Schizothorax) by sequencing 1,140 base pair of mtDNA cytochrome-b (cytb) from Central Himalaya samples , augmented with 68 GenBank sequences (N = 60 Schizothorax/N = 8 outgroups). Genealogical relationships (N = 132) were analyzed via maximum likelihood (ML), Bayesian (BA), and haplotype network clustering, with clade divergence estimated via TimeTree. Snowtrout seemingly originated in Central Asia, dispersed across the QTP, then into Bhutan via southward-flowing tributaries of the east-flowing Yarlung-Tsangpo River (YLTR). Headwaters of five large Asian rivers provided dispersal corridors from Central into eastern/southeastern Asia. South of the Himalaya, the YLTR transitions into the Brahmaputra River, facilitating successive westward colonization of Himalayan drainages first in Bhutan, then Nepal, followed by far-western drainages subsequently captured by the (now) westward-flowing Indus River. Two distinct Bhutanese phylogenetic groups were recovered: Bhutan-1 (with three subclades) seemingly represents southward dispersal from the QTP; Bhutan-2 apparently illustrates northward colonization from the Lower Brahmaputra. The close phylogenetic/phylogeographic relationships between the Indus River (Pakistan) and western tributaries of the Upper Ganges  potentially implicate an historic, now disjunct connection. Greater species-divergences occurred across rather than within-basins, suggesting vicariance as a driver. The Himalaya is a component of the Earth’s largest glacial reservoir  separate from the Arctic/Antarctic. Its unique aquatic biodiversity must be defined and conserved through broad, trans-national collaborations. Our study provides an initial baseline for this process.Global biodiversity hotspots are often remote, tectonically active areas undergoing climatic fluctuations, such as the Himalaya Mountains and neighboring Qinghai-Tibetan Plateau (QTP). They provide biogeographic templates upon which endemic biodiversity can be mapped to infer diversification scenarios. Yet, this process can be somewhat opaque for the Himalaya, given substantial data gaps separating eastern and western regions. To help clarify, we evaluated phylogeographic and phylogenetic hypotheses for a widespread fish (Snowtrout: Cyprininae;  Massive, tectonically derived mountain chains such as the Himalaya are fundamental in establishing global biodiversity gradients, but strong signals of vicariance and local adaptation are generally noted within terrestrial rather than aquatic systems , with Schizothorax being retained within the monophyletic tribe Schizothoracini, which evolved either pre- or post-Barbini, depending upon the molecular marker employed.The subfamily Cyprininae was recently revised , based oSix major biogeographic groups of Snowtrout have been proposed : A CentrThe QTP (and surrounding mountains) are termed the “third pole” because the region contains the greatest amount of global snow and ice beyond the Arctic/Antarctic. It also represents the headwater source for 10 large Asian rivers , which cSchizothorax, provoking a migration into higher-elevation streams with a concomitant contraction of trailing-edge habitats  were employed to assist in the instruction of Bhutanese cadre.Specifically, sampling was accomplished using standard fisheries methods, to include hand-held seines, dip nets, backpack shockers, as well as passive gear such as hoop/ trammel nets and minnow traps. These methods and devices are approved for use by the American Society of Ichthyologists and Herpetologists  were removed from capture devices with <20 placed concurrently within a 19-liter bucket of well-aerated stream water. Direct handling of fish was minimized, and individuals were retrieved via dip net for identification and subsequent release. Larger fishes were gently removed from capture devices and identified/ released at site of capture. Care was taken in all cases to ensure that water temperatures were identical between capture site and holding bucket. Once captured, fishes were continuously monitored, and euthanasia immediately employed if sampling injuries were detected. Fishes were so recognized if they could not maintain equilibrium in the holding bucket, and/or displayed erratic or impaired opercular movements (<20 respiratory cycles/minute). Euthanasia was conducted via an overdose of clove oil (Eugenol), followed by fixation in 10% formalin.https://www.avma.org/sites/default/files/2020-02/Guidelines-on-Euthanasia-2020.pdf). A concentration of 50–150 mg/L was initially employed, then gradually increased to >400 mg/L through periodical additions (~50 mg/L). Complete cessation of opercular movement was used as an indicator of death, with the fish then being retained in solution for >10 additional min.Clove oil satisfies specified criteria and is considered acceptable when used at high concentrations (>400 mg/L), as it causes a reliable and rapid loss of consciousness and induces hypoxia .Tissues for DNA analysis were non-lethally sampled by removing a small piece of anal fin (a non-propulsive appendage). The fish was first placed in a small bucket of stream water treated with clove oil, and subsequently removed via dipnet immediately following a loss of righting ability. A small piece of fin was removed with surgical scissors cleaned in 100% EtOH. The clip was transferred to a Whatman FTA2. All three basins drain south into the east-flowing Ganges River which joins with the Brahmaputra River to terminate in the Bay of Bengal , S. nepalensis (N = 4), and S. raraensis (N = 3); total N = 10] represent a landlocked species-flock within Rara Lake , and S. progastus (N = 17)] were sampled from (west-to-east): Karnali River ; Gandaki River (N = 11/9); Koshi River (N = 5/3). Nepali samples were supplemented with those from Bhutan  chemistry , and analyzed on an ABI Prism 3700 Genetic Analyzer . In addition, we accessed 68 mtDNA cyt-b sequences representing 39 species (N = 60 Schizothorax plus eight outgroups  originate at >4,500m elevation, flow >1,000km to the border of the QTP, and subsequently drop >3,000m to Asian lowlands. Interestingly, the Mekong, Salween, and Yangtze flow in parallel for ~170km, and achieve their closest proximity at <70km . This vBA tree; ), but thBA tree; ).Studies of Himalayan freshwater most often focused on select regions, rivers, and/or mountains –80. Our Schizothorax differs per ML and BA analyses, as does S. argentatus. In the ML tree , as well as the Ili River  has a more extensive range through Iran, Uzbekistan, Kazakhstan, and Kyrgyzstan. Our TimeTree estimation indicated the Central Asia group emerged at 11.6 Ma (CI = 14.3–6.2), an estimate comparable with previous results  is also corroborated by earlier estimates . Similaiddulphi  and S. erystomus  occur inThe next major split, at 7.3 Ma (CI = 11.3–4.7), is again consistent with previous estimates (8.3–7.6 Ma) and defines two large groups  separated in early Miocene , whereas the YLTR West diverged late Pliocene . The YLTR-West species cluster as two separate groups, with S. macropogon  as sister to S. waltoni (YLTR West-A), which subsequently diverged into western and eastern groups detectable via microsatellite DNA but not cyt-b [S. oconnori and S. wangchiachii, which clusters as sister group to samples from Bhutan and YLTR East.The two Central QTP species  sustain this hypothesis, with the western group (to include S. wangchiachii) differing significantly from eastern S. oconnori (YLTR-East), and separated from it by two undescribed Bhutanese lineages . Interestingly, a third Bhutanese lineage (Bhutan-1C) clusters with YLTR-East. We consider these three as representing ‘Early Bhutan,’ given their divergence from a fourth Bhutanese clade (Bhutan-2) that apparently originages from a more recent dispersal event  undersche YLTR;  separatemponents . The resal event .S. oconnori in the ancestral YLTR. One into western Bhutan (Bhutan-1A), and a subsequent one into central/eastern Bhutan . Each is currently unverified as to species but can be tentatively allocated to S. oconnori . It thus appears as if Quaternary climatic oscillations not only yielded distinct evolutionary groupings in both S. waltoni and S. oconnori, but also among Schizothorax represented in Bhutan . The E-QTP/ SEA-B diverged at 1.7 Ma (CI = 3.5–0.8) and consists of seven species from the Yangtze River, whereas the E-QTP/ SEA-C involves seven species from the Mekong/ Salween drainages. The Mekong divergence was seemingly driven by late Pliocene orogenesis [S. gongshanensis, S. lissolabiatus, S. nukiangensis) display low genetic divergence and frequent haplotype sharing, a potential by-product of Quaternary glaciations [S. davidi, S. koslovi, S. chongli, S. gongshanensis) have yet to be fully described or documented, other than in general terms [The E-QTP/ SEA-A species split into three significantly different clades , encompaogenesis , an esticiations . Howeveral terms .sensu stricto) versus more recent divergences via the Lower Brahmaputra.The YLTR originates on the QTP, flows eastward then abruptly south through the Namche Barwa Syntaxis , with suS. richardsonii, S. esocinus, and S. progastus, whereas samples from Bhutan-2 are currently unidentified but link in the network with a haplotype of S. progastus from the Koshi River  form a distinct clade sister to the easternmost Nepali drainage , S. progastus (two lineages), and one representing a mixture of the two  occupy separate trophic niches in Rara Lake . Of the three, only S. nepalensis could be differentiated using mtDNA, and was hypothesized [S. macrophthalmus and S. raraensis via hybridization. Similarly, two morphologically distinct Snowtrout in the upper Karnali River  could not be discriminated, again hypothesized as interspecific hybrids [Schizothorax. Haplotypes of Rara Lake species are generally distinct, but not clearly separated from each other or from Karnali River samples , with Sthesized  as shari hybrids . Our mit samples .S. richardsonii and S. progastus do not differ significantly from one another in the Karnali River Basin, but do so from conspecifics in the Koshi and Gandaki rivers [The geologic age of Rara Lake is estimated at ~60 kya . Its endi rivers , a pattei rivers , 88, 89,Schizothorax. Samples from the Indus and the Ganges (immediately to the east) are unsettled, as reflected in our analyses, with several hypotheses proposed [The southern QTP and western Himalaya are now drained by the contemporary Indus River, which extends south and west from the Karakorum Range rather than from the High Himalaya. Given its western placement, the geomorphic history of the Indus River has an interesting relationship with the biogeography of Himalayan proposed . RelativThe latter hypothesis is supported by isotopic and seismic data extracted from the detrital fan of the Indus River, as deposited for >30 Ma in the Arabian Sea. These data document a major shift at ~5 Ma, with earlier Himalayan deposition superseding those from the Indus suture zone to the north . This doSchizothorax from the Lower Ganges River diverged from a lineage representing the Upper Ganges and the Indus River. Similar patterns have been noted for Indus and Gangetic dolphin [Schizothorax in the western Himalaya  were isolated prior to the capture of the Jhelum by the Indus River. Overall, our analyses reflect these unresolved questions, as indicated by placement of individual haplotypes apart from others with the same geographic origin .Incongruence between molecular and morphological phylogenies represents a challenge for the current study, as reflected by morphologically-identified species from different drainages failing to cluster together. In contrast, the converse is true for different species in the same drainage , 78. ThiSchizothorax in the Himalaya is a monophyletic genus hypothesized as originating in Central Asia and subsequently dispersing southward into Bhutan via down-cutting rivers, as well as westward across the Eastern QTP and into Southeast Asia. The subsequent capture of the YLTR by the Brahmaputra allowed for an east-to-west dispersal south of the Himalaya, facilitating sequential movements northward into Himalaya drainages, first in Bhutan, then Nepal, and eventually into the western Himalaya. Our molecular data corroborate western drainages as being previously affiliated with the Ganges River but subsequently captured by the Indus River.Schizothhorax in particular [Many morphologically-recognized species have also diverged substantially across basins, suggesting the potential for cryptic speciation and/or undescribed, relictual biodiversity. More detailed molecular studies are needed to test this hypothesis and thus promote conservation planning at the regional scale. This will require the analysis of populations now geographically isolated across the Himalaya, with cooperation/ collaboration needed among neighboring countries for comprehensive, large-scale studies , 99. Thirticular .S1 AppendixConfidence intervals for divergence estimates are provided as parentheticals.(PDF)Click here for additional data file.S1 TableSchizothorax sp. identification; River = basin; Location = collection area within basin (confl = confluence); Lat = Latitude; Long = Longitude; KU-T = Univ. Kansas Tissue number (KU:KUIT:#); KU-V = Univ. Kansas Voucher number (KU:KUIT:#); Haplotype = Univ. Arkansas Sequence number; Accession = GenBank Accession number. Sites depicted topographically in Site = sampling site (N1-N9); Species = (PDF)Click here for additional data file.S2 TableSite = sampling site (B1-N9); Species = Schizothorax sp. identification; River = basin; Location = collection area within basin (Chhu = river); Lat = Latitude; Long = Longitude; KU-T = Univ. Kansas Tissue number (KU:KUIT:#); KU-V = Univ. Kansas Voucher number (KU:KUIT:#); Haplotype = Univ. Arkansas Sequence number; Accession = GenBank Accession number. Sites depicted topographically in (PDF)Click here for additional data file.S3 TableAcrossocheilus; Pe = Pethia; Pu = Puntius; T = Tor; N = Neolissochilus; S = Schizothorax); Haplotype = Univ. Arkansas sequence identifier [i.e., from GenBank = letters and numbers; Univ. of Arkansas = starting with ’58’ (Univ. of Kansas tissue vouchers referenced in Species Name = Scientific name (A = (PDF)Click here for additional data file.S1 FigSchizothorax; Cyprinidae) and outgroup taxa derived from sequence analysis of the cytochrome-b mitochondrial gene . Individuals are coalesced into geographic regions, with abbreviations defined as: E-QTP/ SEA = Eastern Qinghai-Tibetan Plateau/ Southeast Asia, with three subclades indicated by A, B, and C; YLTR = Yarlung-Tsangpo River, with subclades indicated by West-A, West-B, and East. Numbers at nodes represent Bayesian posterior probabilities. Sample metadata in Phylogenetic relationships among snowtrout ((PDF)Click here for additional data file.


