Glycine max (L.) Merr.]. Although these results have undoubtedly played a far-reaching role in the study of soybean biology, environmental interactions for complex traits in traditional GWAS models are frequently overlooked. Recently, a new GWAS model, 3VmrMLM, was established to identify QTLs and QTL-by-environment interactions (QEIs) for complex traits. In this study, the GLM, MLM, CMLM, FarmCPU, BLINK, and 3VmrMLM models were used to identify QTLs and QEIs for tocopherol (Toc) content in soybean seed, including δ‐Tocotrienol (δ‐Toc) content, γ‐Tocotrienol (γ‐Toc) content, α‐Tocopherol (α‐Toc) content, and total Tocopherol (T-Toc) content. As a result, 101 QTLs were detected by the above methods in single-environment analysis, and 57 QTLs and 13 QEIs were detected by 3VmrMLM in multi-environment analysis. Among these QTLs, some QTLs (Group I) were repeatedly detected three times or by at least two models, and some QTLs (Group II) were repeatedly detected only by 3VmrMLM. In the two Groups, 3VmrMLM was able to correctly detect all known QTLs in group I, while good results were achieved in Group II, for example, 8 novel QTLs were detected in Group II. In addition, comparative genomic analysis revealed that the proportion of Glyma_max specific genes near QEIs was higher, in other words, these QEIs nearby genes are more susceptible to environmental influences. Finally, around the 8 novel QTLs, 11 important candidate genes were identified using haplotype, and validated by RNA-Seq data and qRT-PCR analysis. In summary, we used phenotypic data of Toc content in soybean, and tested the accuracy and reliability of 3VmrMLM, and then revealed novel QTLs, QEIs and candidate genes for these traits. Hence, the 3VmrMLM model has broad prospects and potential for analyzing the genetic structure of complex quantitative traits in soybean.Genome-wide association studies (GWAS) is an efficient method to detect quantitative trait locus (QTL), and has dissected many complex traits in soybean [ Glycine max (L.) Merr.] is an important crop, and provided a great source of protein, oil, vitamin, and other nutrients for humans around the world. As one of the functional nutrients of soybean, tocopherol (Toc) has strong antioxidative capabilities and benefits to human health. It can scavenge free radicals in the body and increase immune function  is a powerful genomics tool, and it can base on natural populations to detect quantitative trait locus (QTL) underlying complex quantitative traits . GWAS haThe general linear model (GLM) , the mixRecently, a novel model was presented, named 3V multi-locus random-SNP-effect mixed linear model (3VmrMLM) . It is aThe material used in this study included 175 diverse soybean accessions Table S1via specific locus amplified fragment sequencing (SLAF-seq) (MseI (EC: 3.1.21.4) and HaeIII (EC: 3.1.21.4)  were used to obtain more than 50,000 sequencing tags, each 300-500 bp in length. The obtained markers were evenly distributed in unique genomic regions of the 20 soybean chromosomes. The short oligonucleotide alignment program 2 software (SOAP2) was used to align the raw paired-end reads to the soybean reference genome. Based on over 58,000 high-quality SLAF labels from each test sample, raw reads from the same genomic location were used to define SLAF groups. Genotypes were considered heterozygous if the minor allele depth or total allele depth of the sample was greater than 1/3  . The digthan 1/3 .2) for estimating the degree of LD between pair-wise SNPs (MAF ≥ 0.05 and missing data ≤ 10%) was calculated by TASSEL 5.0  was performed using the genome association and prediction integrated tool (GAPIT) R package to analyze the population structure of the natural panel . The linSSEL 5.0 . Unlike https://cran.r-project.org/package=qqman) and “CMplot “ (https://github.com/YinLiLin/R-CMplot).In total, 23,149 polymorphic SNP markers and 175 tested accessions were used to perform GWAS, it was performed using six models, including three single-locus model: MLM, GLM, CMLM, and three multi-locus models: FarmCPU, BLINK, 3VmrMLM. Among these, the GLM, MLM, CMLM, FarmCPU, and BLINK models were implemented with the R package “GAPIT” and visualization used scripts from the R package “qqman” (https://github.com/YuanmingZhang65/IIIVmrMLM). In this study, we used the single environment and multiple-environment methods to identify QTLs and QEIs. The significant threshold value was determined by LOD score ≥ 4.The significant threshold value for the association between SNP and traits were determined by -log10 (P) ≥ 4, which is equivalent to P ≤ 0.0001, for MLM, GLM, CMLM, FarmCPU, and BLINK. The R software IIIVmrMLM  of the 3http://www.soybase.org) (https://www.soybase.org/goslimgraphic_v2/dashboard.php). In addition, the whole genome and QEIs candidate genes among soybean relatives were compared using OrthoVenn2 (https://orthovenn2.bioinfotoolkits.net/task/create) (Candidate genes located in the 200-kb genomic region (100 kb upstream and 100 kb downstream) of each significant or suggested QTL then identified and annotated the candidate genes with the soybean reference genome  . The gen/create) .P < 0.01.Genome resequencing data were used to select the SNP variations within candidate genes. These SNP were located in exonic, intronic regions, upstream and downstream regions. Then, we combined the phenotype values of 56 soybean germplasms in three environments, these soybean germplasms were selected from the 175 diverse soybean accessions Table S1https://cran.r-project.org/package=Phenotype) in R package. For each Toc component, haplotypes containing 18 soybean germplasms accessions were used for comparative analysis. One-way ANOVA and Two-tailed unpaired t -test were used to compare the differences in TC-BLUP value among the haplotypes. Finally, we compared the individual or total Toc content among these different haplotypes.The haplotypes were classified based on all of the SNPs with an MAF >0.05 in each candidate gene. Best linear unbiased predictors (BLUP) value were calculated using the “Phenotype” (http://ipf.sustech.edu.cn/pub/soybean/), which integrated all publicly available RNA-Seq soybean libraries    . Then, w  .−ΔΔCT method (Glyma.12G063400) was used as an internal control for data normalization. Primer sequences for candidate genes were obtained from the qPrimerDB database . First-strand cDNA was synthesized from total RNA using TIANScript RT kits . And qRT-PCRs were performed using SYBR Green  reagents on an ABI 7500 fast real-time PCR platform. All qRT-PCRs were performed in three independent repeats, and the relative levels of transcript abundance were calculated using the 2T method . The GmAdatabase Table S2database .Descriptive statistical analysis of phenotypic data including mean, minimum, maximum, coefficient of variation (CV), heritability, skewness, and kurtosis was performed using IBM SPSS statistics 25.0 . One-way ANOVA with Dunnett’s multiple comparisons test and unpaired two-tailed t-test were performed using GraphPad Prism 9.4.1.Statistical analysis showed a wide range of phenotypic variations in the levels of the individual and total Toc content of the 175 soybean accessions from Harbin, Liaoning, and Jilin in 2021 Table 1.The genotyped samples included 175 soybean germplasms (including landraces and elite cultivars). The genomic DNA of these 175 accessions was sequenced using SLAF-seq. A total of 23,149 high-quality markers  were identified from 153 million paired-end reads with 45 bp-read lengths and the sequencing depth was about 6.5 fold. The number of SNPs varied across the 20 soybean chromosomes. The highest number of SNPs was observed in Chr.18 (1732) and the lowest was detected in Chr.11 (685)  or LOD score= 3, 4, 5, 6, 7, 8, and 9) for testing six GWAS models and counted the number of QTLs detected . A total of 4537 SNPs with MAF ≥ 0.05 were identified among 248 candidate genes. Among them, a total of 50 SNPs from 11 candidate genes were found to reach the threshold with -log10(P) ≥ 2.0 , RNA-Seq data analysis was done. The result showed that the expression levels