for a disease of interest. Then, the user can examine network neighbors of the guide genes in a network view. The network view is implemented interactively; accordingly, the user can obtain detailed information on a link or gene of interest by selecting an object. In HumanNet v3, we reinforced the link information by presenting supporting evidence (publications) for PI and CC links. Next, the web server outputs metrics of how much the guide genes are interconnected in the network and predictive power of HumanNet for the guide genes according to ROC analysis. The web server also presents candidate genes for the given diseases; the genes are sorted by network prioritization scores. In network-based disease annotation prediction modules, a user submits a query gene(s). After that, the web server predicts the diseases potentially associated with the query gene by retrieving disease annotations from its neighbors. HumanNet v3 web server provides the latest versions of five gene annotation databases for pre-defined guide genes and prediction interpretation: GOBP , GWAS Cahttps://covid19.who.int/). Many human genes are involved in infectious diseases. Therefore, identification of host genes associated with COVID-19 will facilitate development of strategies for its prevention and treatment. To demonstrate the utility of HumanNet in COVID-19 study, we performed web-based disease gene prediction with guide genes that are known to be associated with COVID-19. Recently, international consortium of COVID-19 Host Genetics Initiative published results from genome-wide association studies (GWAS) comprised >49 000 patients (P < 0.0001 by permutation test). HumanNet-XC prioritized a total of 4418 candidate genes by connection to the 43 guide genes.COVID-19 is a highly contagious disease by severe acute respiratory syndrome coronavirus (SARS-CoV-2), resulting in more than 4.7 million deaths worldwide as of September 2021 (patients . We compTo confirm the validity of the network-based gene prediction, we utilized a community-wide collection of 722 COVID-19 related gene sets  derived In this report, we present an updated HumanNet version with major expansion of network information. Interologs were not integrated into HumanNet v3 because we noticed a decrease in the accuracy of the network for disease gene associations. This finding implies that protein-protein interaction mapping during the past few years filled out a large portion of the human interactome, which has been supplemented by network information transferred from other species only. Despite the exclusion of interologs, we expanded HumanNet by more than twofold as compared to the previous version. We found that HumanNet v3 outperforms both the previous HumanNet and most of the integrated human gene networks currently available publicly. Finally, we demonstrated that HumanNet can predict host genes associated with COVID-19. These results together support that the improved HumanNet will continue to provide an effective resource for the study of a wide variety of human diseases.https://www.inetbio.org/humannet. The data can be accessed through the following web browsers: Google Chrome, Microsoft Edge, Apple Safari, Mozilla Firefox.HumanNet v3 is available under the Creative Commons Attribution-ShareAlike 4.0 International License at gkab1048_Supplemental_FilesClick here for additional data file.


Genomic data are being produced and archived at a prodigious rate, and current studies could become historical baselines for future global genetic diversity analyses and monitoring programs. However, when we evaluated the potential utility of genomic data from wild and domesticated eukaryote species in the world’s largest genomic data repository, we found that most archived genomic datasets (86%) lacked the spatiotemporal metadata necessary for genetic biodiversity surveillance. Labor-intensive scouring of a subset of published papers yielded geospatial coordinates and collection years for only 33% (39% if place names were considered) of these genomic datasets. Streamlined data input processes, updated metadata deposition policies, and enhanced scientific community awareness are urgently needed to preserve these irreplaceable records of today’s genetic biodiversity and to plug the growing metadata gap. Genomic data have never been more available. Researchers can now genotype thousands of loci or sequence whole genomes from virtually any species, and these data are deposited in open-access repositories. Although generated for diverse research purposes, much of these archived genomic data have immense reuse value for measuring genetic diversity—the raw material on which species’ health depends , 2. In pSI Appendix, Appendix S1–S3 and Supplementary Methods) in the International Nucleotide Sequence Database Collaboration (INSDC)  . Most sc (INSDC) , 9, the  (INSDC) .SI Appendix, Appendix S3). Still only 38% had some location data and a collection year. Records from domesticated species had similar or more extreme levels of missing metadata compared to those from wild species  of the INSDC contained 600 terabytes (1.63 quadrillion base pairs) of genomic data representing over 16,700 unique wild and domesticated eukaryotic species and 327,577 individual organisms  of these datasets, suggesting the 14% we report for the 3,093 putatively wild datasets is representative. Adding a searchable INSDC field that identifies wild-collected individuals would greatly benefit future genetic diversity syntheses and monitoring efforts.We further investigated whether missing spatiotemporal metadata could be manually recovered from sources external to the INSDC. We prioritized 848 genomic datasets  deemed relevant for conservation monitoring, because they each described more than four putatively wild individuals. We located published scientific papers describing 739 (of 852) datasets. By reading these papers, we determined that 493 datasets  reported genetic diversity for wild populations, and we increased metadata coverage for each category B. After In summary, most depositions in the SRA lack sufficient spatiotemporal metadata to enable future reuse and genetic diversity monitoring. Even time-consuming manual efforts to recover these data  are only partially successful. Working directly with individual authors is the only remaining strategy to potentially recover these missing metadata  and these missing metadata become increasingly difficult to recover with time since deposition . In caseThe genetics community has long championed open-data publication. The INSDC databases originated in the early 1980s , which eMolecular Ecology in encouraging authors to link spatiotemporal metadata to genetic sequence data generated for wild species and domesticated species where available . Now is the time to plug this metadata gap for the most foundational layer of biodiversity. Our future ability to study, monitor, and conserve all levels of biodiversity depends on it.Our critical evaluation of whether publicly available genomic data could be used for meaningful biodiversity analyses and assessments shows that most records fall short. The identified metadata gap represents an irreplaceable loss of historical details. In 2019 alone, the SRA grew by 50%, with the addition of trillions of base pairs of DNA sequence added per day. Meanwhile the world’s sixth mass extinction event is underway with 35,000 species now listed as endangered (i.e., The International Union for Conservation of Nature’s Red List of Threatened Species, Supplementary File