Immune dysregulation is a feature of sepsis. However, a comprehensive analysis of the immune landscapes in septic patients has not been conducted.This study aims to explore the abundance ratios of immune cells in sepsis and investigate their clinical value.t test. The Spearman rank correlation coefficient was utilized to find the relationships between immune cell abundance and pathways. The prognostic significance of immune cell ratios for patient survival probability was assessed using the log-rank test. In addition, differential gene expression was performed using the limma package, and gene co-expression analysis was executed using the WGCNA package.Sepsis transcriptome data sets were downloaded from the NCBI GEO database. The immunedeconv R package was employed to analyze the abundance of immune cells in sepsis patients and calculate the ratios of different immune cell types. Differential analysis of immune cell ratios was performed using the We found significant changes in immune cell ratios between sepsis patients and healthy controls. Some of these ratios were associated with 28-day survival. Certain pathways showed significant correlations with immune cell ratios. Notably, six immune cell ratios demonstrated discriminative ability for patients with systemic inflammatory response syndrome (SIRS), bacterial sepsis, and viral sepsis, with an Area Under the Curve (AUC) larger than 0.84. Patients with a high eosinophil/B.cell.memory ratio exhibited poor survival outcomes. A total of 774 differential genes were identified in sepsis patients with a high eosinophil/B.cell.memory ratio compared to those with a low ratio. These genes were organized into seven co-expression modules associated with relevant pathways, including interferon signaling, T-cell receptor signaling, and specific granule pathways.Immune cell ratios eosinophil/B.cell.memory and NK.cell.activated/NK.cell.resting in sepsis patients can be utilized for disease subtyping, prognosis, and diagnosis. The proposed cell ratios may have higher prognostic values than the neutrophil-to-lymphocyte ratio (NLR).The online version contains supplementary material available at 10.1186/s40001-023-01506-8. Sepsis poses a significant global clinical challenge and places a considerable economic burden on intensive care units (ICUs). It is a leading cause of multi-organ failure and mortality in ICUs . InitialSepsis is a life-threatening physiological condition triggered by an immune response dysregulation in the presence of infection and is often associated with significant mortality , 9. The Immune cell ratios, which reflect the intricate interplay of various immune cell populations, have emerged as potential candidates for unraveling sepsis heterogeneity and predicting clinical outcomes , 16. HowThe traditional approach to characterizing immune cell populations in tissues involves techniques, such as flow cytometry or immunohistochemistry, which require the isolation and labeling of specific cell types for analysis. While these methods provide valuable experimental data, they are often limited by factors, such as sample availability, cost, and technical constraints . Cell-tyHere, we first proposed the utilization of immune cell ratios as novel biomarkers for sepsis diagnosis, subtyping, prognosis, and treatment. We applied the method to sepsis and identified specific ratios associated with sepsis, survival outcomes, and infection types Fig. . Our anahttps://singlecell.broadinstitute.org/ [Sepsis-related data sets were obtained from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO). Specifically, GSE185263, which consists of 392 whole blood samples  and utilizes Illumina HiSeq 2500 technology, was utilized for the analysis of sepsis immune cell proportion changes . As GSE1ute.org/ .P < 0.05. To identify co-expression modules, we performed the unsupervised WGCNA analysis by following the guidelines outlined in the package manual [t test using the module eigengene (ME) values. For quantifying the expression of KEGG pathways, we employed the fgsea package with the following parameters: minSize = 15, maxSize = 500, and scoreType = "pos".The expression matrix was analyzed by CIBERSORT, quanTIseq, and EPIC algorithms integrated in the R immunedeconv package for immune cell abundance analysis . A relate manual . Key pare manual . The dift test was used to compare the mean difference of cell ratios between sepsis and control groups in GSE185263, as the sample size is large. Analysis of variance (ANOVA) was used to compare the mean of cell ratio in multiple groups, including SIRS, bacterial, and viral sepsis. The correlation between the two variables was calculated by Pearson or Spearman correlation coefficient for the relationship between KEGG pathways and immune cell ratios. Patients were split into two groups by the median value. Survival difference between the two groups was tested by log-rank test. All the significant thresholds were set as P < 0.01 unless otherwise specified. Survival analysis based on immune cell proportions was performed by R survival package with P < 0.01. ROC curves were plotted by the R pROC package. The schematic diagram of our analysis workflow is provided in Fig. Student’s P < 5E−5 in the sepsis data set GSE185263 . Notably, immune cell ratios eosinophil/B.cell.memory, T.cell.CD4.non.regulatory/T.cell.CD8, Tregs/T.cell.CD8, NK.cell.activated/NK.cell.resting, Macrophage.M1/Macrophage.M2, and B.cell/T.cell.CD4 showed significant associations with survival. Therefore, activated NK proportion, CD8 T cell, and M1 macrophage proportions were positively associated with survival rates. After adjusting for gender and age, all six cell ratios were still significant for survival prognosis. Among the six cell ratios, ratios eosinophil/B.cell.memory and NK.cell.activated/NK.cell.resting were still significant in survival prognosis after adjusting for gender, age, pneumonia, thrombocytopenia, and diabetes mellitus.Survival analysis of critically ill patient data set GSE65682 showed a correlation between immune cell proportions and survival Fig. . 40 immuR = 0.68, P < 0.01), which was down-regulated in sepsis patients. On the other hand, the eosinophil/T-cell CD8 ratio showed the highest negative correlation with primary immunodeficiency , which was down-regulated in sepsis. Besides, each pathway exhibited the highest correlation value with specific cell ratios. For example, the Toll-like receptor signaling pathway had the highest correlation with the neutrophil/macrophage M2 ratio , and it was up-regulated in sepsis. Complement and coagulation cascades had the highest correlation with the neutrophil/Tregs ratio , and it was up-regulated in sepsis. Chronic myeloid leukemia had the highest correlation value with the T-cell CD4 memory resting/macrophage M1 ratio , and it was down-regulated in sepsis. Colorectal cancer had the highest correlation with the T-cell CD4 memory resting/mast-cell resting ratio , and it was down-regulated in sepsis. Melanogenesis had the highest correlation with the T-cell CD4 memory resting/macrophage M2 ratio , and it was down-regulated in sepsis. The NOD-like receptor signaling pathway had the highest correlation with the T-cell CD8/mast-cell resting ratio , and it was up-regulated in sepsis. Progesterone mediated oocyte maturation had the highest correlation with the T-cell CD4 memory resting/eosinophil ratio , and it was down-regulated in sepsis. Small cell lung cancer had the highest correlation with the T-cell CD4 memory resting/macrophage M1 ratio , and it was down-regulated in sepsis. The VEGF signaling pathway had the highest correlation with the T-cell CD4 memory resting/eosinophil ratio , and it was down-regulated in sepsis. Finally, the Wnt signaling pathway had the highest correlation with the macrophage/T-cell CD4 ratio , and it was down-regulated in sepsis.The correlation analysis between immune cell ratios and the expression of the KEGG pathways showed significant associations between specific immune cell ratios and KEGG pathways. For example, the T-cell CD4 memory resting/T-cell follicular helper ratio displayed the highest positive correlation with the T-cell receptor signaling pathway (P = 4E−13) and monocyte/NK-cell resting .Using immune cell ratios to distinguish different types of infections in the data set GSE63990, we observed that the type of infection was significantly related to specific immune cell ratios. For example, the Tregs/macrophage M0, NK-cell resting/macrophage M0 ratios showed differential expression among non-infectious, bacterial, and viral sepsis Fig. . NotablyTo check if there is any biological relevance between the two groups of sepsis patients, we performed differential gene expression analysis. A total of 774 differential genes were identified in samples with high expression of eosinophil/B.cell.memory ratio compared to those with low ratios Fig. A. The clTo validate the association of these cell ratios with sepsis, we used the single-cell data set from the Broad Institute. We focused on the top 2 most significant cell ratios, namely, eosinophil/B.cell.memory and T.cell.CD4.non.regulatory/T.cell.CD8. We found that eosinophil/B.cell.memory ratio was up-regulated in sepsis, whereas T.cell.CD4.non.regulatory/T.cell.CD8 was down-regulated in sepsis Fig. A, B. We We observed that the gene ratio CD16/CD38 had a weaker association with survival than the cell ratio. The reason for the discrepancy may be that the gene ratio CD16/CD38 is not as specific for sepsis as the cell ratio. We found that the gene ratio CD16/CD38 was down-regulated in sepsis and was not associated with the sequential organ failure assessment score (SOFA), which is an indicator of sepsis severity  Boxplot for the gene ratio CD16/CD38 in control and sepsis subjects of data set GSE185263. (B) Correlation analysis between SOFA and the gene ratio CD16/CD38 in data set GSE185263. SOFA: the sequential organ failure assessment score. (C) ROC analysis of the gene ratio CD16/CD38 in viral sepsis diagnosis in data set GSE63990. AUC: area under the curve. (D) Analysis of variance (ANOVA) of the gene ratio CD16/CD38 in different infection types, including non-infectious illness, bacterial infection, and viral infection in data set GSE63990.