of the 11 candidate genes in low and high Toc content germplasms were different. Among them, Glyma.17G188700 can regulate α-Toc content in soybean seeds. The range of the expression levels of Glyma.17G188700 in higher α-Toc germplasms was much higher than those of lower. Other genes regulate Toc content as shown in Glyma.01G054800, Glyma.09G032100, and Glyma.10G171600 can regulate both the γ-Toc and Total-Toc content. Glyma.09G032100 in higher γ-Toc and total-Toc germplasms were much higher than those expression levels of lower. However, Glyma.01G054800, and Glyma.10G171600 in higher γ-Toc germplasms have higher expression levels, but in higher total-Toc germplasms have lower expression levels. Moreover, these candidate genes results of qRT-PCR are consistent with the RNA-seq data  . How imp3VmrMLM is a new algorithm, different from other algorithm, the 3VmrMLM use single-marker genome-wide scanning to select potentially associated markers and uses empirical Bayes and the likelihood ratio test in a multi-locus model to identify significant QTLs, this undoubtedly improves its detection capability . AdditioGlyma.06G038000 encoded alpha/beta-Hydrolases superfamily protein. Glyma.01G054800 encoded plant proteins of unknown function, Glyma.03G186500 encoded a WD-40 repeat family protein, Glyma.20G235800 encoded a WD40 repeat-like superfamily protein, Glyma.03G186200 is a RAB GTPase homolog C2A, Glyma.10G171600 encoded a RAB GTPase homolog A5A, Glyma.17G188700 encoded transposas, Glyma.09G032100 encoded a myb domain protein, Glyma.20G235100 encoded an indeterminate domain protein, Glyma.20G235400 encoded a P-loop containing nucleoside triphosphate hydrolases superfamily protein. Of these genes, Glyma.01G054800 and Glyma.10G171600 are the most special, and these two genes are higher expressed in higher γ-Toc content germplasms, but lower expressed in higher total-Toc content germplasms. The soybean oil contains a higher proportion of γ-Toc, this is very different from the other oil crops , the Chinese National Natural Science Foundation , National Key Research and Development Program of China , the Youth and Middle-aged Scientific and Technological Innovation Leading Talents Program of the Crops (2015RA228), the National Ten Thousand Talent Program (W03020275), Postdoctoral Scientific Research Development Fund of Heilongjiang Province , Program on Industrial Technology System of National Soybean (CARS-04-PS06).This study was conducted in the Key Laboratory of Soybean Biology of the Chinese Education Ministry, Soybean Research & Development Center (CARS) and the Key Laboratory of Northeastern Soybean Biology and Breeding/Genetics of the Chinese Agriculture Ministry.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Bemisia whiteflies on cassava in eastern Democratic Republic of Congo (DRC). Bemisia tabaci transmits viruses responsible for devastating epidemics of cassava mosaic and brown streak diseases. KASP SNP genotyping of B. tabaci specimens collected from cassava in revealed the existence of four haplogroups, while phylogenetic analysis of mitochondrial COI sequences showed the presence of two major clusters of B. afer. This study provides important information on the genetic diversity of B. tabaci and B. afer in eastern DRC and emphasizes the need for continuous monitoring of whitefly populations on cassava to guide the strategic application of management practices that reduce the impact of cassava virus diseases throughout DRC and the wider Central Africa region.We report here the first detailed characterization of Bemisia tabaci and Bemisia afer from cassava in eastern Democratic Republic of Congo (DRC). The Mitochondrial COI sequencing revealed the occurrence of six cassava B. tabaci mitotypes, which were designated into four haplogroups  using KASP SNP genotyping. SSA-ECA (72%) was the most prevalent and occurred in the northern part of the surveyed area, in the Ituri and Nord/Sud-Kivu provinces, whilst SSA-CA (21%) was present in the south, primarily in Haut-Katanga. SSA-ECA was predominant in the areas of north-eastern DRC most severely affected by cassava brown streak disease and was also reported in the new outbreak area in Pweto territory, Haut-Katanga, in the south. Bemisia afer comprised two major clusters with 85.5% of samples in cluster one, while the rest were in cluster two, which has no reference sequence in GenBank. This study provides important information on the genetic diversity of B. tabaci and B. afer in eastern DRC. This knowledge will be used as a basis for further studies to understand and to identify the role of whitefly haplogroups, their population densities and consequences for virus epidemics and spread as well as leading to improved vector and virus management strategies.The present study characterizes  Bemisia tabaci cryptic species complex, may cause major crop losses through the transmission of plant viruses [Whiteflies  comprise more than 1500 species worldwide ,3,4. In  viruses  and are  viruses ,7,8.Bemisia tabaci and B. afer. The greatest damage is caused by B. tabaci through the transmission of cassava mosaic begomoviruses (CMBs) [B. tabaci not only are associated with severe virus epidemics in cassava but also cause physical damage through sap sucking and secretion of honeydew, which lead to the proliferation of sooty mould that impairs photosynthesis [Cassava plants in Africa are colonized by several whitefly species, but the most predominant are s (CMBs) ,10 and cs (CMBs) ,12. Thess (CMBs) ,14. Supeynthesis .Bemisia tabaci comprises many morphologically similar populations but with distinct mitotypes (phylogenetic classification based on COI sequencing) that have been identified based on sequences of the mitochondrial cytochrome oxidase I (COI) gene [B. tabaci in Africa has been categorized, based on COI sequences, into five mitotypes, named sub-Saharan Africa 1 to 5 (SSA 1-5) [COI is not effective at distinguishing the major genetic groupings of cassava B. tabaci in Africa. All the known mitotypes occurring on cassava were reassigned into the six SNP-based haplogroups: sub-Saharan Africa East and Central Africa (SSA-ECA), sub-Saharan Africa East and Southern Africa (SSA-ESA), sub-Saharan Africa Central Africa (SSA-CA), sub-Saharan Africa West Africa (SSA-WA), sub-Saharan Africa 2 (SSA2), and sub-Saharan Africa 4 (SSA4). A Kompetitive allele specific PCR assay (KASP) has been developed to distinguish the six major SNP-based haplogroups [OI) gene ,17. CassSSA 1-5) ,19,20. SSSA 1-5) . SSA1-SGSSA 1-5)  with theSSA 1-5) . Other mSSA 1-5) ,23,24. RSSA 1-5) ,26 usinglogroups .Bemisia tabaci is known to transmit over 300 economically important plant viruses, including begomoviruses, criniviruses, carlaviruses, torradoviruses, and ipomoviruses [B. tabaci as the vector of CBSIs, B. afer is not a vector of these viruses [B. tabaci genotypes occur across this geographical range [B. tabaci haplogroups have not been undertaken. The only comparison of the transmission of CMBs by B. tabaci whiteflies from different parts of Africa showed that there were no significant differences in transmission efficiency [oviruses . While v viruses ,29. The Bemisia afer is a species complex that is known worldwide and colonizes host plants that belong to over 22 families, including cassava [B. tabaci from various countries in Africa [B. afer accounts for less than 20% of the whiteflies collected from cassava compared to B. tabaci [B. tabaci. Based on COI sequencing, two B. afer genotypes have been reported on cassava in Africa, and these were distinct from those found in other parts of the world [ cassava ,32. Althn Africa ,34,35, iB. tabaci using mitochondrial COI sequencing and the newly developed KASP diagnostic [The eastern part of DRC is currently being affected by severe epidemics of CBSD that are expanding to previously unaffected regions ,37. Theragnostic . This reCOI sequencing, and KASP genotyping.Adults of cassava-colonizing whiteflies were collected from the shoot tips of 3–7-month-old cassava plants during surveys carried out in five provinces of DRC  from 2016 