Lyrurus tetrix. At its easternmost Alpine range, events of subpopulation extinction have already been documented in the past decades. Molecular data combined with spatial analyses can help to assess landscape effects on genetic variation and therefore can be informative for conservation management. Here, we addressed whether the genetic pattern of the easternmost Alpine black grouse metapopulation system is driven by isolation by distance or isolation by resistance. Correlative ecological niche modeling was used to assess geographic distances and landscape resistances. We then applied regression‐based approaches combined with population genetic analyses based on microsatellite data to disentangle effects of isolation by distance and isolation by resistance among individuals and subpopulations. Although population genetic analyses revealed overall low levels of genetic differentiation, the ecological niche modeling showed subpopulations to be clearly delimited by habitat structures. Spatial genetic variation could be attributed to effects of isolation by distance among individuals and isolation by resistance among subpopulations, yet unknown effects might factor in. The easternmost subpopulation was the most differentiated, and at the same time, immigration was not detected; hence, its long‐term survival might be threatened. Our study provides valuable insights into the spatial genetic variation of this small‐scale metapopulation system of Alpine black grouse.In modern wildlife ecology, spatial population genetic methods are becoming increasingly applied. Especially for animal species in fragmented landscapes, preservation of gene flow becomes a high priority target in order to restore genetic diversity and prevent local extinction. Within Central Europe, the Alps represent the core distribution area of the black grouse,  By using correlative niche modeling and population genetic methods, we found the spatial genetic structure of Alpine black grouse to be driven by effects of isolation by distance and isolation by resistance. Particularly for species in fragmented landscapes, maintaining gene flow is of high relevance to preserve genetic diversity and minimize extinction risks of populations and species  was specifically targeted by several genetic studies as it is of high conservation concern  are such species. Many populations of these birds are of high conservation concern due to declining trends and increasing habitat fragmentation Storch, . Well‐doBlack grouse habitats within the Alps are naturally separated by high mountain ridges and low valleys  lengths and effective resistances and parameterized regression‐based landscape genetic analyses among individuals and subpopulations. Our study helps to understand drivers of the genetic structure of Alpine black grouse populations at the edge of their range. This is the basis to infer conservation strategies and can help to prevent the loss of this characteristic bird species of Alpine ecosystems.22.1n = 250) and stored in ethanol (for muscle tissue) and frozen (for feces and feathers). DNA extraction and polymerase chain reaction (PCR) amplification were performed as described in Sittenthaler et al. , these indices quantify complementary aspects of population structure and should therefore be considered separately for subsequent analyses  among individuals. Subpopulations in our study area were assigned to clusters based on the combined interpretation of Structure and DAPC results by Sittenthaler et al.  with a sampling frequency of 2000, each initiated with a different random seed for each dataset. In order to keep the acceptance rates for proposed changes between 40% and 60%, delta values were adjusted to Δm = 0.1, Δa = 0.3, and Δf = 0.7. Convergence of chains was confirmed using Tracer 1.7.1  . The process of parameterization of resistance models is broadly discussed . For all data, we used a resolution of 100 m grain size. Preparation steps and further spatial analyses were done in ArcGIS 10.5  LCP lengths were extracted according to the cost distance approach , LCP lengths (IBR), and effective resistances (IBR) were used as predictors. Additionally, we calculated maximum likelihood population effects (MLPE) models . Results of the first and second memgene variables  resolved the four genetic clusters, with ambiguous assignments for ZIK. In estimation of migration rates, BayesAss chains converged well, and log‐likelihood and Bayesian deviance were comparable between repeats. The estimates indicate unidirectional migration patterns between the clusters  than MEM eigenvectors derived from the resistance surface based on the ENM and the resistance surface based on altitude alone . The fraction of genetic distance that is explained by the model [a] is notably higher than the fraction explained by coordinates [c], indicating good model fit (Table α = 0.05) for all models except the ones built with DJost as dependent variable. The models using LCP length as predictor were preferred for all indices of fixation or differentiation  for all our models. On an individual level, analyses resulted in models based on IBD being marginally more explanatory than models based on IBR. The proportion of shared alleles was better explained by the model including the pairwise Euclidean distances among individuals than by the model including the pairwise LCPs across the resistance surface. Pairwise genetic data are known to be noisy, and therefore, inferences are often challenging . The MLPE models showed the LCP lengths to be the best explaining predictors. Taken together, our results suggest the spatial genetic pattern in the studied black grouse metapopulation system to be driven by IBD among individuals and by IBR effects among subpopulations. Our results did not show distinct differences among models, as shown by the small delta AICc and the proportion of explained variance. Additional factors not represented within our chosen approach might be affecting genetic differentiation beyond geographic distances. We purposely excluded highly variable short‐term environmental factors. Anthropogenic factors and disturbances  might as well exert effects on the spatial genetic variation of black grouse  between subpopulations. Dispersal in black grouse most likely happens at an individual's prereproductive stage ; formal analysis ; writing – original draft (lead); writing – review and editing (lead). Peter Klinga: Conceptualization ; formal analysis . Marcia Sittenthaler: Conceptualization ; writing – review and editing . Martin Schebeck: Writing – review and editing . Christian Stauffer: Writing – review and editing . Veronika Grünschachner‐Berger: Funding acquisition (lead). Klaus Hackländer: Writing – review and editing . Ursula Nopp‐Mayr: Conceptualization ; supervision (lead); writing – review and editing .