FBN) gene family is widely distributed in all photosynthetic organisms. Members of this gene family are involved in plant growth and development and their response to various biotic and abiotic stress factors. In this study, 16 members of FBN were identified in Glycine max and characterized by using different bioinformatics tools. Phylogenetic analysis classified FBN genes into seven groups. The presence of stress-related cis-elements in the upstream region of GmFBN highlighted their role in tolerance against abiotic stresses. To further decipher the function, physiochemical properties, conserved motifs, chromosomal localization, subcellular localization, and cis-acting regulatory elements were also analyzed. Gene expression analysis based on FPKM values revealed that GmFBNs greatly enhanced soybean drought tolerance and controlled the expression of several genes involved in drought response, except for GmFBN-4, GmFBN-5, GmFBN-6, GmFBN-7 and GmFBN-9. For high throughput genotyping, an SNP-based CAPS marker was also developed for the GmFBN-15 gene. The CAPS marker differentiated soybean genotypes based on the presence of either the GmFBN-15-G or GmFBN-15-A alleles in the CDS region. Association analysis showed that G. max accessions containing the GmFBN-15-A allele at the respective locus showed higher thousand seed weight compared to accessions containing the GmFBN-15-G allele. This research has provided the basic information to further decipher the function of FBN in soybean.The fibrillin ( Glycine max L.) is an important source of edible oil. Like other crops, abiotic stress factors are major limiting factors affecting its yield and quality. Hence, finding and understanding the role of stress tolerance-causing genes in soybean is an important step toward soybean breeding [Soybean  and bell pepper (Capsicum annuum) [FBN genes. FBN proteins play a crucial function in photosynthesis and are involved in photoprotection in response to high-light conditions at low temperatures in cucumber [TaFBNs are also expressed in response to biotic (stripe rust) and abiotic  stresses [CaFBN genes also upregulate in response to dehydration stress [FBN genes in plant growth and development [FBN genes also contain many light-responsive elements and can promote plant height and flowering under high light levels in tobacco [FBNs have been characterized in a limited number of plant species, although their role in soybean molecular breeding for drought tolerance is yet to be reported.The genome-wide identification and characterization of plant transcription factors (TFs) bears key importance. The TFs play a major role in plant growth and developmental processes, including tolerance against biotic and abiotic stress factors. Lipid-associated proteins, fibrillin (FBN), are mainly present in plastids and are omnipresent in plants. Fibrillin was first found in fibrils in the chromosomes of dog rose ( annuum) ,5. Since annuum) ,7. Chlor annuum) . FBNs arcucumber . The FBNcucumber ,11. In wstresses . Some Can stress . Kim et elopment . FBN gen tobacco . To dateGmFBN in soybean molecular breeding, the current study focused on the characterization of GmFBN for sub-cellular localization, conserved domain database (CDD), motif composition, FBN comparison among the species using sequence logo, comparative phylogenetic, molecular evolutionary analysis, and its potential roles in plant evolution followed by SNP-based marker development. Our findings outline that the GmFBN gene family offers a theoretical and practical foundation for analyzing their function, particularly in the context of soybean molecular breeding.To facilitate the use of AtFBNs were downloaded from the TAIR database (https://www.arabidopsis.org/ accessed on 13 September 2022) and were used as reference. Pfam tools (http://pfam.xfam.org/ accessed on 15 September 2022) were used to identify the specific domain. This domain was BLAST on Phytozome (https://phytozome-next.jgi.doe.gov/ accessed on 21 September 2022) to acquire the putative genomic and protein sequences in targeted species. The soybean genome sequence and the general feature format file (GFF3) were downloaded from the online web server. Chemical properties were predicted by using the online web tool ExPASy ProtParam [http://us.expasy.org/tools/protparam.html accessed on 11 October 2022). CELLO v.2.5 subcellular localization predictor (http://cello.life.nctu.edu.tw/ accessed on 21 October 2022) [http://www.softberry.com/ accessed on 21 October 2022), and WoLF PSORT [https://wolfpsort.hgc.jp/ accessed on 21 October 2022) were used to predict subcellular localization for GmFBNs. The total numbers of conserved domains in each GmFBN gene were determined using the NCBI CDD tool (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi accessed on 21 September 2022) and TBtools.rotParam   method was used to deduce evolutionary history [The protein sequences of  history . To testhttp://gsds.gao-lab.org accessed on 7 October 2022) server was used to evaluate retrieved coding and genomic sequences from databases to identify the exon-intron structure. To examine the exon-intron structure, BED file and NJ phylogenetic tree data were used. The MEME web portal was utilized to analyze protein motif distributions. A PlantCARE database (accessed on 11 November 2022) [cis-elements based on their projected biological activities, and results were visualized using TBtools.The GSDS 2.0.8. (er 2022)  was to ehttp://web.expasy.org/protparam/ accessed on 11 October 2022). Data regarding protein length, amino acid composition, protein molecular weight, p-value, and GRAVY score were retrieved for all GmFBNs using ExPASy ProtParam.Physicochemical properties were predicted by ExPASy ProtParam , and sequence logos were created using WEBLOG (https://weblogo.berkeley.edu/logo.cgi accessed on 16 November 2022) [To construct the sequence logos for conserved amino acid residues, multiple sequence alignment of er 2022) .http://visualization.ritchielab.org/phenograms/plot accessed on 17 November 2022), following Kumar et al. [FBN gene pairings, a phylogenetic tree was used for interpretation. Rates of synonymous and non-synonymous substitution were calculated using TBtools on the resulting groups of two pairs. Additionally, the Ka/Ks ratio was also examined to determine the pattern of codon selection that occurred during evolution [A. thaliana and G. max were used to generate the collinearity data. From previously generated data, collinearity, GFF, and CTL files were used for synteny visualization, following Yang et al. [Soybean genome assemblies files were used to create a chromosomal length file, and data extracted from a physicochemical properties file were used to create a gene location file. These files were then visualized in PhenoGram (volution . To perfGmFBN genes in dehydration and control conditions (https://www.ncbi.nlm.nih.gov/DataSets/ accessed on 12 December 2022). The FBN expression values (based on FPKM) were extracted to generate the heat map of GmFBNs expressed in response to drought. The heat map was constructed using TBtools software to express the transcript level of the GmFBN genes.The transcript level values were retrieved from the NCBI GEO Dataset (Accession Number: GSE98958) and used to study the expression of Forty-six soybeans accessions were planted in 2021 at the MNS University of Agriculture, Multan. Following augmented design, the field experiment was conducted under both water-limited (WL) and well-water (WW) experimental units. The field was prepared by laser leveling followed by standard agronomic practices. Briefly, one bag of urea and di-ammonium phosphate per acre were applied before sowing. Each soybean genotype was planted (using 2–3 seed planting sites) in two beds, each measuring 15 feet long and 2.5 feet wide. Plant-to-plant spacing was strictly controlled at 1 foot. Plant thinning was also performed to eradicate unhealthy plants. Weeds were also controlled manually. The WL experimental units were subjected to drought conditions, specifically during the flowering period, while WW experimental units received irrigation once every two weeks. Data regarding maximum and minimum temperature, relative humidity, and rainfall is presented in The CTAB method was used to isolate genomic DNA from soybean seedling leaves . DNA conhttps://phytozome-next.jgi.doe.gov/ 21 September 2022). The GmFBN sequences in the above-mentioned soybean cultivars were retrieved using Local BLAST. The Seqman program from the DNASTAR Lasergene package was used for multiple sequence alignment, which revealed sequence polymorphism only in GmFBN-15. This approach has been reported earlier by Nisar et al. and Fatima et al. [GmFBN-15.The whole genome sequence of three cultivars of soybean  was downloaded from . Specific primers were designed flanking the SNP at 433 bp. The PCR recipe, 2.0 µL of genomic DNA at 100 ng/µL, 0.5 µL of forward and reverse primers at 10 µm, 6.0 µL of 2× PCR Master Mix , and 4 µL ddH2O, was used to make a final volume of 13.0 µL. DNA thermal cycler  was used to amplify the target region. The PCR reaction was: denaturation at 94 °C for 3 min, followed by multiple cycles (32 cycles for GmFBN-15) of denaturation at 94 °C for 30 s, annealing at temperature 56.7 °C for 30 s, extension at 72 °C for 25 s, and a 5 min final extension at 72 °C. The amplified PCR product was then subjected to digestion using BpiI restriction enzyme. The conditions for enzymatic digestion were: 5.0 µL of PCR product, 0.2 µL BpiI FastDigest enzyme, 1 µL 10× FastDigest Green Buffer, and 9.0 µL nuclease-free water for each sample, and incubation at 37 °C for ~20 min followed by gel electrophoresis. Agarose gel (2.5%) was used to separate the digested fragments, in 1× Tris-borate-EDTA (TBE) at 90 volts for 30 min.The CAPS marker was developed on the identified SNP of t-test at a significance level of p < 0.05.Descriptive statistics were conducted using Microsoft Excel 2019. The effect of each allelic variation on the observed phenotypic traits was analyzed using the Student’s A. comosus (angiosperm), A. thaliana, G. max, G. soja, G. hirsutum, B. rapa and P. trichocarpa (dicotyledons), B. distachyon and Z. mays (monocotyledons), and P. patens (Bryophyte). Among these, 16 FBN genes were identified in G. max, 16 in G. soja, 14 in A. thaliana, 11 in Z. mays, 12 in B. rapa, 14 in G. hirsutum, 11 in P. trichocarpa, 9 in B. distachyon, and 10 in P. patens. Gene IDs of the studied species are presented in B. distachyon lowest number of FBNs), indicating that the FBN genes were subjected to large-scale expansion.A total of 113 FBN genes were retrieved from nine different species, including cis-acting elements that were found in the upstream regions of GmFBN , one of the early plant pedigrees (A. comosus (angiosperm), A. thaliana, G. max, G. soja, G. hirsutum, B. rapa and P. trichocarpa (dicotyledons), B. distachyon and Z. mays (monocotyledons), and P. patens (Bryophyte)  . AccordiP. patens through the course of evolution. In order to evaluate the extent of conservation within the FBN protein family, multiple sequence alignment was used to create sequence logos for each amino acid residue among G. max, Z. mays, and A. thaliana. We found that there were no conservation regions of G. max with G. soja, and A. thaliana, except M(1) in G. max, Z. mays, and A. thaliana , we investigated non-synonymous and synonymous divergence levels  between GmFBN gene pairs. It was established that six