to 2018. Samples were collected from 106 cassava farmer fields at intervals of 5–10 km along motorable roads traversing each sampling area. At least 50 adult whiteflies  were collected per field from cassava plants randomly selected at nearly regular paces covering all sections of the visited field. The insects were immobilized in 95% ethanol and transferred into 1 mL screw cap vials before being transported to the laboratory at the International Institute of Tropical Agriculture (IITA)-Kalambo and stored in the freezer at −20 °C. The whiteflies were subsequently sent to IITA-Tanzania where they were processed for DNA extraction, PCR, 2, 0.45% Tween-20, 0.01% Gelatine, and 60 µg/mL Proteinase K. The mixture was then vortex shaken, spun down, and immediately incubated on ice for 15 min. This was followed by incubation at 55 °C in a water bath for 30 min. The lysate was stored at −20 °C for downstream use. For PCR use, the lysate was diluted using sterile Diethyl pyrocarbonate (DPEC)-treated water in a ratio of 1:9. The samples from each province out of the 212 were Haut-Katanga (56), Ituri (42), Nord-Kivu (40), Sud-Kivu (50), and Tanganyika (24).DNA was extracted separately from two female adult whiteflies that were selected from each vial, representing a single farmer’s field, making up to 212 insects selected in total. The insects were macerated in 20 µL of lysis buffer in a 1.5 mL Eppendorf tube. The lysis buffer contained 10 mM Tris-HCl (pH 8.0), 50 mM KCl, 2.5 mM MgClCOI was amplified using one set of primers, 2195-Bt-F (5′-TGRTTTTTTGGTCATCCRGAAGT-3′) and C012-Bt-sh2-R (5′-TTTACTGCACTTTCTGCC-3′) [COI gene. The PCR reaction contained 1X QuickLoad Master Mix , 1 mM MgCl2, 0.24 µM of each primer, 2 µL DNA, and sterile distilled water to achieve the desired reaction volume of 25 µL. PCR was carried out at 95 °C for 5 min initial denaturation of template DNA, followed by 35 cycles at 94 °C for 40 s, 56 °C for 30 s for annealing, and 72 °C for 90 s for extension, with a final extension at 72 °C for 10 min. The PCR products were run on a 1% agarose gel in 1×TAE buffer stained with GelRed . DNA bands were visualized while using a Gel Doc XR+ Gel Documentation System. Out of the 212 samples, 200 generated clear bright bands of PCR products, which were sent to Macrogen Inc.  for purification, and direct sequencing in forward and reverse directions. DNA sequences were manually edited using Ridom Trace Edit v1.1.0 . One hundred eighty-three samples out of the two hundred had good sequences suitable for phylogenetic analysis. The sequences were assembled into contigs using CLC Main Workbench 7.0.2 . Multiple alignments of the edited sequences were performed using ClustalW in MEGA version 7.0.26 [COI sequences were included in the phylogenetic tree for comparison with previously published mitotypes. The number of B. afer haplotypes (phylogenetic classification of COI sequences with 100% nucleotide identity) was determined using Dna-SP 6.12.03 [A partial fragment of TGCC-3′) . These pn 7.0.26 , and theB. tabaci into the six haplogroups. This assay is only currently applicable to cassava-colonizing B. tabaci and not on other cryptic species or B. afer.The KASP assay currently uses six sites/SNPs to designate cassava-colonizing B. tabaci by COI sequencing were tested using KASP with a set of six primers , as described in Wosula et al. [Whiteflies that were designated as cassava a et al. . Conventa et al. . The KASKASP genotyping was performed in a Stratagene MX 3000P . The following cycling conditions were used: Stage 1: 30 °C 60 s (pre-read); Stage 2: 94 °C for 15 min hot-start Taq activation (1 cycle); Stage 3: 94 °C for 20 s, 61 °C  for 60 s (10 cycles); Stage 4: 94 °C for 20 s, 55 °C for 60 s (29 cycles); Stage 5: 94 °C for 20 s, 57 °C for 60 s (3 cycles); and Stage 6: 37 °C for 60 s  followed by an end-point fluorescent read. These conditions were used for four primers , while Stage 3: 94 °C for 20 s, 68 °C  was used for two primers: BTS613 and BTS46-203. The quality of genotyping cluster plots was visually assessed and only samples in distinct clusters with respective positive controls were considered for manual SNP calling using the MxPro software incorporated into the Stratagene MX 3000P unit.B. tabaci whiteflies. Geo-referenced co-ordinates for sites that were surveyed for whitefly abundance and CBSD incidence in 2016 and 2018 based on previously published data [Geo-referenced coordinates for samples successfully designated by KASP SNP genotyping were used to generate maps using ArcGIS 10.1 . Maps were produced illustrating the geographic distributions in eastern DRC of SNP-based haplogroups (KASP) data for cassava hed data  were useCOI for 200 whitefly samples generated 183 good sequences, out of which 100 were cassava B. tabaci (Haut-Katanga (21), Ituri (26), Nord-Kivu (16), Sud-Kivu (35), and Tanganyika (2)) and 83 were B. afer tabaci (Haut-Katanga (32), Ituri (10), Nord-Kivu (15), Sud-Kivu (13), and Tanganyika (13)). The phylogenetic tree of cassava B. tabaci showed three distinct mitotypes  of cassava B. tabaci. The major SSA1 mitotype had four sub-groups, which were SSA1-SG1 (74%), SSA1-SG1/SG2 (2%), SSA1-SG3 (1%), and SSA1-SG2 (17%). SSA2 accounted for 4% while SSA4 was 2%  using KASP, except for a single sample that was not distinctly placed. SSA-ECA made up 72% of the samples. The SSA-ECA haplogroup (72 samples) mainly occurred in two provinces—Sud-Kivu (44.4%) and Ituri (31.9%)—while the remaining 22.2% were in Nord-Kivu and 1.4% in Haut-Katanga. SSA-CA comprised 21% of the 100 samples. The SSA-CA haplogroup (21%) occurred mainly in Haut-Katanga province (85.7%), while the remaining 14.3% were found in Tanganyika and Sud-Kivu. The haplogroup SSA-ESA had only two samples with one each in Sud-Kivu and Haut-Katanga provinces. There were four samples of SSA2, all in Ituri province. One sample from Haut-Katanga was not clearly distinguished. The SNP haplogroups map illustrates the predominance of SSA-ECA, which, apart from one sample, was restricted to the three northerly provinces of Ituri, Nord-Kivu, and Sud-Kivu, while SSA-CA was restricted to the two southerly provinces of Tanganyika and Haut-Katanga. Other SNP haplogroups with less than five samples each were SSA2 (Ituri), SSA-ESA (Sud-Kivu/Haut-Katanga), and SSA-ECA/CA (Haut-Katanga) (The 100 whiteflies identified as cassava Katanga) .B. tabaci was beyond the scope of this study, recently published data on CBSD epidemiology in eastern DRC demonstrate the greater abundance of B. tabaci in areas where CBSD incidence is higher  identified were 78% for Tanganyika, 54% for Haut-Katanga, 43% for Nord-Kivu, 24% for Sud-Kivu, and 27% for Ituri. The phylogenetic tree of 83 samples shows two major clusters of B. afer . ClusterB. afer . B. aferB. afterCOI sequences revealed the existence of five haplotypes, with one haplotype having a matching reference sequence, AF418673 from Uganda. This made up 49.4% of the samples. The other four haplotypes did not have any matching sequences in the database and can therefore be considered novel haplotypes. One of the haplotypes with 12 samples is a distinct cluster, with only 86.4% nucleotide similarity to samples in cluster one and the reference sequence AF418673. A total of 15 selected sequences that represent the five haplotypes of B. afer found in this study have been submitted to GenBank under the following accession names: MT985999-MT986013.A haplotype analysis of Bemisia tabaci in five provinces in eastern DRC. This is of significance since this is the part of Africa where there is the most active spread of CBSD, which is considered one of the world’s most dangerous crop diseases [COI sequencing  and the SSA1 subgroups  reported in this study are consistent with what has been found for cassava-colonizing B. tabaci in other cassava growing regions/countries in sub-Saharan Africa [This study reports, for the first time, a detailed picture of the genetic diversity of cassava-colonizing diseases . The thrn Africa ,22,23,24B. tabaci across Africa [B. tabaci genotypes overlap.The KASP genotyping of