Perdix and Alectoris. Our results suggest that species of the two genera can hybridize in nature and that artificial translocations and releases of farm reared birds for restocking or reintroduction purposes may be only partially responsible for the DNA-morphology mismatches of Italian partridges.One of the major drivers of genetic pollution is artificial translocation, which causes hybridization and introgression. We analyzed genetic markers of Grey and Rock Partridges from collections, wild populations and farms, mostly in Italy. We documented a mismatch between morphology and DNA in the identification of some individuals, as well as hybridization between the two genera of the Grey and Rock Partridges: Alectoris and Perdix from collections (museums and private collections), extant wild populations and farms. Consistent with previous studies, we found haplotypes of allochthonous species within the same genus, likely due to introductions for hunting activities. In addition, we found hybrids between Perdix and Alectoris species with genetic markers from both genera in single individuals. Such introgression was bidirectional and in both mitochondrial and nuclear markers. Counterintuitively, most of the hybrid samples came from collections before the 1950s, when large-scale translocations started, from wild populations where Grey Partridge (Perdix perdix) and Rock Partridge (Alectoris graeca) overlap in their distribution, whereas only one hybrid occurred among the farmed birds. Our results suggest that Perdix and Alectoris species can hybridize in nature and that artificial translocations and releases of farm-reared birds for restocking or reintroduction purposes may be only partially responsible for the genomic mismatches of Italian partridges.Translocations and releases of farm-reared birds are considered among the major drivers of genetic pollution with consequent loss of genetic diversity in wild populations. In this study, we aimed to assess the extent of hybridization and introgression in the Italian partridges as a consequence of translocation. We surveyed two mitochondrial markers and one nuclear marker of  The Phasianidae Horsfield 1821 family includes several small to large ground-living game birds and is the richest of the seven traditional families of the Galliformes Temminck 1820 order ,4, creatAlectoris Kaup 1829 and Perdix Brisson 1760, both characterized by historical hunting exploitation [Alectoris has been also described as a natural phenomenon in the Alps [In Europe, there are several autochthonous, native species belonging to Phasianidae, many of which have a particular economic importance as game birds for hunting activities, which frequently cause direct or indirect conservation problems for the species ,11. Two oitation ,15,16,17oitation ,20,21. Tthe Alps . Indeed,the Alps . Alectoris occurs in the southern part of the Palaearctic region with seven species. The Rock Partridge, Alectoris graeca (Meisner 1804), is the most widely distributed species of the genus in Italy. It is currently recognized as a polytypic species with four subspecies based on of morphological criteria [The genus  Meisner 804, is tcriteria . Subsequcriteria . This spcriteria  as well criteria  and Rondcriteria , is clascriteria ,29 and icriteria . Alectoris chukar (J. E. Gray 1830), native to Asia, resulted in the formation of hybrids with the native Rock Partridge [As frequently reported, the trend of European bird populations’ decline is related to direct and indirect anthropogenic causes, mostly due to the loss of suitable habitats ,32,33,34artridge ,16,21,36artridge ,37. Perdix is characterized by similar socio-economic and taxonomic issues, in part related to the intense hunting exploitation and the massive release of farm-reared birds [Perdix perdix (Linnaeus 1758), is distributed in most of Europe and the western Palearctic as far as southwestern Siberia; the Daurian partridge, Perdix dauurica , is distributed in Russia and Mongolia; the Tibetan partridge, Perdix hodgsoniae (Hodgson 1857), is present in Nepal, Tibet and China. Bao et al. [Perdix, with P. hodgsoniae being the sister to the other two species. Diversification in this genus is considered related to the Tibetan Plateau uplift combined with Pleistocene glaciations [The genus ed birds . Three sed birds  and coveo et al.  resolvedciations ,39. Amona Pallas 11, is diciations . For the two Italian partridges and for other species, artificial translocations and massive releases of genetically uncontrolled farm-reared individuals into wild extant populations are known to create a series of adverse genetic effects, such as introgressive hybridization with loss of genetic diversity  and disrPerdix and Alectoris genera, were deeply influenced by the cold-dry glacial periods in which the arctic Tundra covered great parts of northern and central Europe and several species moved towards the southern European areas [The geographical distributions of several species, including those of an areas ,41,44. Tan areas ,46. GlacHowever, since the second half of the 20th century, artificial translocations and massive releases of farm reared partridges were widely performed across Europe to face the rapid decline of both Rock and Grey Partridges and sustain their hunting exploitation ,17,37,39Alectoris and Perdix populations [Morphological distinction between congeneric species is almost entirely based on characters that are non-discrete and qualitative ,37,39,47ulations ,16,18. Alectoris and Perdix specimens from museums, private collections, extant wild populations and farms. Indeed, assuming that native genetic diversity should be preserved in museum samples dating before the beginning of the known massive release of genetically uncontrolled birds, we aimed at assessing the magnitude of the effects and the starting time of the human-mediated hybridization in the two Italian partridge species.The aim of the present study was to assess the extent of hybridization and introgression in the Italian partridges. We performed an extensive survey of the diversity of three genetic markers of COI, and a fragment of the non-protein-coding displacement loop, DLOOP; the third marker was from the nuclear genome, representing a fragment of the oocyte maturation factor mos, CMOS. In most conservation-oriented genetic studies, both mitochondrial DNA (mtDNA) and nuclear DNA (nDNA) are used ,16,20,36Alectoris and Perdix available in GenBank from Albania, Armenia, Canada, China, Cyprus, Denmark, Finland, France, Greece, Israel, Italy, Kashmir, Kazakhstan, Mongolia, Russia, Saudi Arabia, Scandinavia, Spain and USA were downloaded and added to the dataset composed of the new sequences obtained during this study. Newly generated sequences were obtained mainly from Italy (n = 959), from different individuals (i) collected from wild extant populations (n = 103), (ii) preserved in museums and private collections (n = 105) and (iii) from rearing farms (n = 751). Few new sequences (n = 16) were obtained from bird samples of unknown origins.Two hundred and forty-four sequences of the three selected markers of Alectoris and for all three species of the genus Perdix (P. perdix (n = 857), A. graeca (n = 237), A. chukar (n = 60) and A. rufa (n = 50), whereas the other species had only from one to six sequences each. The overall dataset included DNA sequences from 1219 individuals for six of the seven species of the genus s Perdix . The speP. perdix, 22.3% of A. graeca, 3.4% of A. chukar and 0.7% of A. rufa.The overall Italian sample included 989 sequences, both as new sequences and from GenBank. On the base of our morphological assignment or species identification from GenBank sequences, 73.5% of the Italian sequences are of For most birds, especially for those from collections (museums and private collections), we searched for the year when the bird was collected using labels or archives. P. perdix on a morphological base, date earlier than the middle of the 20th century, before artificial translocations and massive release of genetically uncontrolled farm reared birds took place. Of the remaining collection samples, 30 are recent, dating later than the mid-20th century, whereas the other 44 samples could not be dated reliably. All the other 884 Italian samples are recent to current.Overall, 31 samples, of which 22 assigned to Taxidermized samples were collected under the supervision of museum staff. Both live and museum specimens were sampled with a non-invasive method, collecting just a few feathers (from three to five), avoiding any damage to the sample. DNA was extracted from a single feather or from faeces (<10 mg) modifying previous published protocol  as a new adaptation of the Wizard Genomic DNA Purification Kit . Faeces were included in the dataset only if the bird was seen to take flight and the samples were collected immediately. From two to four mm of feather quills or 5–10 mg of faeces were placed in a 1.5 Eppendorf tube. A solution of 500 µL of nuclei lysis solution and 120 µL of 0.5 m EDTA for each sample was prepared and placed at −20 °C until latescence . At this point, 17.5 µL of proteinase K (10 µg/µL) for each sample was added, firmly mixed, and 637.5 µL of the solution was added to each sample. After overnight incubation, samples were homogenized using sterile potters and incubated . The procedure then follows the manufacturer’s instruction with the only final modification: samples showing visible pellet were re-suspended through 80 µL of DNA Rehydration Solution (Promega). Samples not showing visible pellet were re-suspended in just 50 µL of the same solution to avoid excessive DNA dilution. Tubes were incubated 10′ at 37 °C and overnight at 4 °C, then stored at −20 °C or immediately used for subsequent PCR amplifications.A problem that we took into consideration is the cross-contamination between contemporary and museum samples and between faeces and samples having more and fresher DNA. To avoid these problems, DNA extraction was separated day by day on the basis of sample typology, avoiding processing actual and historical samples together. Furthermore, separate laboratory rooms and dedicated laminar flow hoods were used. PCR amplifications were performed using both already published primers or primers specifically designed for this research with published or modified protocols, as detailed below.Perdix DLOOP, an amplification with LPPGLU (F5′-3′CACTGTTGTTCTCAACTACAGG) and H414 (R5′-3′ GGTGTAGGGGGAAAGAATGGG) primers [Alectoris genus, the first amplification of DLOOP was performed using PHDL and H1321 (F5′-3′TAGYAAGGTTAGGACTRAGTCTT) primers [For the  primers  was carr primers  followed primers , followi primers  and Barb primers , subdiviCOI a first amplification was performed with Bird-F1 (F5′-3′TTCTCCAACCACAAAGACATTGGCAC) and Bird-R1 (R5′-3′ ACGTGGGAGATAATTCCAAATCCTG)) primers [2O to volume (25 µL). Subsequently, for museum and faeces specimens, showing difficulties in amplifying the long fragment, this amplicon was re-amplified through a nested-PCR amplification with internal primers . Nested-PCR cycle program was: 3′ at 94 °C followed by 29 cycles of 30″ at 94 °C, 45″ at 52 °C, and 45″ at 72 °C, followed by a final extension of 10′ at 72 °C. Nested and semi-nested protocol were based on a mixture in a total volume of 25 µL with 1 µL of first amplicon, 12.5 µL of 2× PCR Master Mix (Promega), 1 µL each of 10 µM primer and nfH2O to volume (25 µL).For both genera, for  primers , amplifyCMOS was obtained by a nested-PCR approach based on a first amplification with CMOS2 primers , specifically designed for this study, with a mixture in a total volume of 25 µL with 1 µL of first amplicon, 12.5 µL of 2× PCR Master Mix (Promega), 1 µL each of 10µM primer and nfH2O to volume (25 µL) amplified through the program: 2′ at 95 °C followed by 32 cycles of 30″ 94 °C, 30″ 49 °C and 2′ 72 °C, followed by a final extension of 10′ at 72 °C. If this amplification did not work, as for museum and faeces specimens, this first amplification was followed by a nested amplification with CMOS primers [® for PCR Product Clean-Up (usb) following the manufacturer’s instructions and sequenced in forward and reverse directions by Eurofins Genomic sequencing service .When nested amplifications were needed, amplicons were purified with EXOSAP-IT Express (Thermo Fisher Scientific) following supplier protocol, and then 1 µL of each amplicon was used in subsequent amplification. Finally, PCR products were purified using ExoSAP-ITWhen working with mtDNA, the risk as argued by several authors, of amplification of nuclear insertions of mtDNAs  should be considered. Following the literature, this risk was reduced by using feathers as DNA source ,51 and cFor a selection of samples that revealed potential mismatches between morphological and DNA taxonomical identifications, the different steps were repeated extracting a different feather from the same bird to confirm the reliability of the sequences and remove the possibility of contamination or mislabelling as an explanation of the apparent mismatch.The quality filtering steps for retaining sequences for the analyses, both for the ones from GenBank and the newly generated ones, were correct translation to amino acids with no stop codons for coding markers, absence of indels for coding markers and sequence length not less than a threshold of 60% of the total length of the fragment. Only sequences that passed such quality control were retained for the analyses.Sequences were aligned with MAFFT  with defThe approach in DNA taxonomy used