duplicated gene pairs showed Ka/Ks values <0.5, whereas one duplicated gene pair showed Ka/Ks values of 0.5 , and on null (control) plants for comparison [GmFBN-2, GmFBN-1, GmFBN-10, GmFBN-11, and GmFBN-15 members of the fibrillin gene family that were found to be strongly upregulated by the gene expression analyses (The Gene Expression Omnibus (GEO) dataset was used to investigate mparison . Gene exmparison . In respanalyses .GmFBN-15, a polymorphic site was identified in the coding region. To distinguish the allelic variation, one molecular marker (GmFBN-15-F/R) was developed using the CAPS technique. One allelic variation  had a BpiI restriction site, un-restricted for G-allele , A. thaliana, G. max, G. soja, G. hirsutum, B. rapa and P. trichocarpa (dicotyledons), B. distachyon and Z. mays (monocotyledons), and P. patens (Bryophyte). Members of the GmFBNs gene family were distributed widely in all the phylogenetic groups. Based on these findings, it appears that the FBN genes in these monocots that were in the same clade might have a similar biological function. Furthermore, the evolutionary study provides a base for future functional studies on FBN genes in soybean.To analyze the evolutionary relationships of the GmFBN genes in the G. max genome (~978 Mb) which were higher in number compared to P. trichocarpa (~500 Mb genome), P. patens (~500 Mb genome), and A. thaliana (~125 Mb genome). The probable reason for the larger number of FBNs in G. max (16), as compared to P. trichocarpa (11), P. patens (10), and A. thaliana (14), is that G. max is allotetraploid and the uneven distribution of GmFBNs on G. max chromosomes shows probable gene addition through segmental duplication incidents. It has been reported that gene duplication and divergence generally leads towards evolution [FBN also expanded and contributed to the genome complexity of plants.We identified 16 volution . The genGmFBNs have varied intron lengths that might play crucial roles in the functional divergence of GmFBNs. It has been well documented that intron played an important role in the evolution of different species [Gene structure analyses exhibited that  species ,2.FBNs, and it is evident that they are regulated by a wide range of biological and environmental factors [cis-regulatory elements in downstream genes is regulated by transcription factors, which play a role in a wide range of biological activities [GmFBN genes contained numerous cis-regulatory elements. Hormonal-responsive elements, including MeJA, abscisic acid, gibberellic acid, salicylic acid, and auxin, were also present in this blend, and these factors are connected in their response to light and drought. Unexpectedly, several components associated with light sensitivity were also present in all GmFBN genes.Gene function determines the extent to which a gene is expressed in various tissues and at various times during development. Several research works have reported the effects of abiotic stress on  factors ,11,12,25G. soja that regulate flowering timing [GmFBN was investigated in this study using the G. max PAN-genome. All GmFBN genes were analyzed for sequence polymorphism; however, allelic variation was only found in the GmFBN-15 coding area. Therefore, in order to conduct marker-trait association studies, only this candidate gene was considered. Allele fixation throughout evolution may account for the lack of variation in the other GmFBN genes, or this may be related to the small sample size of accessible G. max accessions in PAN-genomics research. Additional research is needed to confirm or explore these two possibilities. SNP-based molecular markers are easy to deal with and offer higher throughput compared to other markers [GmFBN-15. Williams-82 contained A-allele while the other two cultivars contained G-allele at that point [GmFBN-15, which is GmFBN-3 present on chromosome 1.Over the last ~100 years soybean genetic gain is estimated to be ~12 kg/acre . This img timing . In ordeg timing ,28,29,30 markers ,32. A siat point b. AlthouGmFBN genes in that members of the FBN gene family may improve plant performance for abiotic stress and increase yield-related traits in different stages, and can be used further for soybean breeding programs. The findings presented here will be useful for future studies into the biological roles of GmFBN genes.This study provides useful information for FBN genes in nine different organisms. Bioinformatics analyses revealed that FBN genes are relatively less conserved and contain cis-acting elements necessary for plant growth and development, and respond to various external stimuli, including drought. Moreover, marker-trait association analyses also highlighted the potential role of FBN in soybean molecular breeding.In this study, we analyzed 113 different


Co-occurrence distribution pattern analyses between bacterial datasets and eighteen monitored pharmaceuticals were performed. Higher concentrations of iohexol, ranitidine, levofloxacin, and roxithromycin were observed in the b-HTWW while atenolol, diclofenac, propranolol, and trimethoprim were higher in the b-DTWW. MPN growth assays showed recurrent occurrences of Pseudomonas aeruginosa and Aeromonas caviae among these biofilms. An enrichment of multi-resistant P. aeruginosa cells was observed in the hospital sewer line. P. aeruginosa MPN values were negatively correlated to roxithromycin concentrations. The tpm DNA metabarcoding analyses confirmed these trends and allowed an additional tracking of more than 90 species from 24 genera. Among the recorded 3082 tpm ASV (amplicon sequence variants), 41% were allocated to the Pseudomonas. Significant differences through ANOSIM and DESeq2 statistical tests were observed between ASV recovered from b-HTWW, b-DTWW, and epilithic river biofilms. More than 500 ASV were found restricted to a single sewer line such as those allocated to Aeromonas popoffii and Stenotrophomonas humi being strictly found in the b-HTWW file. Several significant correlations between tpm ASV counts per species and pharmaceutical concentrations in biofilms were recorded such as those of Lamprocystis purpurea being positively correlated with trimethoprim concentrations. A tpm source tracking analysis showed the b-DTWW and b-HTWW tpm ASV to have contributed, respectively, at up to 35% and 2.5% of the epilithic river biofilm tpm-taxa recovered downstream from the WWTP outlet. Higher contributions of TWW taxa among epilithic biofilms were recorded closer to the WWTP outlet. These analyses demonstrated a coalescence of WWTP sewer communities with river freshwater taxa among epilithic biofilms developing downstream of a WWTP outlet.The ability of WWTP outflow bacteria at colonizing rock surfaces and contributing to the formation of river epilithic biofilms was investigated. Bacterial community structures of biofilms (b-) developing on rocks exposed to treated wastewaters (TWW) of a hospital (HTWW) and a domestic (DTWW) clarifier, and to surface waters of the stream located at 10 m, 500 m, and 8 km from the WWTP outlet, were compared. Biofilm bacterial contents were analyzed by cultural approaches and a  Pseudomonas, Acinetobacter, Arcobacter, Trichococcus, Tetrasphaera, Rhodoferax, Rhodobacter, and Hyphomicrobium [Comamonas, Sphingobacterium, Ochrobacterium, Stenotrophomonas, Shinella, Diaphorobacter, Agrobacterium, Achromobacter, Phenylobacterium, and Flavobacterium [Wastewaters (WW) can have complex chemical and microbiological contents . The 16Sicrobium ,3,4. Simacterium . This diacterium . The domacterium  like leaacterium ,10,11. Acinetobacter, Clostridia, Aeromonas, and Alistipes were reported [blaTEM (penicillin resistance), qnrS (fluoroquinolone resistance), sulI (sulfonamides resistance), mecA (methicillin-resistance gene), and tetW and tetO (tetracycline resistance) [A selective effect, even at low concentrations, of these WW chemical pollutants on sewer microbial communities was suggested to occur. Antibiotics were found to modulate WW microbial communities by driving a decay of sensitive bacteria and selecting resistant species ,13. Furtreported . Furtheristance) ,17. Thesistance) . Poor deistance) . The main goal of this study was to assess the ability of WWTP-related bacteria at competing with native freshwater microbial communities and at occupying particular river ecological niches. An experimental framework was designed to demonstrate that HTWW  and DTWW (domestic-treated WW) bacteria released into a stream not only can get mixed with endogenous river taxa but can also interact with the native communities to favor the formation of epilithic biofilms. Rock surfaces were considered growth opportunities for WWTP-related taxa with strong biofilm development capacity and high tolerance to chemical pollutants which are simultaneously delivered with the TWW (treated wastewaters). To test these hypotheses, blueschist rocks were exposed over 8 to 16 weeks to river surface waters and treated wastewater, and their biofilm bacterial communities and pharmaceutical contents were analyzed and compared. These investigations were performed using the French Sipibel experimental site .tpm metabarcoding approach. This metabarcoding approach was found to be highly discriminant and to allow the differentiation of more than 100 species of γ-proteobacteria such as those of the Aeromonas and Pseudomonas which are highly prevalent in WW [tpm-harboring taxa could be used in a SourceTracker Bayesian approach [tpm source tracking revealed a significant number of sewer tpm ASV among river epilithic biofilms, even at a distance of up to 8 km from the WWTP outlet. These observations demonstrated the ability of WWTP tpm-harboring bacterial taxa at invading major river ecological niches and competing with native freshwater taxa.The rock bacterial biofilm community structures were investigated by classical most probable number growth assays and platings, by quantitative PCR assays targeting DNA signatures of integrons and fecal source indicator species, and through the nt in WW . The conapproach  to inferhttp://www.graie.org/Sipibel/ (accessed on 16 February 2023)) was used in this study. It has a processing capacity of 32,000 equivalent inhabitants. The outflows of this WWTP are delivered into the Arve river which flows through Switzerland and France over 108 km before reaching the Rhône river. Flow monitoring indicated an average of 66 m3 of water discharged per second close to the WWTP with a maximum flow in May and June. The Bellecombe WWTP processes are described in Chonova et al. [The WWTP of Bellecombe , HTWW , or the Arve surface waters. This approach allowed an investigation of the co-accumulation of micro-organisms and chemical pollutants in the collected biofilms, and to highlight co-occurrence patterns between these contaminants. Before being used on site, blueschist rocks were brushed, cleaned with 5% hyperchlorite, and sterilized by autoclave. Blueschist rocks were placed in stainless steel traps which were immerged under 5 cm of water in the various compartments to be tested: (1) in the clarifiers of the hospital  and domestic  lines, and (2) in the Arve river at 8 km upstream and downstream the entry point of the treated effluents , at 500 m upstream and downstream the entry point  and at 10 m upstream and downstream the entry point  see . SamplinPhysicochemical parameters of blueschist rock biofilms or water samples were monitored . NutrienAeromonas caviae and Pseudomonas aeruginosa were quantified