samples in this study further revealed the need to adopt this technique as a diagnostic assay for cassava s Africa . The curs Africa ,26,27. PBemisia tabaci continues to be one of the most important agricultural pests in Africa as it transmits CMBs and CBSIs that cause major crop losses in cassava-production systems. Eastern DRC represents the ‘frontline’ in the westwards and southwards spread of CBSD [B. tabaci haplogroups in order to relate their occurrence with the risk of CBSD spread. However, earlier evidence has shown that cassava viral epidemics are associated with high abundances of whiteflies [ of CBSD ,37. Ther of CBSD . Althougiteflies ,43 and titeflies . A studyiteflies .B. afer whitefly populations in cassava-growing territories in eastern DRC. It reveals the existence of two major clades of B. afer on cassava in DRC. Two clades of B. afer were previously reported in samples from Malawi, Tanzania, and Uganda [B. afer in Africa, where a greater focus has been placed on B. tabaci due to the magnitude of damage caused through the transmission of CMBs and CBSIs. Although there has been much less research attention on B. afer compared to B. tabaci, it is nevertheless important to have an improved understanding of this species, both since it can be readily confused with B. tabaci and since it is known to be an economically important viral vector in other cropping environments, transmitting the crinivirus, the sweet potato chlorotic stunt virus found in sweet potatoes in Peru [B. afer comprises approximately 45% of the whiteflies collected on cassava in eastern DRC and is predominant in the provinces of Tanganyika and Haut-Katanga compared to cassava B. tabaci. Changes in virus/vector affinities can occur as both evolve over time, and new viruses can be introduced to cropping systems where they did not previously occur. It is therefore important for future studies to monitor viral transmission by the identified species and haplogroups within those species. The findings from the study reported here contribute to improving knowledge of whitefly cryptic species in some of the most important cassava-growing regions of sub-Saharan Africa and provide vital baseline knowledge to help track current and future viral epidemics and support virus- and vector-management strategies to control those epidemics.This study reports, for the first time, the genetic diversity of d Uganda . This is in Peru . SequencB. tabaci in eastern DRC. The COI sequencing, which has been used in most studies, designated these whiteflies into mitotypes previously reported in other countries, with SSA1-SG1 as the most predominant. KASP SNP-genotyping revealed the existence of four haplogroups of cassava-colonizing B. tabaci whiteflies with the two most abundant, SSA-ECA and SSA-CA, as the most predominant in the northern and the southern parts of the region, respectively. The northern region dominated by SSA-ECA is also the part of DRC most affected by spreading CBSD epidemics. This study also reports the detailed characterization of B. afer on cassava, another common whitefly species that is largely ignored. However, knowledge of its dynamics, genetic characteristics, and distribution are important for researchers conducting research on cassava whiteflies, which collectively are some of the most economically important insect species on the African continent. The findings from this study significantly expand the knowledge of cassava-colonizing whiteflies and their relationship with ongoing viral epidemics and contribute important baseline information for the development of virus vector management strategies.This study presents in detail the diversity of cassava-colonizing


Albugo occidentalis, is one of the major yield-limiting diseases of spinach (Spinacia oleracea) in some major commercial production areas, particularly in southern Texas in the United States. The use of host resistance is the most economical and environment-friendly approach to managing white rust in spinach production. The objectives of this study were to conduct a genome-wide associating study (GWAS), to identify single nucleotide polymorphism (SNP) markers associated with white rust resistance in spinach, and to perform genomic prediction (GP) to estimate the prediction accuracy (PA). A GWAS panel of 346 USDA (US Dept. of Agriculture) germplasm accessions was phenotyped for white rust resistance under field conditions and GWAS was performed using 13 235 whole-genome resequencing (WGR) generated SNPs. Nine SNPs, chr2_53 049 132, chr3_58 479 501, chr3_95 114 909, chr4_9 176 069, chr4_17 807 168, chr4_83 938 338, chr4_87 601 768, chr6_1 877 096, and chr6_31 287 118, located on chromosomes 2, 3, 4, and 6 were associated with white rust resistance in this GWAS panel. Four scenarios were tested for PA using Pearson’s correlation coefficient (r) between the genomic estimation breeding value (GEBV) and the observed values: (1) different ratios between the training set and testing set (fold), (2) different GP models, (3) different SNP numbers in three different SNP sets, and (4) the use of GWAS-derived significant SNP markers. The results indicated that a 2- to 10-fold difference in the various GP models had similar, although not identical, averaged r values in each SNP set; using GWAS-derived significant SNP markers would increase PA with a high r-value up to 0.84. The SNP markers and the high PA can provide valuable information for breeders to improve spinach by marker-assisted selection (MAS) and genomic selection (GS).White rust, caused by  Spinacia oleracea L.) is one of the important vegetable crops in the world economically, which was estimated to average $490 million (fresh and for processing) per year during 2018–20 in the United States (US), with 97% of the value for the fresh market  > 4.0 either in SMR, GLM, or MLM  in this article.).GWAS was performed in a two step process. In the first step, 2 357 260 SNPs were used to perform GWAS implementing single marker regression (SMR), GLM (PCA), and MLM (PCA + K) methods in TASSEL 5 . Howeverhttps://doi.org/10.6084/m9.figshare.17283194) distributed on the six spinach chromosomes  , and LOD value of 5.42 was used as significance threshold based on the 13 235 SNPs in this study.http://www.spinachbase.org/). Our emphasis was to find analogs of disease resistance genes near the significantly associated SNP markers.Genes were searched within 50 Kb on either side of significant SNPs of the spinach Sp75 genome annotation at the SpinachBase site (The ridge regression best linear unbiased prediction (rrBLUP) method was used to perfrom GP using the rrBLUP package  in R VerGP for white rust resistance was performed in 346 spinach accessions based on ratios of training / testing sets, number of SNPs, and GP models. (1) GP was performed using nine different ratios of training / testing sets, 2 fold (1:1), 3-, 4-, 5-, 6-, 7, 8-, 9-, and 10-fold (9:1) across three sets of SNPs: (i) all 13 235 SNPs, (ii) 40 SNP markers, and (iii) 9 SNP markers (GWAS-derived SNP markers). (2) Eight different SNP number sets from 9 SNPs to 4846 SNPs were used to estimate GP by BL for three SNP sets: (i) Set.13235SNP, (ii) Set.4836SNP_select, and (iii) Set.8839SNP.random. (3) GP was estimated with nine GP models, BA, BB, BL, BRR, SVM, RF, rrBLUP, gBLUP, and cBLUP, in cross-prediction for white rust resistance among seven SNP sets . These seven SNP sets were selected based on results obtained and information provided in the result section. In addition, GWAS-derived SNP markers for GP were analyzed and discussed.The PA for the tested models in this study was estimated by calculating the average Pearson’s correlation coefficient (r) between the GEBVs estimates from the training set and white rust phenotypic values in the validation set or testing set , 53, 69.The white rust disease showed signs and symptoms on leaves, and the disease severity was recorded using the 0 to 10 disease scale . The scaAmong the 346 spinach accessions, 23 showed white rust resistance with a rate 3 or below , indicatThe genetic diversity analysis among the 23 