to identify independently evolving units from single-locus datasets was the Automatic Barcode Gap Discovery, ABGD , with thThe phylogenetic reconstructions and the results from DNA taxonomy were considered in comparison to the morphological identification of each individual and its origin  in order to support qualitative inference on the potential effects of the uncontrolled release of farm-reared birds.All the procedures were performed in compliance to European rules (Directive 2010/63/UE). The project was approved by the ethical committee of Perugia University (prot 7/2022). In particular, the approval by the ethics committee was not necessary because of the nature of some of the samples  and because of the non-invasive in vivo sampling method. Birds were immediately released at the same sampling site after sampling. Two feathers were collected from live animals, excluding those having a functional role, when handlingthe animals for sexing. Museum and in vivo sampling were authorized by local authorities. DLOOP (n = 982: 185 from GenBank and 797 new ones), followed by COI (n = 383: 55 from GenBank and 328 new ones) and CMOS (n = 131: 14 from GenBank and 117 new ones). A subset of 189 individuals had sequences from for both mitochondrial markers, 87 individuals had at least one nuclear and one mitochondrial marker, and 52 individuals had all three markers sequenced.The marker with the highest number of sequenced individuals was The phylogenetic reconstructions clearly separated two genera and all the species included in the analyses, even if for some individuals there was a mismatch between their morphological identification and one or more of the DNA sequences obtained from them. CMOS obtained for six species represented 26 sequence types, with no evidence of heterozygosity  were present in both genera.One of the 26 sequence types identified for CMOS : CMOS16 COI, the 383 retained sequences from seven species represented 98 haplotypes. The most likely solution of ABGD revealed seven taxonomic units, broadly corresponding to the seven morphological species  on the base of diagnostic morphological traits fell within the P. perdix DNA taxonomic clade. Out of the 207 sequenced individuals with P. perdix morphology, one genetically fell in the P. dauurica clade, six in the A. chukar clade and six in the A. graeca clade , one (DLOOP172) between A. chukar and P. perdix, one (DLOOP169) between three species, namely A. chukar, A. rufa and P. perdix.For  species . All ind. chukar . Seven oOverall, out of 1219 sequenced individuals, 68 (5.6%) revealed instances of mismatch between morphological classification and DNA taxonomy. For 41 of the 68 mismatches, only one sequence was available, whereas for 27 individuals two or more markers were available. P. perdix, but the three markers were unambiguous from the genus Alectoris and from the species A. chukar. Two other individuals, CO15_31 and CO15_32 ; in four birds (2.1%) the disagreement with morphology was confirmed by both markers and for the other 11 individuals (5.8%), only one of the two mitochondrial markers matched the morphological species. Out of the 189 individuals for which both mitochondrial markers, Out of the overall 68 birds with evidence of discordance between morphology and DNA or between genetic markers, 63 were Italian. Of the Italian mismatched birds, six were from extant wild populations , only one was from farmed birds , 55 were from collections (out of 105 birds: 52.4%).Out of the 55 mismatched birds from collections , 38 had a collection date and 16 date back to earlier than the middle of the 20th century, with eight of these being even from the 19th century . Out of Out of the 884 extant Italian samples and from collections dating later than the mid-1950s only 29 revealed evidence of mismatch, accounting to only 3.3%. A. chukar in Italian A. graeca  and for 27 of them for which we obtained two different markers, 24 showed also mismatches between markers. The two genera volution ,62. Alectoris and Perdix are not closely related genera in the family [CMOS, of 10.0% to 23.3% in COI, and of 15.9% to 30.3% in DLOOP. Thus, the discordances seem more likely due to recent or older hybridization and introgression. The fact that exactly the same haplotype is in some cases currently present in individuals of different genera makes the hypothesis of relatively recent hybridization more plausible, at least for those cases. The possibility for species of game birds of the order Galliformes to hybridize between distantly related species is not entirely novel, given that the Common Pheasant, Phasianus colchicus, is known to be involved in multiple numerous hybrid interactions with species of other genera [The extensive amount of hybridization and introgression left evidence in the patterns of (1) phenotype–genotype discordance: genetic markers of a genus were found in birds that were phenotypically unambiguously from another genus, and 2) mitonuclear discordance: sequences of mitochondrial and nuclear markers originally from two different genera were found within the same individual. Both discordances could be explained by hybridization or by incomplete lineage sorting. Unfortunately, with the available data it is not possible to accurately test which process could be more plausible , given t mitonucle family ,62. In ar genera .In line with previous results, we also found discordance between mitochondrial markers of the same individuals: mitochondrial DNA heteroplasmy is a known phenomenon in both plants and animals , and it The possibility of contamination can be reliably excluded, given that for all the instances of discordance, additional feathers were obtained from the samples and the amplification procedures performed again to confirm the DNA sequences making it unlikely to find exactly the same contaminants. The unlikely scenario of birds from the museum being patched up or made to look prettier by using skin or feathers from a different species could be removed from consideration by the fact that repeated feathers confirmed the same DNA sequences.In our case study, the spread of allochthonous genotypes from farm to wild birds, which was already highlighted as a potential problem for species management and conservation ,58 does Alectoris species vs Perdix species, appears very unlikely. Furthermore, considering only the 25 of the 55 birds from collection for which we had multiple markers, 23 of them (92.0%) showed mismatches even between genetic markers, confirming their potential status as hybrids. The higher propensity to find mismatches in samples stored in museums or private collections could be seen as a strong bias. Indeed, given that morphological distinction between congeneric species is almost entirely based on non-discrete