using the MPN (most probable number) methods described in Navratil et al. [Enterococci, total coliforms, and E. coli were measured using the IDEXX Colilert and the Enterolert type E kit  following the manufacturer’s instructions. Biofilms on the immerged Blueschist rocks were scraped using a sterile spatula and a sterile toothbrush. Microbial DNAs of biofilms were extracted with the Gene-Elute-LPA kit  using the manufacturer’s instructions. DNA extracts were used in qPCR assays performed in triplicates on a Bio-Rad CFX96 qPCR apparatus using the Brilliant II SYBR Green low ROX qPCR mix . Quantifications of the gene targets were performed using the CFX Manager 3.0 software . Total bacteria were quantified by qPCR using the 338F and 518R primers targeting the 16S rRNA gene according to [Bacteroidales were quantified using the AllBac296F and AllBac467R primers according to [Counts of total heterotrophic bacteria were estimated by inoculation of 10-fold diluted TSA (tryptic soy agar) amended with 1.2% agar. l et al. . Intestirding to . Total Brding to . Relativrding to . Mobile tpm phylogenetic marker allows an allocation of amplicon gene sequences to bacterial species of, mainly, a group of γ-proteobacteria including the Aeromonas and Pseudomonas. PCR products were generated as already described [tpm raw reads were processed using the dada2 package for R [https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/ (accessed on 16 February 2023)). The SOP (standard operating procedure) at https://benjjneb.github.io/dada2/bigdata_paired.html (accessed on 16 February 2023) for paired-end reads was used to process the tpm raw reads. The decontam package for R [tpm reads were taxonomically affiliated using the tpm metabarcoding sequences database [The escribed . PCR proge for R . Linker,ge for R  was useddatabase . tpm inferred taxa between the b-HTWW, the b-DTWW, and the river biofilms samples were investigated using the DESeq2 package for R [tpm species and the concentration of pharmaceuticals were computed using the Corrplot R package v0.84. Spearman correlation matrices were illustrated by a heatmap computed on the Excel software. Coalescence phenomena between bacterial communities of the treated wastewater effluents (contamination sources) and the river ones (receiving environment) were investigated using the SourceTracker computer package described by [tpm gene read, burn-in: 100, restart: 10). The confidence on the computed contribution values were estimated using the relative standard deviation (RSD) from the three SourceTracker runs  and beta diversity (Bray-Curtis dissimilarity distances) indices and rarefaction curves were computed using the R software v3.5.3 with the Vegan package v2.5.6 as carried out in . All Wilge for R . Spearmaribed by . The Bays .P. aeruginosa strains were isolated from HTWW, DTWW, and river surface waters but also from the raw WW from the hospital and domestic sewers. P. aeruginosa strains were isolated using a Pseudomonas agar base  completed with 5% glycerol, 200 mg/L cetrimide, and 15 mg/L nalidixic acid. Isolates were confirmed as belonging to P. aeruginosa using the ecfX-specific PCR screening [P. aeruginosa antibiotic resistance using n = 188 Sipibel field site isolates. creening . Antibiop-value < 0.05). Iohexol, ranitidine, levofloxacin, and roxithromycin were found in significantly higher concentrations in b-HTWW than in b-DTWW . Most of these trends were confirmed with the WW monitoring  . Correlograms computed from Spearman correlation matrices between the pharmaceutical concentrations monitored in biofilms or WW confirmed these segregations between the domestic and hospital treatment lines . Interestingly, higher caffeine contents were observed among the DTWW than HTWW  but no major differences were observed between the b-HTWW and h-DTWW . Pharmaceuticals, physicochemical, and classical bacterial parameters were monitored for the rock biofilms and water samples from the river, and domestic and hospital treatment lines of the WWTP of Bellecombe . Principn b-DTWW  (Wilcoxonitoring . In fact < 0.05) . Atenolont lines . It is tnt lines . Higher 5 to 1.8 × 107 per g biofilm (dry weight) . Total Bacteroidales per g biofilm ranged from 0 to 1.4 × 103 copies per g biofilm (dry weight). Generally, fecal indicator bacteria  were found in higher numbers among the b-DTWW samples than b-HTWW . A PCA was computed from this dataset . Interestingly, b-RU_far5 (8 km upstream of the WWTP) river biofilms showed higher numbers of integron II DNA sequences . Nevertheless, high numbers of P. aeruginosa gene targets of 3.67 × 101 to 8.05 × 104 and 6.83 × 103 to 7.04 × 106 MPN/g biofilm were detected among, respectively, the b-HTWW and b-DTWW. P. aeruginosa numbers were below the limit of detection for the biofilms sampled from the Arve River. Microbial contents of the biofilm samples were monitored by culture- and DNA-based methods including quantitative PCR assays. This highlighted high 16S rRNA gene copy numbers from 1.41 × 10 weight) . River b dataset . b-DTWW equences . Most miP. aeruginosa numbers were found to be positively correlated to pharmaceutical loads of both the b-HTWW and b-DTWW and concentrations of aciclovir, atenolol, clofibrate, diazepam, and epoxicarbamazepine . There was no significant difference between ASV numbers of biofilms from b-RU and b-RD samples. However, the distance between sampling points and the outlet of the WWTP impacted negatively the ASV numbers. B-RU_close and b-RD_close biofilms showed significantly lower numbers of ASV than those sampled from b-RU_med, b-RU_far, b-RD_med, and b-RD_far . b-HTWW biofilms showed significantly lower ASV numbers than those from the b-DTWW ones . Shannon index computed from the tpm ASV datasets showed heterogeneous values going from 5.14 to 1.11 . Evenness indices showed values from 0.98 to 0.17. b-HTWW3 (0.98), b-HTWW4 (0.89) and b-RU_close3 (0.86) showed the highest values while b-RU_far3 (0.17), b-RU_far4 (0.45) and b-RD_far1 (0.50) showed the lowest ones . The e et al.  generate to 1.11 . Sample est ones . Distanctpm bacterial communities of the biofilm samples according to their origin, a Bray-Curtis dissimilarity matrix was computed on the ASV table after a Hellinger transformation . However, ANOSIM tests did not show significant differences between river biofilms sampled upstream and downstream of the outlet of the WWTP . Taxonomic affiliations of the ASV were performed. This allowed the classification of more than 99% of the reads at the phylum level  and Cyanobacteria but in low numbers. At the genus level, taxonomic affiliations allowed the classification of about 80% of the tpm reads into 24 well-defined genera  than the b-TWW related ones. Nevertheless, Aeromonas, Pseudomonas, and Herbaspirillum were found among all the biofilm samples , P. anguilliseptica-like (4.80%), H. aquaticum (2.41%), A. sobria (1.45%), P. fluorescens (1.19%) and P. koreensis (1.14%). Several species of health concern were detected among the tpm dataset including A. sobria, P. aeruginosa, A. caviae, and A. hydrophila. Infra-specific diversity of the P. aeruginosa reads was explored according to Aigle et al. (2021). ASV_1211 and ASV_1373 were found to match the tpm type-G08-24 of the P. aeruginosa PA14 sub-clade. ASV_1664 and ASV_1682 matched the tpm type-G12_15_17_18_35 sequences of the PAO1 sub-clade. Two fish pathogens, P. anguilliseptica and A. salmonicida, could be tracked using the tpm dataset.ASV were mainly allocated to the undances . Interes samples . Taxonomhis work . Five sptpm ASV allocated to particular species were investigated (Lamprocystis purpurea (5/12 samples) and Stenotrophomonas humi (4/12)  . No species were found to vary significantly between b-RU and b-RD river biofilm samples (DESeq2: p > 0.05). Distribution biases of the stigated . Eleven i (4/12) . NitrospU: 6/17) . DESeq2 tpm ASV including highly prevalent ones showed differentiated patterns according to their occurrences among b-HTWW or b-DTWW biofilms (Gammaproteobacteria), ASV_42 , ASV_52  or ASV_131  showed higher read numbers among b-HTWW samples (DESeq2: p < 0.05). Conversely, ASV_22 , ASV_39 , ASV_59  and ASV_84  were found in higher numbers among the b-DTWW samples (Hyphomicrobium sp.), ASV_2 , and ASV_63  which showed higher read numbers among river biofilms (DESeq2: p < 0.05). Conversely, nine ASV were found in higher numbers among biofilms exposed to TWW: ASV_46 , ASV_93 , ASV_96  and ASV_148  (DESeq2: p < 0.05)  showed higher read numbers among biofilms sampled upstream of the WWTP rather than downstream (DESeq2: p < 0.05)  . Dechlor < 0.05) .tpm metabarcoding dataset and the pharmaceutical concentrations was computed and highlighted significant Spearman correlations (L. purpurea were found positively correlated to the concentrations of atenolol (D) , those of Pseudomonas_Gp_BR to bezafibrate, of A. veronii to caffeine, and of L. purpurea to iohexol (H) and ranitidine (H). L. purpurea tpm reads also showed significant positive correlations with concentrations of trimethoprim (D), and negative ones with iohexol (H), ranitidine (H), roxithromycin (H), and sulfamethoxazole (H) as indicated in S. humi and A. popoffii read numbers were positively correlated to iohexol (H), levofloxacin (H), ranitidine (H), roxithromycin (H), and sulfamethoxazole (H), but negatively to clofibrate, proponolol (D) and trimethoprim (D) , and bezafibrate, but negatively with roxithromycin (H) concentrations , and roxithromycin (H), and positively with caffeine. P. anguilliseptica-like tpm reads showed negative relations with trimethoprim, which was in higher concentrations in the b-DTWW but also clofibrate, and diazepam. H. aquaticum tpm read numbers were found correlated to bezafibrate and trimethoprim (D), and negatively with diazepam and levofloxacin (H). A heat map illustrating relations between the elations . Among tprim (D) . The Humtrations . Among ttpm ASV from the b-HTWW and b-DTWW (termed b-TWW when grouped) biofilms with those observed in epilithic biofilms upstream of the WWTP outlet was estimated among downstream WWTP outlet epilithic biofilms by a SourceTracker Bayesian analysis . tpm bacterial communities of downstream WWTP biofilm river samples were also found to be explained by about 0.7% of the b-HTWW biofilm ASV  . These trackings of tpm bacterial sequences going from b-TWW towards river biofilms were further explored using a Venn diagram illustrating the origin of the ASV (P. anguilliseptica-like), ASV_186 , ASV_402 , ASV_928  and AVS_1173  . On the  the ASV . Biofilm the ASV . b-DTWW, the ASV . b-RU shsis-like . P. aeruginosa was detected among all samples either by PCR assays or the tpm metabarcoding approach, this species was further used to explore the transfer of antibiotic-resistant strains from the hospital and domestic sewer systems down into the connected river. P. aeruginosa strains were isolated from wastewater of the clarifiers of the hospital and domestic sewer lines of the WWTP, and the Arve River. Antibiograms were carried out on 188 isolates  . Over this collection, 57 strains were found to be multi-resistant (showing resistances to at least three antibiotic families) and 40% of these had been isolated from the HWW treatment line  and likely to come from the hospital WW. Several strains of the hospital line were found highly resistant to the tested antibiotics such as bpoe3519, bpoe3454, or bpoe3516 isolated from the HWW samples and showing respectively 15, 14, and 