accessions showed that (1) the accessions from the same country were located at neighbor each other with less genetic distance in the phylogenetic tree in most cases; (2) two clusters were grouped: the five accessions, PI 227045, PI 165994, PI 175311, PI 433210 and PI 648949 from Iran, China and India as one group, and other 18 accessions as another group; and (3) In group I, the four accessions, PI 207518, PI 220686, PI 211632, and PI 212120 had different genetic base from others as I-outlier , Table 1Based on PCA and phylogenetic analysis when PCA = 2 to 10 by GAPIT 3 in the 346 spinach accessions with 8399 randomly selected SNPs distributed on six chromosomes, two sub-populations (clusters) were the most clearly divided in the GWAS panel of the 346 accessions . The GWABased on 2-cluster, Q1 and Q2 consisted of 301 (87.0%) and 45 (13.0%) accessions, respectively, nevertheless, based on 3-cluster (G1 to G3), there were 301 (87.0%) G1, 26 (7.5%) G2, and 19 (5.5%) G3 accessions, respectively . Combini10(p)] distributions in QQ-plots showed a large divergence from the expected distribution  and its standard error (SE) from the 100 runs for each combination are listed in ) displayed in charts created by R package divided by two models: left half from BL (Bayesian LASSO) and right half from rrBLUP, and grouped by the nine folds with three SNP sets  in each SNP set using the same model, either BL or rrBLUP . There were 24 combinations for GP analysis, consisting of eight SNP number sets selected from three SNP groups. Each GP analysis was run for 100 times to calculate GP statistical parameters and r values. The average r-value (r) and SE of 100 runs for each GP combination are presented in the GP was performed with eight different SNP number sets  selected from three different SNP groups in cross-predictions for white rust resistance using BL model in three SNP sets: Set.13235SNP, Set.4836SNP.select, and Set.8839SNP.random  decreased when decreasing the SNP number  was 0.79 when 4836 SNPs were used and decreased to 0.25 when 9 SNPs were used. In the Set.4836SNP.select, the average r-value (r) was 0.82 when 4836 SNPs were used and decreased to 0.31 when 9 SNPs were used. In the two SNP groups, the r-value was higher than 0.50 when 100 SNPs or more were used. But the average r-value (r) was very low in the Set.8839SNP.random of the SNP group; ranged from 0.19 to 0.07; and the highest was only 0.19 when 4836 SNPs were used : > = 0.82 in all.13235-SNP set; > = 0.73 in the 40-SNP marker set; and > =0.59 in the 9-SNP marker set. The other three models, SVM, RF, and rrBLUP, still had a high average r-value (r) > =5.2 in the all.Nine GP models  were used to conduct GP for white rust resistance among seven SNP sets: all, 40 m, 9 m, 40r, 9r, 40rr, and 9rr, where all signifies all 13 235 SNP set; 40 m is the 40 SNP markers in the  values in the four random sets , suggesting that we can’t use a small SNP number randomly selected from a million SNP set in GS for white rust resistance.SNP set. SVM and RF have r-value > = 0.63 in the 40-SNP marker, and > =0.47 in 9-SNP marker set, but rrBLUP had a low value with 0.38 and 0.25, respectively , Fig. 7,) were observed when using the GWAS-derived SNP marker sets: > = 0.73 in 40-SNP marker set (m40) and > =0.59 in 9-SNP marker set (9 m) across the six GP models   , Fig. 7.P models , Fig. 7,White rust is a non-culturable oomycete pathogen making it difficult to screen and select spinach genotypes for resistance. Currently, no efficient method has been developed to evaluate white rust resistance in greenhouse or growth chamber conditions as disease severity among known resistant and susceptible genotypes is difficult to discriminate in a single disease cycle . Therefot-test. Forty SNP markers were associated with white rust resistance with LOD >5.42 in one of the six tested MLM models . After combining analysis of the six models in GAPIT 3 and three models in TASSEL 5, nine SNPs located on chrs 2, 3, 4, and 6 were relatively consistent across the models and were selected as the associated SNP markers for white rust resistance in this study  were used to conduct GWAS by implementing multiple models, including six models in GAPIT 3, three models in TASSEL 5, and is study . Awika eIn this study, a total of 121 genes were identified to be located within 50 Kb distance from the 40 associated SNP markers . ThirteeDespite the success of GWAS in identifying genetic loci associated with several agronomic and disease resistance-related traits, it will be challenging to pinpoint the causal gene in each of these loci. A successful GWAS only identifies probable genomic regions but requires subsequent characterization for validating the actual identification of causal relationship with disease using proteomics/ transcriptional profiling. Given the complexity and nature of the white rust, most genes identified in our study, whether a given gene is likely to be involved in determining a resistant phenotype alone would need cloning individual genes in the appropriate genetic background. Most verified plant disease resistance genes isolated to date contain a nucleotide-binding site and leucine-rich repeat (NBS-LRR) domains- similar to the one we identified in this study. Activated NB-LRRs represent a tip of the signaling cascade that triggers defense responses and not the causal genes defining the resistance alone. It will be impulsive to correlate expression patterns of the identified candidate genes and disease reaction. The percent variation (R-square%) explained by individual SNP  shows th) in each SNP set using the same model, either BL or rrBLUP  to 10-fold (9:1) had similar, although not identical, averaged r values : > = 0.82 in all.13235-SNP set, > = 0.73 in the 40-SNP marker set, and > =0.59 in the 9-SNP marker set. The three models, SVM, RF, and rrBLUP, still had high average r-value (r) > =5.2 in the all SNP set, > = 0.63 in the 40-SNP marker, and > =0.47 in 9-SNP marker set, but rrBLUP had low value with 0.38 and 0.25, respectively  with the smallest SE  had similar high average r-value  decreased when decreasing the SNP number  was 0.79 when 4836 SNPs were used and decreased to 0.25 when 9 SNPs were used. In the Set.4836SNP.select, the average r-value (r) was 0.82 when 4836 SNPs were used and decreased to 0.31 when 9 SNPs were used. In the two SNP groups, the r-value was higher than 0.50 when 100 SNPs or more were used. However, the average r-value (r) was very low in randomly selected set: Set.8839SNP.random, which was randomly selected from 217 531 SNPs (4.06%); ranged from 0.07 to 0.19  than the randomly selected SNP sets in all of the tested GP models  and S8. In this study, 346 USDA spinach germplasm accessions were phenotyped for white rust resistance under field conditions; 23 accessions showed white rust resistance or intermediate resistance with a disease rate 3.0 or less based on 0–10 scale; and the seven accessions, NSL 6098, PI 175311, PI 220686, PI 224959, PI 226671, PI 227045, and PI 648958 showed the highest white rust resistant levels with a score of 2.0 or less, indicating their suitability as parents in breeding programs to develop white rust-resistant hybrids and cultivars. Genome-wide association study (GWAS) was performed in the 346 accessions with 13 235 SNPs and identified nine SNPs, chr2_53 049 132, chr3_58 479 501, chr3_95 114 909, chr4_9 176 069, chr4_17 807 168, chr4_83 938 338, chr4_87 601 768, chr6_1 877 096, and chr6_31 287 118, located on chromosomes 2, 3, 4, and 6 associated with white rust resistance. Genomic prediction (GP) was tested for prediction accuracy (PA) using Pearson’s correlation coefficient (r) between the genomic estimation breeding value (GEBV) and the observed values. High averaged r values were observed in each SNP set using different GP models and up to 0.84 when using GWAS-derived significant SNP markers. The SNP markers and the high PA can provide valuable information for breeders to improve spinach by marker-assisted selection (MAS) and genomic selection (GS).Web_Material_uhac069Click here for additional data file.