characters ,37,39,47Another potential bias favouring a higher occurrence of hybrids in collections could be related to the possibility that morphologically unusual individuals have a higher likelihood of being kept and preserved in museums or in private collections, exactly because they looked unusual, making them more likely to be actual hybrids or descendants of hybrids. P. perdix and A. graeca more frequently (48.4%) in collection samples older than the 1950s, before artificial translocations and massive release of farm-reared birds took place, than in recent and current samples (2.3%). More than the type of sample, it is the temporal progression of hybridization signature to suggest a marginal contribution of human mediated introgression in the overall spread of hybridization affecting Italian partridges. Indeed, we found the signature of hybridization between A. graeca and A. rufa by Randi and Bernard-Laurent [A. graeca and three P. perdix with evidence of hybridization were from wild extant populations living in the Sibillini Mountains National Park , where the two species are sympatric between 1300 and 1800 m. a.s.l. [Since the two species are native to Italy and their populations reached the maximum expansion during the first half of the 20th century showing a wide contact zone along the extremes of altitude of their respective distribution range ,39,66,67-Laurent , even if. a.s.l. , consistAn unlikely alternative scenario should consider that translocations of farmed animals reared in promiscuous farms already occurred centuries ago.Alectoris and Perdix could not be uniquely attributed to the process of farming, although in small artificial settings, the potential for interspecific and intergeneric mating is enhanced as previously reported for other species [Our results suggest that the driving mechanisms in inducing the bidirectional genetic exchange between  species ,70,71. U species . The effWe acknowledge the potential weakness that out of 1219 animals for which we tested the phenotype–genotype potential mismatch, we had three sequenced markers for only 52. Thus, our survey of genetic diversity cannot provide inference on detailed patterns and processes. Yet, the main message that hybridization between genera exists and that it can be seen both in nuclear and mitochondrial markers from and towards both genera is a clear and unambiguous result.In conclusion, the main result of our survey focused on Italian Grey and Rock Partridges is that genetic diversity of each of the two species passed into the other species. The recorded mismatches between genera could not be unambiguously attributed to the effect of farming these birds  but seem to be plausibly determined by hybridization in the wild. The effect of restocking and reintroduction programs of game birds was previously described as one of the main causes of the occurrence of hybrids; yet, plausible signs of hybridization were found more commonly in birds that were collected before the start of massive translocations of game birds. The highlighted mismatches between DNA and morphology in species belonging to different genera represents a call for a better understanding of the biology and management strategy for partridges, in order to avoid unexpected effects on the genotypes of the wild populations ,74, and Further research should (i) verify, in captivity, the absence of biological reproductive barriers between two genera by trying different sex-species combinations under controlled conditions and (ii) assess the frequency of natural hybrids by performing non-invasive intensive biological sampling in areas of proven sympatry. Pending this advancement of knowledge, it seems appropriate, in a precautionary way, to avoid forcing the two genera spatial overlapping, as for instance, releasing Grey Partridges in mountain areas where the conservation of Rock Partridge relict populations is declared a priority.Furthermore, given the highlighted possible inconsistence between different markers, in selecting individuals for restocking or reintroduction interventions, it should be appropriate to test more than one marker. This should be encouraged especially in the case of Grey Partridge conservation programs for which the genetics is still based on mtDNA ,39,40.


To test this hypothesis, we investigated STAT3 SNPs using SNP scan™ technique in a case-control study of TB patients (n = 470) and HC subjects (n = 356), and then conducted functional studies of them using cellular models. We found that SNPs in STAT3 3`-UTR of rs1053004 TT and rs1053005 AA genotypes or T-A haplotype were associated with susceptibility to TB or TB severity. While the TT/AA genotype correlated with the low constitutive expression of stat3 and IL-17A in PBMC, the variant stat3 of rs1053004-rs1053005 T-A haplotype indeed reduced stat3 expression in reporter assays. Interestingly, host PBMC expressing the rs1053005 AA genotype and low constitutive stat3 exhibited the reduced ability to mount fast-acting innate immunity against mycobacterial infection in cellular models. Finally, mechanistic experiments showed that the STAT3 down-regulation broadly depressed STAT3 downstream anti-mycobacterial activities involving VDR-related CAMP pathway as well as IL-32, iNOS and autophagy mechanisms, leading to an enhanced mycobacterial infection. The findings of this study suggest that low constitutive stat3 derived from the TT/AA genotype/T-A haplotype acts to down-regulate STAT3, depressing multiple anti-mycobacterial pathways/mechanisms downstream, which leads to an enhanced mycobacterial infection or TB in high-risk individuals.Signal transducer and activator of transcription-3 (STAT3) plays an important role in biological balance. Our and others previous studies implied that STAT3 had a great effect on fast-acting innate immunity against tuberculosis (TB). We hypothesized that  Mycobacterium tuberculosis (Mtb), is one of the top 10 causes of death worldwide and a leading killer among infectious diseases. Around 10 million people fell ill with TB, and 1.2 million died from the disease in 2018. After exposure to TB pathogen aerosol, host immune factors are decisive for a potential clinical outcome of resulting active TB, latent TB infection (LTBI) or resisters with early clearance of TB bacillus without immune signature of infection (Tuberculosis (TB), caused by nfection .via in-depth mechanistic studies of human diseases.Signal transducers and activators of transcription-3 (STAT3) are widely expressed in host cells and have been shown to play multiple and distinct biological roles in regulating immune balance . STAT3, stat3 SNP down-regulation of STAT3 and downstream pathways leads to a change in susceptibility to TB in humans.Correlation between STAT3 SNP and susceptibility