14 antibiotic resistances over the 21 tested conditions (P. aeruginosa infections (strains) . The P. ent line . These ient line . The isonditions . Strainsfections . It is tChemical and biological contaminants of sewer systems can greatly vary according to the origin of the wastewater . At the tpm-metabarcoding approach was then applied to explore the co-occurrence patterns of pharmaceuticals and bacterial species from over 20 genera including Pseudomonas among these biofilms [tpm ASV (up to 800) recovered in this study suggesting a strong ability of the tpm-harboring bacterial taxa at getting established in a river system. The treated WW (TWW) biofilms were made of about 100 to 300 ASV, and the 16S rRNA gene qPCR assays did not show significant differences in terms of total bacterial counts per investigated biofilm whatever their location and sampling period. Their contents varied between 1.41 × 105 to 1.8 × 107 16S rRNA gene copy numbers per g of biofilm (dry weight). Most of these biofilms were found to contain the HF183 marker indicative of the occurrences of significant exposures to Human fecal bacterial releases, and also of the DNA markers indicative of the occurrences of integrons that can spread ARGs. A comparison of these tpm ASV distribution patterns between samples was performed. NMDS ordinations of Bray-Curtis dissimilarities indicated significant differences between biofilm community patterns of the hospital (b-HTWW) and domestic lines (b-DTWW) and of the connected river. Previous analyses using denaturing gradient gel-electrophoresis (DGGE) also indicated such a differentiation of the hospital (b-HTWW) and domestic lines (b-DTWW) bacterial communities but suggested a lower diversity in the b-HTWW [tpm-metabarcoding approach implemented here rather indicated significantly lower Shannon indices for tpm-harboring bacteria among the domestic (b-DTWW) than the hospital (b-HTWW) and river biofilms. These investigations showed atenolol, diclofenac, propranolol, and trimethoprim concentrations to be higher in the biofilms of the domestic line (b-DTWW) of the Sipibel WWTP rather than of the hospital one. However, iohexol, ranitidine, levofloxacin, roxithromycin, and ketoprofen were found in significantly higher concentrations in the biofilms developing from the treated hospital WW. Furthermore, more antibiotics were globally found in the b-HTWW than in the b-DTWW. A biofilms . The rivtpm-harboring bacterial cells growing in the biofilms, 15 ASV  were found to be shared between the b-HTWW, b-DTWW and the river biofilms downstream (b-RD) the WWTP outflow. Otherwise, 13 ASV were strictly shared between the b-HTWW and b-RD (river biofilm downstream the WWTP) biofilms, and 40 between the b-DTWW and b-RD biofilms. In addition to these strict presence/absence distribution patterns, up to 67 tpm ASV were found to vary significantly between the b-HTWW and b-DTWW biofilms. Some of these showed very high fold changes between the two sewer lines such as ASV_6 (an unclassified Gammaproteobacteria)  that was found in much higher numbers in the hospital line biofilms (b-HTWW). On the opposite, ASV_84 (a P. anguilliseptica-like species) and more than 40 additional ASV were in significantly higher relative numbers in the domestic WW-related biofilms (b-DTWW). In order to further explain these differences, co-occurrences between the tpm-harboring species and pharmaceuticals were further investigated. Among the tpm metabarcoding libraries and pharmaceutical loads of the biofilms were observed. The phototrophic purple sulfur bacterium growing in the biofilms named L. purpurea was found to be the main tpm-harboring species showing distribution biases matching pharmaceutical concentrations. This species can use sulfur as the electron donor of its photosynthetic pathway [tpm-harboring species, S. humi, and A. popoffii, showed tpm read number distribution patterns rather indicative of a tropism for the hospital sewer system. The S. humi and A. popoffii tpm read numbers were found positively correlated to the higher concentrations of iohexol, levofloxacin, ranitidine, roxithromycin, and sulfamethoxazole found in the hospital biofilms. This could be related to the pathogenic nature of A. popoffii, and its implication in urinary tract infections [A. popoffii could thus be a potential indicator of hospital releases. The association of S. humi with the hospital sewer network could be related to its involvement in denitrification [tpm sequences of other Human opportunistic pathogens such as A. caviae, A. sobria, P. aeruginosa, P. flavescens, and P. putida were detected in this study, but their distribution patterns were not highly correlated to the monitored pharmaceuticals (Spearman correlation rho factors < 0.8). Nevertheless, P. aeruginosa read numbers were found to be negatively correlated to roxithromycin found in the hospital b-HTWW biofilms. This latter observation was further supported by the MPN growth assays. This is in line with the previous report showing roxithromycin to inhibit biofilm formation by P. aeruginosa when associated with other antibiotics [P. aeruginosa isolates showing multiple antibiotic resistances (up to 15 antibiotic resistances). Several positive correlations between the  pathway . Here, ifections . A. popofication . Furtheribiotics . Interestpm-bacterial taxa coming from the hospital and domestic lines in the build-up of the river biofilm bacterial communities were further investigated using a Bayesian source-sink tracking approach [tpm-harboring taxa among the river epilithic biofilms. Biofilms recovered at 10 m from the WWTP outlet showed up to 35% of their tpm ASV contents to have originated from the domestic sewer line (b-DTWW). Furthermore, hospital-borne tpm ASV (b-HTWW) were found to have contributed to the build-up of these communities. These b-HTWW taxa represented up to 2.5% of the epilithic biofilm tpm bacterial communities. Such signatures of sewer tpm ASV could even be recorded among the epilithic biofilms collected at 8 km from the WWTP outlet, and at percentages varying between 0.16 to 23% of the total tpm community. The observed differences in contributions of tpm-bacterial taxa between the sewer lines were likely related to the higher bacterial discharges coming from the domestic WWTP than the hospital one. The average discharge volumes coming from the DTWW network were estimated at 2198 m3/day while, from the HTWW one, they were estimated at 140 m3/day [3 of surface waters ). This indicates that, even if the Arve river can significantly dilute these exogenous taxa, some were still highly active and could efficiently colonize blueschist rock surfaces. A previous report indicated that shifts in river biofilm bacterial communities could be related to the impact of WWTP outflows but these changes were suggested to be driven by the released pharmaceutical pollutants [Contributions of the WWTP approach . This So0 m3/day . Interesllutants . Here, wtpm metabarcoding approach which allows an allocation of DNA imprints at the species/sub-species levels for more than twenty genera. This is the first report showing that the tpm marker can be used to assess bacterial diversity among river and sewer systems. This approach allowed us to show that the tpm-profilings of blueschist biofilms generated from treated WW (of clarifiers) were highly correlated to the accumulation of certain chemical pollutants. Chemical cocktails from the hospital and domestic sewers led to distinct tpm bacterial communities. These differences are likely to be related to the distinct functional abilities of these taxa at using or tolerating these pollutants. Wastewater treatment processes have been greatly improved over the years but still releases significant amounts of exogenous microbial cells and high concentrations of chemical pollutants. The incidence of these spillovers on natural aquatic systems remains to be investigated. Here, we have investigated the ability of WWTP clarifier sewer taxa at colonizing blueschist rocks in order to establish the likelihood of these taxa at getting established among the connected river system. This investigation was mainly performed through the use of the tpm-harboring bacterial taxa over the WWTP and their detection among the connected river system allowed us to apply a SourceTracker analytical scheme. This analysis showed a significant coalescence of the sewer tpm-harboring taxa among river epilithic biofilms. This study thus clearly demonstrated the ability of sewer taxa at colonizing inert surfaces of river systems. These taxa could harbor ARG, and be virulent and multi-resistant to antibiotics as observed for P. aeruginosa isolates recovered from the study site. The next step in these studies will be to investigate the evolution of resistomes and virulomes among these systems. Virulent properties might be beneficial for the colonization of highly competitive biotopes such as river rock surfaces. The large spread of


Chlamydia contains important obligate intracellular bacterial pathogens to humans and animals, including C. trachomatis and C. pneumoniae. Since 1998, when the first Chlamydia genome was published, our understanding of how these microbes interact, evolved and adapted to different intracellular host environments has been transformed due to the expansion of chlamydial genomes. This review explores the current state of knowledge in Chlamydia genomics and how whole genome sequencing has revolutionised our understanding of Chlamydia virulence, evolution, and phylogeny over the past two and a half decades. This review will also highlight developments in multi-omics and other approaches that have complemented whole genome sequencing to advance knowledge of Chlamydia pathogenesis and future directions for chlamydial genomics.The genus  The distinguishing feature of Chlamydia is its biphasic developmental cycle which alternates between extracellular infectious elementary bodies (EBs), which attach to and enter the host cell, and intracellular replicative reticulate bodies (RBs) residing in a membrane-enclosed inclusion. Upon RBs replication and inclusion growth, they dedifferentiate into EBs, to be released out of host cells and continue the infectious process  (Chlamydiaceae consists of two genera: 1) Chlamydia  species: Ca. Chlamydia corallus, Ca. Chlamydia ibidis, Ca. Chlamydia sanzinia and Ca. Chlamydia testudines  technologies and expansions in publicly available chlamydial genomes have dramatically increased our knowledge on chlamydial evolution and phylogeny, genome structure, metabolic processes, and potential virulence factors of these organisms. Presently, WGS is considered the gold standard for molecular epidemiology, evolution, and genetic diversity, and has become an integral part of cell biology studies in the genetically recalcitrant  process . Under ses (ABs) . The chles (ABs) . Currenthlamydia Figure 1studines  and, 2) volucris . The ava22.1Chlamydiaceae, culturing and isolation is laborious, generally yielding lower levels of chlamydial genetic material contaminated with host DNA. In the past decade, there have been advances in obtaining chlamydial genomes from contaminated and/or low-yielding DNA samples retrieved from clinical and environmental samples using non-targeted and targeted approaches. These developments have resulted in a substantial increase of WGS data being generated  DNA extracted from cultured isolates, direct next generation sequencing (NGS) is commonly