Salmonella enterica serovar Gallinarum biovar Pullorum (S. Pullorum), a septicemic pathogenic bacterium of poultry due to high mortality of chicks or poults, could not only result in a high mortality rate among embryos and chicks, but also lead to persistent infection and transmission to eggs or progeny in adult chickens during the carrier state. Diseases caused by Salmonella infection via vertical transmission continue to pose a highly significant threat to both human and animals; however, research on phage therapy regarding the vertical transmission of Salmonella is currently lacking. In this study, we evaluated the effect of Salmonella phage CKT1 on controlling the vertical infection of S. Pullorum by detecting the bacterial load in the reproductive system, eggshells and liquid whole eggs of adult broiler breeders. The results showed that the oral use of phage CKT1 could effectively reduce the colonization level of S. Pullorum in various organs including liver, spleen, heart, ovary and oviduct of adult breeders. More importantly, phage treatment significantly decreased the Salmonella-specific IgG level in serum of infected chickens, and reduced the bacterial load in eggshells and liquid whole eggs, thus decreasing the probability of vertical transmission of S. Pullorum in poultry. In addition, the total bacterial load in the poultry breeding environment was also significantly reduced after phage therapy, probably due to the decrease in the Salmonella load in cecal contents and restoration of the intestinal microbiome in chickens.Salmonella. As facultative intracellular parasites, Salmonella could spread by vertical transmission and pose a great threat to both human and animal health; however, whether phage treatment might provide an optional strategy for controlling bacterial vertical infection remains unknown. Herein, we explored the effect of phage therapy on controlling the vertical transmission of Salmonella enterica serovar Gallinarum biovar Pullorum (S. Pullorum), a poultry pathogen that causes economic losses worldwide due to high mortality and morbidity. A Salmonella phage CKT1 with lysis ability against several S. enterica serovars was isolated and showed that it could inhibit the proliferation of S. Pullorum in vitro efficiently. We then evaluated the effect of phage CKT1 on controlling the vertical transmission of S. Pullorum in an adult broiler breeder model. The results demonstrated that phage CKT1 significantly alleviated hepatic injury and decreased bacterial load in the liver, spleen, heart, ovary, and oviduct of hens, implying that phage CKT1 played an active role in the elimination of Salmonella colonization in adult chickens. Additionally, phage CKT1 enabled a reduction in the Salmonella-specific IgG level in the serum of infected chickens. More importantly, the decrease in the S. Pullorum load on eggshells and in liquid whole eggs revealed that phage CKT1 effectively controlled the vertical transmission of S. Pullorum from hens to laid eggs, indicating the potential ability of phages to control bacterial vertical transmission.Phage therapy is widely being reconsidered as an alternative to antibiotics for the treatment of multidrug-resistant bacterial infections, including salmonellosis caused by  Salmonella enterica serovar Gallinarum biovar Pullorum (S. Pullorum) can produce an acute systemic disease with severe gastrointestinal illness in young chicks followed by a high mortality rate. However, it rarely causes such severe clinical disease in adult chickens . The T-cell response to f laying , which le system . TherefoSalmonella-free broiler breeders  at 22 weeks old were authorized by Yisheng  and strictly transported to avoid any contamination. Chickens were randomly divided into two groups (10 chickens/group). Each group was housed in a separate 20-square-meter room more than 50 m apart with wood shavings and waterlines by different experimental personnel to avoid cross-contamination. All experimental chickens were determined to be free of S. Pullorum infection via weekly Salmonella isolation from anal swabs before this experiment [S. Pullorum CVCC526 (1.8 × 109 CFU) in 200 μL of PBS by injection into the breast muscle, and those in Group 2 were injected with PBS buffer only , the serum was collected from two groups of chickens, then the Group 1 chickens were divided into an S.P group  and an S.P + Phg group  with 5 chickens in each group, whereas Group 2 chickens without infection were divided into a Con group (control group) and a Phg group (only phage treated). To avoid any contamination of Salmonella or phages, the four groups were housed in separate air-filtered isolate cabinets  in a well-ventilated room with four compartments of approximately 10 square meters.A total of 20 periment . ChickenS.P + Phg group were treated orally with a single dose of phage (1 × 108 PFU/chicken) in a total volume of 1 mL, whereas the chickens in the Con group and S.P group were orally inoculated with the same volume of sterile SM buffer. All chickens were maintained at an age-appropriate temperature for 6 days and monitored daily for clinical signs and egg collection. At day 6 post phage treatment, all chickens from each group were weighed, and blood was collected from the brachial wing vein. Then, chickens were sacrificed by cervical dislocation, and the liver, spleen, heart, ovary, follicle, and oviduct were taken for subsequent enumeration of Salmonella.At the times designated as day 1 and day 2 , the chiS. Pullorum infection in adult breeders, the serums of hens at day 0 and day 6  with the method described at http://www.ID.vet.com. Besides, the S. Pullorum-specific antibody was also determined by the slide agglutination test using commercialized agglutination antigens .To determine the effect of phage treatment on the prevalence of nd day 6  were colS. Pullorum load. Three suspected S. Pullorum colonies for each sample were identified by polymerase chain reaction (PCR) assays using a specific target gene ipaJ [To determine bacterial loads in the liver, spleen, heart, ovary, follicle, and oviduct, tissue samples were weighed and homogenized in 1 mL of PBS buffer . The dilene ipaJ .S. Pullorum load in eggshells, the method developed by Al-Ajeeli et al. was used with a slight modification [Salmonella colonies were counted and identified per the method above.To quantify the fication . BrieflyS. Pullorum in cecal contents was determined using real-time-quantitative polymerase chain reaction (qPCR) with S. Pullorum-specific SEP1 gene primers . Total DNA was extracted from the cecal contents of all chickens at day 6 using Nabil et al.’s method with slight modifications [4 to 108 CFU of cells and tested by qPCR with the same conditions as the unknown samples. The standard was included in all PCR runs, and the S. Pullorum load in samples was quantified with CFU/g.The load of ications . BrieflyThe total bacterial load in the air was quantified by the open-plate method with a slight modification . Brieflyp < 0.05.GraphPad Prism 9.0.0 software was used for data analysis. The data of bacterial load in tissues, eggshell, and liquid whole egg were statistically analyzed by the Mann–Whitney test. For the bacterial load in the air and the ratio of organs to bodies, one-way analysis of variance (ANOVA) and post hoc Tukey’s test were performed. Significance was determined at S. Pullorum lytic phage CKT1 was observed to produce clear plaques with diameters ranging from 4.0 to 5.0 mm in 8 h  even at MOI of 0.0001. However, at all tested MOIs, phage titer could be increased to approximately 1010 PFU/mL, indicating its strong replication ability and lytic activity against S. Pullorum and potential for phage therapy , belonging to the lication A. Phage a phages B. In addSalmonella, we constructed an adult broiler chicken model with S. Pullorum CVCC526 by pectoral injection at the onset of sexual maturity  on eggshells and 44% (4/9) in liquid whole eggs . Likewise, the slide agglutination test showed that 100% of chickens were positive for S. Pullorum at 6 d, whereas the positive rate of Salmonella-infected chickens was surprisingly decreased to 40% at 6 d post-phage therapy  ; this may indicate that phage CKT1 affects the spleen and liver of adult chickens.ificance A, indica < 0.01) B, while Salmonella colonization in the chickens’ liver, spleen, heart, and cecum during the early stages of infection was quantified. As shown in S.P group, the S. Pullorum load in the liver, spleen and heart in the S.P + Phg group decreased by nearly 83.1%, 94.4% and 89.7%, respectively. The S. Pullorum load in the above three organs in the Con group and Phg group could not be detected. Thus, these data indicated that phage