to TB has not been demonstrated, although STAT3 has been reported to regulate the development and function of T helper 17 (Th17) cells for anti-TB cellular immune responses . In factTo test our hypothesis, we performed the STAT3 SNP analysis in humans and then conducted in-depth mechanistic experiments using cellular models. Our experimental studies in humans and cellular models support the hypothesis and provides previously unreported findings and potential mechanisms regarding molecular genetics and functions of STAT3 SNP in human TB.The study was approved by the institutional review boards for human subjects’ research and institutional biosafety committees at the Shanghai Pulmonary Hospital (SPH) of Tongji University. All subjects are adults, and signed written informed consent.TB patients were recruited at the Shanghai Pulmonary Hospital . The severe TB and mild TB patients were classified according to our previous study . Brieflywww.hapmap.org). SNP genotypes were determined by SNP scan TM kits . The collaborative genetic studies of most subjects at SPH and others were completed.Whole blood samples were collected from enrolled subjects and used to isolate genomic DNA using the QIAamp DNA Blood Mini kit . SNP sites were selected from previous reports, by functional relevance and haplotype-tagging capacity as indicated on the hapmap website (PBMCs were isolated from ethylenediaminetetraacetic acid (EDTA)-treated blood of human subjects using Ficoll–Paque plus density gradient centrifugation and then cultured with RPMI1640 media supplemented with 2 mM glutamine, 50 U/ml of penicillin and 50 μg/ml of streptomycin, and containing 10% FBS (Invitrogen) according to our previous publications .Total RNA was extracted from human PBMCs using RNA column enrichment procedures . CD14+ and Vδ2+ T cells were isolated and enriched from fresh PBMC using MACS methods , respectively. RNA was reverse-transcribed into complementary DNA (cDNA). The cDNA was used to amplify target gene fragment in triplicate reactions for each gene. Sequences of q-PCR primers were listed in A wild-type or 3’-UTR of STAT3 fragments with haplotypes of T-A, T-G and C-G of SNP rs1053004-rs1053005 were constructed and inserted downstream of the luciferase reporter gene of the miR-RB-Report vector , respectively. Lipofectamine 3000 were used to transfect the reporter plasmids into 293T cells. Dual luciferase reporter system kit  was used to detect firefly and renilla luciferase activity.Mycobacteria bovis Bacillus Calmette–Guerin (BCG) Danish strain (ATCC 35733) and M. tuberculosis H37Rv were grown at 37°C in Difco Middlebrook 7H9 broth (Becton Dickinson) or on Middlebrook 7H10 agar supplemented with 10% oleic acid-albumin-dextrose-catalase-enriched Middlebrook , 0.2% glycerol and 0.05% Tween-80 for 3–4 weeks. Mycobacteria were cultured in the ABSL-II level lab of the Shanghai Pulmonary Hospital of Tongji University.The The human alveolar epithelial cell line A549, human macrophage THP-1 and mice macrophage RAW264.7 were grown in RPMI 1640 supplemented with L-glutamine (2 mM), sodium pyruvate (1 mM) and 10% heat-inactivated fetal bovine serum (FBS).THP-1 cells were treated with 50 ng/ml Phorbol 12-myristate 13-actate  for 48 h to differentiate into macrophages, then washed with PBS and maintained for infection.via counting CFU  of 10 for ~4 h. Cells were infected with H37Rv at a MOI of 4 for 4 h. After infection, extracellular bacilli were removed by washing with PBS four times. Then, mycobacteria-infected cells were co-cultured with naive PBMC containing monocytes/macrophages, innate-like γδ T cells and other innate lymphocytes in media without antibiotics for 3 days. Then, co-cultured PBMC with the infected monocytes/macrophages and lung cells were lysed in sterile PBS with SDS. Serials dilutions were performed for quantitative culturing. Mycobacteria viability were quantified ting CFU .Cells were transferred by lentivirus vector carrying STAT3 shRNA or empty lentivirus vector, and stimulated by Vitamin D (VD), BCG and medium overnight, respectively. Then, cells were lysed by incubation in RIPA lysis buffer on ice for 5 min. Next, lysates were separated by SDS-PAGE and transferred to a polyvinylidene difluoride membrane (Merck/Millipore). After blocking with 5% BSA, the membrane was incubated with Abs against STAT3 (Sangon Biotech), LC3 (Abcam), or GAPDH (Sangon Biotech) overnight at 4°C, followed by incubation with the respective secondary Abs.http://pngu.mgh.harvard.edu/~purcell/plink/) in accordance with the Hardy–Weinberg equilibrium in the controls. False discovery rate (FDR) correction of multiple hypothesis testing was performed.The allele and genotype frequencies were determined by direct counting. The demographic characteristics of the different groups were compared by chi-squared test using Statistical Package for Social Sciences (SPSS) version 21.0 software . A chi-squared test was performed to investigate the associations between allele frequencies and TB, and unconditional logistic regression analysis was used to investigate the associations between genotypes and TB assuming various genetic models , respectively, in case and control groups using Plink software (t test (parametric method) or by the Mann–Whitney test (nonparametric method).Statistical analysis was done by using GraphPad Prism software . Data were analyzed by the Student It remains unknown whether genetic variations of STAT3 could influence the susceptibility or resistance to TB in humans. Some publications demonstrated that STAT3 SNPs appeared to be associated with cancers, autoimmunity or selected infections. However, STAT3 SNP association with TB has not been reported in humans. Here, we analyzed genetic polymorphisms of rs1053005, rs1053004, rs2293152, rs744166 using SNP scan™ technique in a case-control study of TB patients (n = 470) and HC subjects (n = 356). The genetic frequencies of four SNPs in this study were accorded with Hardy–Weinberg Equilibrium Table 2,Some STAT3-SNP genotypes appeared to be more frequent in HC than in TB. Virtually, the frequency of rs2293152 genotype GG in HC subjects was significantly higher than that in TB patients compared to genotype CC/CG  genotype (p <0.05)   were isolated from uninfected HC who expressed the stat3 rs1053005 AA, AG and GG genotypes, respectively. The isolated PBMC were then co-cultured for 3 days with BCG-infected A549 lung-epithelial cells, and then assessed for CFU counts in lysate of co-cultured cells. The use of BCG, not Mtb, for transient intracellular infection of lung cells/monocytes was justified, because published studies demonstrated that BCG was similar to Mtb in transient short-term (3-day) infection or replication in monocytes/macrophages  genotype . This would provide an alternative