used. Due to decreasing costs and ongoing developments in NGS, hybrid approaches such as nanopore sequencing to complement short-read WGS, are used to improve and/or provide closed complete genomes for hlamydia . In cont methods . One of  methods . This ap samples , livesto samples , DNA fro strains , as wellisolates  and DNA isolates . The rec regions . These t regions , while P regions . These nChlamydia and the microbiome; the microbiome has been shown to impact Chlamydia colonisation  and comparative approaches. Finally, a variety of phylogenomic analyses are performed to establish phylogenetic relationships among analysed strains and/or species  of most chlamydial genomes. Such hypothetical protein genes are conserved and considered “chlamydial-specific hypothetical protein genes”, with homologues commonly found among chlamydial species (Chlamydiae phylum as well as their closest relatives belonging to the Planctomycetes-Verrucomicrobiae-Chlamydiae (PVC) superphylum. Open-access ChlamDB provides various tools for comparing, analysing and retrieving Chlamydiae-specific genomic data  or partially conserved (~967 periphery genes), and only 19% of genes (~380 genes) unique to singular genomes. According to homology analyses, the periphery genes within species accounted for differences in organic molecule transport and metabolism, while unique genes contributed to differences in intracellular trafficking, secretion, and vesicular transport   .Chlamydiaceae possess several distinct polymorphic regions (pmps) and inclusion membrane proteins (Incs), Type III secretion system (T3SS), and other metabolic pathways, such as tryptophan biosynthesis , T3SS effector translocated actin-recruiting protein (tarP), pmp genes and the PZ , ~20 – 40 kb for C. abortus, C. psittaci and C. pecorum, (~15 to 20 genes), to ~55 kb and ~81 kb for C. trachomatis and C. muridarum (> 45 genes) , a variable number of phospholipase D-like genes (PLD), cytotoxin (tox) homologs, purine interconversion genes guaA and guaB, and a different subset of species-specific hypothetical proteins. Additionally, a near-full tryptophan (Trp) operon can be found in the PZ regions of C. caviae and C. felis, while in C. trachomatis and C. suis, the PZ regions only contain partial Trp operons  Figure 35 genes) . This re operons .accB and accC are common to all Chlamydia and are considered the 5’ boundary of the PZ, while other PZ genes vary between the species. Notably, chlamydial tox genes have significant homology to the large clostridial toxins (LCTs) and are present in almost all Chlamydia spp., however it may vary in copy number. C. muridarum has three tox copies, C. pecorum and C. suis two copies, while C. trachomatis, C. caviae, C. crocodile, C. felis, C. gallinacea, C. psittaci, C. buteonis, and avian C. abortus strains have one tox gene. A cytotoxin gene is absent from the PZs of the human pathogen C. pneumoniae and the ovine pathogen C. abortus , inner membrane components (e.g. Cds R/S/T/U/V and Cds L/N/Q), extracellular needles , chaperons , and a variable number of genetically diverse effectors , and is usually found in four clusters across the chromosome  is a functionally characterised nuclear membrane targeting protein . These expression differences correlated with specific LGV-mutations in the CT192 and CT214 promoters and within the CT059-CT058 transcript. These Inc sequence and expression differences may be associated with LGV strain tissue tropism to macrophages, possibly by inhibiting phagolysomal fusion  with multiple short repetitive motifs  and FxxN), a middle region and a C-terminal autotransporter β-domain. This autotransporter β-domain is responsible for translocating the protein to the bacterial surface , while others are more varied (such as pmpG and pmpE families). The subtype pmpG is the most expanded in gene copy numbers. Among chlamydial species, the number of pmp genes ranges between seven and nine genes in C. avium, and C. trachomatis, to 18 and 21 genes in C. psittaci and C. pneumoniae, accounting for approximately 14% of the coding capacity of their genomes  tracts. This may lead to random, high-frequency, on/off reversible switching of gene expression, involved in host adaptation and immune evasion , a ~40kDa surface-exposed porin protein containing four variable domains (VD I to VD IV), contributing to approximately 60% of the chlamydial outer membrane mass . These allow for the conversion of uridine monophosphate (UMP) to cytidine triphosphate (CTP). With the exception of C. trachomatis and C. muridarum, chlamydial genomes also contain the pyrE (orotate phosphoribosyltransferase) gene that encodes for uridine monophosphate synthetase (C. pneumoniae has a uridine kinase (udk) gene, which converts uridine or cytidine into UMP or CMP, respectively , guanosine triphosphate (GTP), thymidine triphosphate (TTP) and uridine triphosphate (UTP) for survival (Npt1), which converts UTP to CTP and provides an alternative pathway for Chlamydia to obtain ATP  and sodium-driven oxidative phosphorylation to generate its own ATP for energy or nucleic acid synthesis) and a hexose phosphate transporter, allowing Chlamydia to use glucose-6-phosphate as an energy source  stimulates the indoleamine-2,3-dioxygenase (IDO) enzyme to catabolise host tryptophan to kynurenine, essentially starving the invading organism. Due to this, IFN-γ treatment can be used for infection control , indole-3-glycerol phosphate synthase (trpC), phosphoribosylanthranilate isomerase (trpF), tryptophan synthase beta chain (trpB) and tryptophan synthase alpha chain (trpA). The complementary kynU and prsA encode for kynureninase and phosphoribosylpyrophosphate. However, C. suis and C. trachomatis have only partial trpR-trpBA genes, while the rest of the species lack all trp operon genes   intergenic region from trpBA, a recent study demonstrated that these could be independently transcribed and not necessarily expressed as a monocistronic transcript. Pokorzynski and colleagues showed that iron starvation can switch on the Trp salvage pathway, mediated by the iron-dependent repressor YtgR, which binds to an operator sequence within the trpR-trpBA intergenic region to repress transcription initiation from the alternative promoter for trpBA (A (near) complete and functional sittaci) . Interesheir PZs . Using aor trpBA .C. trachomatis, the trp operon has a loss of function due to a single nucleotide deletion and frameshift in trpA gene encoding a truncated tryptophan synthase alpha (TrpA) subunit. Conversely, the trp operon genes of C. trachomatis urogenital strains (D – K) are intact and functional, having the ability to produce tryptophan from indole, further allowing them to recover from IFN-γ exposure and resume their infectious cycle and this is supported by experimental studies  needed for de novo biotin synthesis. Other species, such as C. trachomatis, C. caviae and C. muridarum lack a functional biotin operon and thus depend on biotin salvaging , highly conserved, non-conjugative or integrative chlamydial virulence plasmid , and four tandem repeat sequences, with each iteration comprising of 22 base pairs near the origin of replication . Brieflyase gene . A recenectivity . Finallyectivity .C. trachomatis diagnostics, the chlamydial plasmid CDSs are useful targets for diagnostic testing due to their stability, and high copy number, with up to ten copies per genome  in the genomes  of ibiotics .Chlamydia spp. is the tetracycline resistance gene tetA(C) found in tetracycline-resistant C. suis strains, the only chlamydial species to have naturally obtained a resistance gene (tetA(C) gene encodes a tetracycline efflux pump which has been integrated as a genomic island (Tet-island) into the C. suis invasion-like gene (inv) on the chromosome. This integration most likely occurred during a transposition event directed by the transposase-encoding insertion sequence IScs605  (C. trachomatis L2/434 and chloramphenicol (Cam)-resistant C. muridarum VR-123. WGS of the recombinant clones identified examples of duplications, mosaic recombination endpoints, and recombined sequences that were not linked to the selection marker ) was reported in co-culture studies . Co-cult caviae) . Similarn marker . A more y of 28% . However5C. trachomatis circulating lineages within global populations . Instead, these genetically distinct strains clustered within lineages that were previously occupied exclusively by UGT isolates (namely genotypes D–K). These trachoma isolates appear to be recombinants with the C. trachomatis UGT genome backbones, where recombination was noted in ompA and pmp loci replacing them with those ompA and pmp genotypes characteristic of ocular isolates (C. trachomatis strains (serovar D and LGV). Recent outbreaks of LGV (L2b strain) within men who have sex with men (MSM) populations have resulted in genetic recombination of the ompA gene from non-LGV strains  that infect humans, parrots, and, most recently, horses. Within this highly clonal ST24 lineage, the equine, human and parrot strains differ by less than 200 single nucleotide variants (SNVs), evenly distributed around the highly conserved and syntenic chromosome (C. psittaci lineages (such as ST24 and pigeon-associated clade) SNVs and differences in gene content were noted in distinct chromosomal regions, including T3SS, ompA, Inc and pmp genes  or multiple conserved gene markers (e.g. multi locus sequence typing (MLST)) due to decreased costs. Genotyping using the full-length as well as fragments of the highly variable ompA gene is employed in genetic diversity studies for veterinary and human chlamydial infections, as it provides an initial molecular characterisation of the infecting strains  hosted on a platform that provides easy to use sequence and phylogenetic analyses. Furthermore, WGS studies are often supplemented with extended genotyping of samples using MLST due to high congruency with WGS phylogenetic clustering . GSMMs are mathematical models used to computationally describe the movement of metabolites within an organism. This model was then integrated with proteomic data to elucidate metabolic differences and altered flux between EBs and RBs  and has highlighted the issues around single gene sequencing to predict species evolution. In addition to enriching our understanding of Chlamydia, advances in genomics provides opportunities for rapid diagnosis of chlamydial infections and antimicrobial resistance detection using targeted single-gene nanopore sequencing or direct metagenome sequencing (The members of family e planet . With requencing . The advChlamydia hierarchical genome typing scheme based on core genome MLST or SNPs, such as those developed for C. trachomatis (Chlamydiae are still hidden, but with more and more genome-scale data published every day, our understanding of this complex and widespread bacterial species continues to improve.The increasing number of chlamydial genomes sequenced and in publicly available databases poses challenges for future genome analysis as phylogenetic trees become more computationally intensive to construct. Thus, the future development of a chomatis  will proConceptualisation: MJ, LL, GM. Formal analysis: LL, SP, VK, GM and MJ. Data analysis: LL, SP, VK and MJ. Writing, original draft preparation: LL and MJ. Writing, figure preparation,: LL, VK and SP. Writing, review and editing: LL, SP, VK, GM and MJ. All authors have contributed to the article and approved the submitted version.