CKT1 could reduce the S. Pullorum load in tissues and might further alleviate injury to the liver and spleen. Then, we utilized qPCR to quantify the S. Pullorum load in cecal contents. As shown in S. Pullorum load in the S.P + Phg group decreased significantly (p < 0.05) compared to the S.P group, indicating that phage CKT1 could also reduce colonization of S. Pullorum in the cecum of adult chickens.Next, the effect of phage treatment on S. Pullorum persists within the ovary and oviduct of hens after sexual maturity, which leads to the occurrence of vertical transmission. Thus, the effect of phage CKT1 to limit the vertical transmission of S. Pullorum was examined. As shown in S.P group, phage treatment significantly reduced the S. Pullorum load in the ovary and oviduct from below the detection line, and no S. Pullorum could be re-isolated from the ovary and oviduct in the S.P + Phg group, suggesting the elimination of S. Pullorum in the reproductive system with the use of phage CKT1. No S. Pullorum contamination was detected in both the Con and Phg groups.S. Pullorum in eggs, there is likely to be a failed hatching process and vertically infected chicks; therefore, we also detected the S. Pullorum load in liquid whole eggs. As shown in S. Pullorum load of the S.P + Phg group decreased significantly (p < 0.05). Meanwhile, the isolation rate of S. Pullorum in the S.P group significantly decreased from 55% (6/11) to 11% (1/10) (p < 0.05) , and the isolation rate of S. Pullorum decreased significantly from 82% (9/11) in the Con group to 30% (3/10) (p < 0.01) (For  < 0.05) . In addi < 0.01) .Salmonella infection caused an approximately 32.5-fold and 23.3-fold increase in the total bacteria load in the air at both day 3 and day 6, respectively, while phage treatment significantly decreased the total number of bacteria at 3 d (p < 0.001) and 6 d (p < 0.0001), respectively.To examine the effect of phage treatment on poultry breeding environments, the total number of bacteria in the air were detected at day 3 and day 6. As shown in S. Pullorum in both the productive organs and various tissues, thus effectively controlling the risk of vertical transmission to eggs. We also demonstrated that phage treatment significantly inhibited the total number of bacteria in the air, thus further protecting the eggshell from Salmonella contamination. In addition, the reduction in S. Pullorum on the eggshell might prevent Salmonella penetration to eggs, resulting in a reduced risk of vertical transmission [Here, we confirmed that phage CKT1 could reduce the number of smission ,31.S. Pullorum can mediate the formation of Salmonella-containing vacuoles (SCVs) in macrophages for immune escape, leading to the liver, spleen, and other organs being colonized by S. Pullorum [S. Pullorum in the spleen was lower than in the liver, ovary, and oviduct, probably due to the role of the immune system in eliminating S. Pullorum [S. Pullorum in the heart of adult chickens in the S.P group was the same as the result found by Wigley et al. and Shen et al., which showed that S. Pullorum colonization in the heart would disappear with infection time [S. Pullorum in chick liver and spleen on day 6 post-infection [Salmonella loads in organs. The absence of S. Pullorum in the ovary and oviduct for the use of phage CKT1 indicated that phage therapy was able to control the colonization level of S. Pullorum in the reproductive system. Currently, little is known about how phages cross the intestinal barrier and reach other organs including the reproductive tract of chickens. Despite a recent study showing that the oral administration of phage had a minimal effective on systemic dissemination in mice [S. Pullorum in the cecum might provide a carrier for phage CKT1 to be transported across the intestinal barrier to enter macrophages by invading Salmonella cells, thus being successfully transferred to other organs [S. Pullorum in the reproductive organs was that phage CKT1 reached the reproductive tract relying on transcytosis or on the bacterial host acting as a vector. The recently discovered phage SHWT1 [Salmonella, implying that phages can be used to clear the S. Pullorum colonized in macrophage. So, another possible explanation is that phage treatment reduced the load of S. Pullorum in the macrophage of liver and spleen, which might lead to a failed transfer of Salmonella to the productive organs.After the invasion of host cells, Pullorum . HoweverPullorum . In addiion time ,14. Howenfection . Success in mice , but forr organs . In addir organs . Thus, tr organs . A possige SHWT1  appears Salmonella serovars and has a narrower host range than Salmonella phage STP4-a and PVP-SE1 [Salmonella-specific IgG antibody levels. However, antibody can usually exist in the blood for 2–12 weeks; this confusing result and the reason for reduced Salmonella-specific IgG antibody level should be explored further.At present, phage therapy has provided a relatively new tool for addressing diseases caused by bacterial infections in humans, animals, and plants . However PVP-SE1 ,40. Curr PVP-SE1 ,42. It h PVP-SE1 . Majewsk PVP-SE1 . In thisSalmonella infection caused an increase in the total number of bacteria in poultry breeding environments, and phage therapy significantly reduced the total bacterial load. We previously demonstrated that S. Pullorum infection could result in remarkably increased Escherichia-Shigella and Klebsiella becoming the predominant bacterial taxa, while phage CKT1 treatment significantly reduced their populations in intestine and promoted the proliferation of beneficial microbiota in Firmicutes, thereby further alleviating the body weight loss of infected chicks [Salmonella and Escherichia that easily form aerosol particles, and phage lysis on Salmonella in cecal contents and restoration of normal gut flora reduced the number of these bacteria in feces, which in turn leads to a decrease in total bacteria load in the poultry breeding environment. Another thing worth noting is that the chicken breeders without any Salmonella contamination used in this study were so expensive that only five adult chickens at the onset of sexual maturity in each group, which might not be sufficient to provide convincing analytical results. The present study provides a glimpse into the possibility of phage treatment on the vertical transmission of Salmonella, and related research still need further, in-depth investigation.In addition, we found that d chicks . So, we S. Pullorum in both the productive organs and various tissues of adult broiler breeders, thus decreasing the probability of vertical transmission of S. Pullorum.Altogether, our data demonstrated that phage therapy could effectively reduce the colonization level of


The antioxidant capacity and redox potential of these betaxanthins were compared to those of model betaxanthins derived from dopamine, l-DOPA , and pyrrolidine and structure–property relationships were established by using matched molecular pair analysis and a model developed using a genetic algorithm. Either a phenol or indole moiety enhance the antioxidant capacity of betaxanthins, which is overall much higher than that of their amino acid precursors and standard antioxidants, except for the cysteine-betaxanthin. The one-electron oxidation of amino acid betaxanthins produces radicals stabilized in multiple centers, as demonstrated by quantum chemical calculations.Betaxanthins are natural products with high antioxidant and anti-inflammatory properties. Here, we describe the semisynthesis of twenty-one betaxanthins derived from proteinogenic amino acids, including the elusive betaxanthin of  The gradual increase in oxygen levels in the atmosphere forced primordial living organisms to fixate amino acids capable of meeting the challenges posed by reactive oxygen species to their cells . Tryptopl-tyrosine-derived water-soluble pigments that impart color to most plants of the Caryophyllales order  juice submitted to alkaline hydrolysis .HPLC-ESI-qTOF-MS/MS data were acquired using a Shimadzu 20A liquid chromatograph equipped with an SPD-20A PDA detector and coupled with a Bruker Daltonics MAXIS 3G ESI-qTOF mass spectrometer, operating in the positive ion mode. The betaxanthins were analyzed with an Ascentis C18 column  at 1 mL min1H NMR spectra of betaxanthins were recorded using a Bruker Avance III 500 spectrometer, operating at 500 MHz at 298 K. The zgpr pulse program (presaturation) was used to suppress the residual water signal. Solutions were prepared in D2O  immediately before spectral acquisition. Chemical shifts are reported as δ values (ppm) referenced to trimethylsilyl propionate (TSP) or D2O. All spectra were processed using the software MestReNova .