approach to circumvent the unavailability of stat3 knockout mice due to the crucial role of STAT3 in embryogenesis -mediated inhibition of intracellular BCG growth in the transduced cells compared to the control , althougFurthermore, we determined whether silencing STAT3 could impact autophagy pathway. The ability of STAT3 to regulate autophagy has not been reported , althougThus, our results and in-depth mechanistic studies demonstrated that STAT3 down-regulation depressed diverse antimicrobial activities involving VDR-related CYP27B1, DEFB4A and CAMP pathways as well as IL-32, iNOS and autophagy mechanisms, leading to an enhanced mycobacterial infection.STAT3 is an important transcriptional factor involved in a broad spectrum of biological functions . Since gSTAT3 SNP TT/AA genotypes and T-A haplotype appear to be a genetic risk factor predisposing humans to TB and TB severity. Our large-scale case-control studies of STAT3 SNP demonstrated that rs1053004 TT and rs1053005 AA genotypes or T-A haplotype were associated with an increased susceptibility to TB and severe TB. Similarly, other studies have shown that rs1053004–rs1053005 T-A haplotype were also associated with higher HBV DNA levels . Given tstat3 RNA expression. In fact, rs1053005 AA genotype correlated with the reduced constitutive expression of STAT3 in PBMC of HC. And the AA genotype/T-A haplotype coincided with a reduced STAT3 expression in CD14+ monocytes/macrophages in PBMC from TB patients who significantly associated with the AA allele and T-A haplotype. These results were consistent with the reduced STAT3 expression in CD4+ T cells and γδ T cells of TB patients, as published by us and another group. Notably, our mechanistic experiments confirmed that the variant stat3 RNA derived from rs1053004–rs1053005 T-A haplotype indeed reduced stat3 expression perhaps due to the variant structure itself in the reporter gene-expression system. Our extensive findings are in line of the other report demonstrating that cancer patients with STAT3 SNP rs1053004 TT genotype expressed lower STAT3 protein as detected by Western blotting when compared to those with CC genotype  the rs1053005 AA genotype coincided with the reduced constitutive expression of stat3 and IL-17A in PBMC, and the variant stat3 of rs1053004–rs1053005 T-A haplotype indeed resulted in a reduced stat3 expression in reporter assays; (iii) host PBMC expressing the rs1053005 AA genotype and low constitutive stat3 exhibited the reduced ability to mount fast-acting innate immunity against mycobacterial infection in cellular models; (iv) the STAT3 down-regulation broadly depressed STAT3 downstream anti-mycobacterial activities involving VDR-related CAMP pathway as well as IL-32, iNOS and autophagy mechanisms, leading to an enhanced mycobacterial infection. Thus, the current study helps to establish the hypothetical regulatory axis of STAT3 SNP–STAT3 downregulation–downstream multiple anti-mycobacterial pathways in enhanced mycobacterial infection. Together, our findings suggest that low constitutive stat3 derived from the AA genotype or T-A haplotype to down-regulate STAT3, then depress downstream multiple anti-mycobacterial pathways/mechanisms, and then lead to an enhanced mycobacterial infection or TB.In summary, our experimental studies in humans and cellular models provided previously unreported findings and functional mechanisms as follows: (i) The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors.The studies involving human participants were reviewed and approved by the Shanghai Pulmonary Hospital. The patients/participants provided their written informed consent to participate in this study.FW, ZC, and HS conceptualized the study and conceived the project. FW, GH, and WS contributed with study design, sample processing and data analysis. LS contributed with data analysis. YP helped with sample processing. WS contributed with the recruitment of the participants and sample collection. ZC and HS wrote the paper with input from all other authors. All authors contributed to the article and approved the submitted version.This work was supported by the Chinese National Major Projects Grants [2018ZX10731301-006-001 to HS], National Natural Science Foundation of China Grants , Shanghai National Natural Science Foundation of Grant [20ZR1406200 to FW], Medical Research Plan of Fudan University [DGF501022/028/002 to FW], and Clinical Research Plan of SHDC [16CR1028B to WS].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.


X-chromosomal STRs are a powerful tool to assess a broad variety of complex kinship scenarios. We introduce herewith the first Swiss X-STR dataset based on 1198 individuals , characterized with the Qiagen Investigator® Argus X-12 QS multiplex kit. Anomalous allele patterns, allele and haplotype frequencies, and forensic and population genetic parameters are presented. We detected linkage disequilibrium within three out of the four designated linkage groups and no apparent intra-national population substructure. We compared the dataset to a global panel of X-STR datasets and it fits well in the European context, as expected.The online version contains supplementary material available at 10.1007/s00414-021-02684-y. X-chromosomal STRs can be very helpful for the assessment of complex kinship scenarios. However, after 20 years of research and X-STR usage in forensic genetics, there is still a continuous need for high-quality population data . With thFST among potential subpopulations were done with STRAF [We analyzed a sample of 1198 Swiss individuals  with Qiagen Investigator® Argus X-12 QS multiplex kit in an ISO17025 accredited laboratory framework. DNA extractions were prepared as described in Zieger and Utz . Test foth STRAF . We checp-value of 0.006 for DXS7423, none of the 12 loci significantly deviates from HWE after correcting for multiple testing of 12 loci, based on a Bonferroni-adjusted threshold at 5% significance level p = 0.0008. Haplotype frequencies are available online as FamLinkX [Allele frequencies are listed in Table p < 0.01) correspond to combinations within and not between linkage groups  of all analyzed samples. All variants are listed in Table We discovered variant alleles in about 3%  and uniformly distributed, suggesting no significant degree of population stratification for this marker set  based oet Table .The allele frequencies of the complete Swiss dataset were compared to 36 other worldwide populations  using muSupplementary file1 (XLSX 26 KB)Supplementary file2 (XLSX 29 KB)Supplementary file3 (XLSX 14 KB)Supplementary file4 (SAV 23 KB)Supplementary file5 (DOCX 267 KB)Supplementary file6 (DOCX 13 KB)Supplementary file7 (DOCX 13 KB)Supplementary file8 (DOCX 176 KB)Below is the link to the electronic supplementary material.