UBC genes have been detected in several plant species, characterization of this gene family at the whole-genome level has not been conducted in Brassica napus. In the present study, 200 putative BnUBCs were identified in B. napus, which were clustered into 18 subgroups based on phylogenetic analysis. BnUBCs within each subgroup showed relatively conserved gene architectures and motifs. Moreover, the gene expression patterns in various tissues as well as the identification of cis-acting regulatory elements in BnUBC promoters suggested further investigation of their potential functions in plant growth and development. Furthermore, three BnUBCs were predicted as candidate genes for regulating agronomic traits related to oil content and yield through association mapping. In conclusion, this study provided a wealth of information on the UBC family in B. napus and revealed their effects on oil content and yield, which will aid future functional research and genetic breeding of B. napus.Ubiquitin-conjugating enzyme (UBC) is a critical part of the ubiquitin–proteasome pathway and plays crucial roles in growth, development and abiotic stress response in plants. Although  Ubiquitination is a crucial regulatory process for the selective protein degradation mechanism which regulates cell physiology through the ubiquitin-26S proteasome pathway in plants . Ubiquitvia transesterification  is a multistep reaction mediated by three enzymes, E1 , E2  and E3 (Ubiquitin-ligase enzyme) . Ubiquitfication . Subsequn system . Finallyn system .Most ubiquitin-like conjugating enzymes (UBLs) and E2s comprise a conserved catalytic core consisting of approximately 140-150 aa known as the UBC domain harboring the active site cysteine residue required for enzyme-ubiquitin . MoreoveUBCs usually form a multigene family and the number of UBCs in the multigene family is greater in the higher eukaryotes than in the lower eukaryotes, due to the expansion during the process of evolution , since they lack the active-site Cys residue, which is not active on their own  specializes in protein for ubiquitination in peroxisome maintenance  complex, which is involved in salt stress tolerance mediated by brassinosteroid (BR)  gene, resulting in postponed progression of disease symptoms, and limited reproduction as well as the growth of Septoria in wheat leaves   and in pt leaves . In Vitiesponses . In concBrassica napus  is a globally important oilseed crop, which is derived from the hybridization between Brassica rapa  and Brassica oleracea  followed by chromosome doubling approximately 7500 years ago  were obtained from the Genoscope database (http://www.genoscope.cns.fr/brassicanapus/) (B. rapa ‘Chiifu’ (v3.0) datasets were obtained from the database (https://bigd.big.ac.cn/gwh/Assembly/134/show) (B. oleracea ‘HDEM’ (broccoli) datasets were acquired from Bolbase database (http://www.ocri-genomics.org/bolbase/index.html) (https://www.ebi.ac.uk/interpro/) was applied as queries to perform HMM search against protein sequences of annotated genes using HMMER version 3.1 (http://hmmer.org/) (UBCs (predicted above) were utilized as queries to carry out BLASTP searches against the full-length protein sequences of 48 AtUBCs from The Arabidopsis Information Resource (TAIR) database (http://www.arabidopsis.org/) and 39 OsUBCs from Rice Genome Annotation Project (http://rice.plantbiology.msu.edu/downloads_gad.shtml) with E-value < 1e-5. The putative BnUBCs with hits of both AtUBCs and OsUBCs were deployed for further confirming the existence of the UQ_con domain using the Pfam (https://www.ebi.ac.uk/interpro/), SMART (http://smart.embl-heidelberg.de/) and CDD (https://www.ncbi.nlm.nih.gov/Structure/cdd) databases. The molecular weight (MW), isoelectric point (PI), instability index, aliphatic index and grand average of hydropathicity (GRAVY) of UBC proteins, were calculated using the ProtParam tool ExPASy (https://web.expasy.org/protparam/). The subcellular location of BnUBCs was predicted using Plant-mPLoc (http://www.csbio.sjtu.edu.cn/bioinf/plant-multi/#) (Genome sequence and annotation data of anapus/) . B. rapa34/show)  and B. oex.html) . The ubier.org/)  with E-ver.org/) . The amimulti/#) .B. napus in the Genoscope database (http://www.genoscope.cns.fr/brassicanapus/). The chromosomal distribution of BnUBCs was graphically represented using the RIdeogram package of the R software (https://github.com/TickingClock1992/RIdeogram) (BnUBCs gene structure was conducted by Gene Structure Display Server 2.0 (http://gsds.cbi.pku.edu.cn/) (http://meme-suite.org/tools/meme) with the following parameters settings: the maximum number of motifs, 10; minimum width of motifs, 6; maximum width of motifs, 100 aa; and E-value < 1e-10  and amino acid sequences were determined based on the genome annotation of deogram) . Multipledu.cn/) . Conserv < 1e-10 . MoreovelantCARE  for the B. rapa, B. oleracea, B. napus and A. thaliana, a phylogenetic analysis was performed. A phylogenetic tree was constructed applying MEGA 5.2 software (http://itol.embl.de/)  were identified by BLASTn searches of their CDSs based on two criteria: coverage of sequence length > 80%, and identity of aligned regions > 80% (https://github.com/qiao-xin/DupGen_finder)   was usedns > 80% . In addi_finder)  was emplUBC orthologous genes between B. napus and the other three species  was calculated according to their CDSs. In addition, to minimize errors, only the gene pairs with Ks < 1 were remained for further analysis  were collected from the NCBI SRA database (accession no. SRP136038) (BnUBCs were quantified based on their fragments per kilobase of exon per million reads mapped (FPKM) values using Cufflinks with default parameters (BnUBC genes were used to construct clustered heatmaps with TBtools (BnUBC genes was performed using the clusterProfiler package of the R software.The publicly available RNA-seq datasets of five different P136038) . The exprameters . Further TBtools . Then, GB. napus were applied to detect the natural sequence variations of BnUBCs  was applied as a query for searching against the protein dataset of B. napus. The peptides of assumed BnUBCs showing hits of both AtUBCs and OsUBCs were further employed to confirm the presence of the UBC domains by searching in the Pfam, SMART and CDD databases. In total, 200 BnUBCs were identified in B. napus (BnUBCs ranged from 168 bp (BnaA08g09170D) to 5,656 bp (BnaC07g05960D) with the deduced amino acid sequences varying from 55 aa (BnaA08g09170D) to 1,649 aa (BnaA07g03330D) (BnaA08g09170D) to 184.41 kDa (BnaA07g03330D), and their GRAVY and pIs ranged from -0.904 (BnaC04g10080D) to 0.112 (BnaA08g13930D) and from 4.19 (BnaA04g11090D) to 9.57 (BnaA09g09660D), respectively , while A03 and A05 harbored the highest of BnUBCs (11 each). The average number of BnUBCs in the Cn subgenome was 11.4, with the lowest number (5) on C09 and the highest number on C03. Hence, no biased tendency was observed between the two subgenomes. Furthermore, on each chromosome, BnUBCs were unevenly distributed, especially, since the genes on A06 and A08 were located at the ends.The chromosomal positions of detected ectively Figure 1UBC genes in A. thaliana, B. rapa, B. oleracea, and B. napus, a tree of phylogenetic was constructed based on the multiple sequence alignments of 48 AtUBCs, 93 BraUBCs, 95 BolUBCs, and 200 BnUBCs. All 200 BnUBCs could be categorized into 18 subfamilies and the number of groups was consistent with a previous report  and group VIII (ten BnUBCs) members were involved in RUB and SUMO conjugation pathways, respectively, and other three subgroups  contained the members lacking the Cys active-site (UEVs).To explore the evolutionary relationships among the s report   contained a single intron, while the others harbored multiple introns. BnaA07g03330D contained the most introns and exons. Besides, 33 of 200 BnUBCs lacked untranslated regions (UTR) at both ends or one end because of inaccurate annotation. The number of introns among the BnUBCs ranged from 1 to 26, and the length of introns ranged from 14 to 6,632 bp. Moreover, exon numbers inBnUBCs also varied widely across distinct subfamilies, ranging from 2 to 26. However, the majority of the members within the same subfamily tended to show similar intron-exon distribution patterns. For example, members of Group X generally possessed five exons, whereas those of Group XV, harbored eight exons. Therefore, the organization of introns and exons presented valuable evidence for the phylogenetic relationship among members of this gene family.Concerning the evolution of multigene families, the variety of gene structures provided an important resource . For expBnUBC genes  contained both CAAT-box and TATA-box elements, which usually existed in eukaryon. Moreover, the MYB element, which participates in the regulation of phenylpropanoid secondary metabolism in plants was identified in 192 out of 200 BnUBCs. The MYC element was identified in 183 of the 200, (91.50%) BnUBCs, which were involved in the regulation of plant growth and development as well as resistance to environmental stress and secondary metabolite synthesis. Furthermore, many BnUBCs contained light-responsive elements such as Box 4 element (part of a conserved DNA module involved in the light response), G-box element (cis-acting regulatory element involved in the light response), GT1-motif (light responsive element), and TCT-motif (part of a light responsive element) , tandem duplication as well as segmental duplication events  and transposed (17.4%) gene duplication events were primarily responsible for gene family expansion  event after divergence from A. thaliana  of BnUBC orthologous genes to BraUBCs, BolUBCs, and AtUBCs were calculated. The Ka/Ks less than one represents purifying selection, whereas Ka/Ks equal one indicates neutral evolution and Ka/Ks more than one represents positive selection  were less than one, suggesting that these genes were subjected to strong purifying selection  based on the mutational rate estimate, R = 1.5 × 10-8 synonymous substitutions per site per year , an essential ubiquitin-protein ligase, by targeting DUO POLLEN1 (DUO1). DUO1 upregulated the expression level of APC/C, which stimulates the production of miR159 -induced and ubiquitination-mediated degradation of DELLA , molecular function (MF), and cellular component (CC)  based on the previously published RNA-seq datasets of B. napus (BnUBCs were estimated with FPKM and displayed as a heatmap (BnUBCs showed relatively weak expression (FPKM < 1) and 24 BnUBCs were silience in any of the five tissues. The remaining BnUBCs showed high expression levels (FPKM ≥ 1), the majority of which expressed at a specific organ or differentially expressed in various tissues (BnaC06g16140D (ortholog of AT3G57870) presented the highest expression in all tissues, suggesting its critical roles in plant growth. Genes showing low expression levels (FPKM <1) across all five tissues could be regarded as pseudogenes  among the BnUBCs was calculated (17 SNPs/kb), whereas 13 SNPs/kb for the genes across entire genome. BnUBCs in the An subgenome contained slightly higher SNP density (20 SNPs/kb) than that in the Cn subgenome (14 SNPs/kb). Moreover, variations in SNP number between some paralogous gene pairs of BnUBCs were observed. For example, BnaA03g11080D possessed 65 SNPs, however, its paralog BnaC02g12440D contained no SNP. Moreover, the paralogs BnaA07g03330D/BnaC03g46750D, contained 235 and 33 SNPs, respectively. Based on the paired t-test, no significant difference was detected in SNP density between the BnUBC paralogs. Additionally, SNP annotation presented that 1,671 SNPs existed in the exon regions of BnUBCs and 600 SNPs lead to missense mutations.SNPs in a natural population with 324 entified  . Moreover, BnaC02g25260D was significantly associated with plant height    .Arabidopsis  are not correlated with the genome size . Increasing evidence suggest that segmental duplications may be the main factor responsible for the expansion of gene families in plants  and that form the basic functional links among the complex regulatory networks  were presented in most BnUBCs  cis-acting element functioned in the response to ABA stress  was approximately 4-fold higher than that of AtUBCs, while the number of BraUBC and BolUBC genes was <3-fold higher than that of AtUBCs, indicating gene loss in Brassica species during evolution  maintained six copies in B. napus and were not loss after WGD, implying their crucial roles in plant growth and development. In B. napus, the Ka/Ks ratios between UBC paralogs were obviously less than one, indicating that these genes were undergone purifying selection during evolution.Gene duplication is considered a major mechanism leading to gene family expansion and functional diversification . In planoleracea . Thus, tB. napus . Accordilication Table 1.volution . Moreovegenitors . NotablyBnUBCs localized to the nucleus, and only a few localized to the cytoplasm  to predict their possible functions. The RNA-seq data  was slightly higher than that of genes in the entire genome (13 SNPs/kb), suggesting that a large number of polymorphisms accumulated in BnUBCs during evolution. The SNP density of BnUBCs in the An subgenome was higher than that in the Cn subgenome, which is consistent with some other gene families in B. napus  are implicated in ABA responses and the ubiquitin-like SUMO protease 1 (ULP1) gene AtESD4 is involved in flowering time regulation , Really Interesting New Gene (RING) and U- box type and cullin-RING ligase (CRL)  . Thus, tin maize , 68 in sin maize  and 62 iin maize ; this faeviously .UBC family in B. napus. A total of 200 BnUBCs were identified and classified into 18 groups. The gene structures and motifs were highly conserved among members of the same phylogenetic subgroup. Moreover, cis-acting elements found in the BnUBCs promoters and the expression patterns of BnUBCs in diverse tissues demonstrated that these genes play a crucial role in plant growth and development. In addition, synteny analysis of the UBCs between B. napus and three ancestors  revealed the expansion history of the BnUBC gene family. Furthermore, genetic variations identification and association mapping analyses of BnUBCs uncovered their potential genetic effects on agronomic traits related to oil content and yield in B. napus. Overall, this study provided useful information about BnUBCs and will facilitate functional studies as well as the genetic breeding of B. napus in the future.In the present research, we conducted a comprehensive investigation of the 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 in the article/SY, CT, and XY designed the research. SY, HW, XL and PH performed the experiments. SY, MX, MH and XC analyzed the data. SY, CT, and XY wrote and revised the manuscript. All authors contributed to the article and approved the submitted version.