•+ assay was performed according to the protocol of Re et al.  by potassium persulfate (2.45 mmol L−1) in the dark at room temperature for 16 h. The stock solution of ABTS•+/ABTS was diluted in phosphate buffer pH 7.0 (0.1 mol L−1) or acetate buffer pH 3.6 (0.3 mol L−1) to an absorbance of 0.7 (46.7 μmol L−1 ABTS•+) at 734 nm. The kinetics of bleaching of ABTS•+ after the addition of antioxidant were monitored by a change in the absorption at 734 nm for 6 min (ΔA) at 25 °C. The slope of the linear correlation between ΔA and the concentration of antioxidant, α, is a measure of antioxidant capacity. Consequently, the αsample/αTrolox ratio is the Trolox equivalent antioxidant capacity, TEACABTS.The TEAC/ABTSe et al. . A stock−1 solution of TPTZ  in 40 mmol L−1 aqueous HCl, 2.5 mL of a 20 mmol L−1 solution of FeCl3⸱6H2O in water, and 25 mL of 0.3 mmol L−1 acetate buffer pH 3.6. The assay was performed by measuring the change in the absorption at 593 nm for 30 min (ΔA) at 37 °C due to the reduction of the ferric-tripyridyltriazine (Fe(III)-TPTZ) complex to its ferrous form (Fe(II)-TPTZ) upon the addition of the antioxidant. The slope (α) of the linear correlation between ΔA and the antioxidant concentration was measured. The antioxidant capacity was calculated as the ratio between the value of α for the sample and for the antioxidant standard Trolox (1–5 µmol L−1 concentration range), αSample/αTrolox, and is reported as TEACFRAP.The ferric-reducing antioxidant power (FRAP) was determined using the protocol developed by Benzie and Strain . The FRA−1, analyte concentration: 1 mmol L−1 in aqueous KCl (0.1 mol L−1) at pH 7.0.Cyclic voltammograms were acquired at 25 °C using a Metrohm Autolab PGSTAT101 potentiostat/galvanostat, controlled using the proprietary software NOVA. A screen-printed carbon working electrode  with a carbon auxiliary electrode and a silver reference electrode was used; potential range: −0.4 to 1.0 V, scan rate: 50 mV strans and (S)-C6 configurations and submitted to a conformational search using quantum chemical GBSA/GFN2–xTB methods, as implemented in the Conformer–Rotamer Ensemble Sampling Tool   and their iso stereoisomers ((R)-C6), as well as the isolation or synthesis of a single cis/trans diastereoisomer, is unproductive because betaxanthins and other imines isomerize in aqueous solution [ product ,61,62,63 product . The ressolution ,66,67. TAmino acid betaxanthins are high-capacity antioxidants. Antioxidant capacity and activity assays performed in vitro contribute to the overall understanding of the mechanisms of antioxidant action and to establishing structure–property relationships, although their results do not necessarily reflect or explain the complex behavior and effectiveness of antioxidants in vivo [ in vivo . Any ant in vivo . Results in vivo ,70. TherAlthough amino acid betaxanthins have been found in vegetables and fungi ,34,53,71–-oxidation gives the stable dehydroascorbic acid. Trolox 1e–-oxidation produces a resonance stabilized radical that, upon further 1e–-oxidation yields a closed-shell quinone. Therefore, it is apparently easy to explain why Trolox can scavenge two radicals per molecule, as determined by many independent groups after the seminal work of Ingold and collaborators [l-DOPA. The phenol substituent of Tyr, however, influences the TEAC at pH 7.0 but not under acidic conditions, suggesting that deprotonation enhances its antioxidant capacity. Last, the pH effect on the peak potential and peak current of Pro-Bx suggests the existence of a pKa of around 6, a fact that cannot be easily rationalized considering the estimated pKas of betaxanthins  and catechol (O–H) moieties enhance the antioxidant capacity of betaxanthins. Although many endogenous antioxidants contain nitrogen and sulfur moieties, most natural and artificial exogenous antioxidants are phenols [•+ as a reference. In fact, the spin density of betaxanthins show TEAC and Ep,a values similar to those of Gly-Bx and highlight that, considering all orbitals and the population of α and β electrons, the highest spin density is located within the 1,7-dAhM system. However, a comparison of SOMO and LUMO revealed that those betaxanthins with higher antioxidant capacity and lower Ep,a have a lower SOMO–LUMO gap and the SOMO is localized mostly in the substituent at the α-C, while the LUMO is delocalized throughout the 1,7-dAhM system. Analysis of orbital surfaces revealed that the 1,7-dAhM system behaves mostly as two imine groups instead of an iminium–enamino polymethine system. Most importantly, the sulfur atom in Cys-Bx induces a node in C8 that jeopardizes the conjugation in the enamine function of the 2-thiazoline ring, possibly affecting its ability to stabilize and interact with radicals. Therefore, this analysis revealed that ionization resulting in SOMO and LUMO delocalized in different portions of the molecule are related to a higher antioxidant capacity and lower Ep,a. phenols . This no phenols ,82. Cons phenols ,84,85. B phenols ,62,86,87 phenols . The 1,7 phenols ,88,89. HThe cysteine-betaxanthin has poor antioxidant capacity. The characterization of Cys-Bx revealed that initial betaxanthin formation is followed by intramolecular cyclization leading to a thiazolidine ring that is oxidized in a 2e−,2H+ process to produce a 2-thiazoline ring, as inferred by mass spectrometry and 1H NMR spectroscopy analysis. This result has major biological implications since it is the first evidence that betaxanthins are susceptible to the nucleophilic attack of thiol nucleophiles, including the side chain of cysteine residues in peptides and proteins, which can lead to the formation of adducts. Although it is unclear how the final oxidation takes place, Cys-Bx does not scavenge ABTS•+ or undergo SET with the ferric-tripyridyltriazine complex. The poor antioxidant capacity of Cys-Bx and the similarity between its structure and that of Gly-Bx, except for the CH2S group closing the heterocyclic ring, suggests that the S atom compromises the formation of a stable radical or radical cation by oxidation of Cys-Bx. It is unlikely that Cys-Bx is formed upon use of cysteine to preserve processed beetroots and the natural occurrence of this compound is yet to be verified.ABTS, 7.0 and the TEACABTS, pH 3.6 of the betaxanthins derived from proteinogenic amino acids show modest linear correlation, as evidenced by a coefficient of determination (R2) of 0.80. The same is observed when comparing the TEACABTS, 7.0 with TEACFRAP, pH 3.6 (R2 = 0.76) and the TEACABTS, 3.6 with TEACFRAP, 3.6 (R2 = 0.82). Values of TEAC also show a poor linear correlation with the Ep,a (R2 < 0.5). Dwyer correlated the electronic properties of amino acid side chains, mostly inductive and field effects described by the σI, σR, σα, and σF parameters, with their influence in the structure of proteins [Ep,a of amino acid betaxanthins. Using a genetic algorithm parameterized with MKS changes of N1, N9, and all COOH, HOMO and LUMO energies, the HOMO–LUMO gap, the σI, σR, σα, and σF parameters for amino acid side chains, and Ep,a, we could determine a linear model that fits the TEACABTS, pH 7.0 data reasonably well; TEACABTS, 7.0 = 2.420 − 0.004 Ep,a − 4.120 × ELUMO − 4.420 MKS-N1, R2 = 0.91. Such models provide clues on which parameters, among those selected for the analysis, are important for the problem in hand. Therefore, the anodic peak potential, the energy of the LUMO, and the MKS charge of the N1  seem to be inversely correlated with the TEAC of amino acid betaxanthins at pH 7.0.The antioxidant capacity and peak potentials of amino acid betaxanthins are not correlated with the electronic properties of their amino acid precursors. The TEACproteins . These pThe reaction of amino acids with betalamic acid produces betaxanthins whose antioxidant capacity is much higher than that of their amino acid precursors, which may represent an evolutive advantage for organisms submitted to oxidative distress. This effect is general, except for the previously unknown Cys-Bx, which is a poor antioxidant in vitro and has not been identified in vivo. The presence of ionizable side chains containing a catechol (O–H) or an indole (N–H) substituent increase the antioxidant capacity of betaxanthins by favoring their oxidation at multiple centers, which always include the 1,7-diazaheptamethinium system. Trp-Bx is an efficient antioxidant in vitro that has been found in Opuntia fruits ,92, but


Moreover, genotyping-by-sequencing (GBS) was performed on all genotypes and generated in 16,966 SNP markers which were used for genetic association analysis using single-marker analysis. The analysis identified 27 significant SNPs distributed across all seven chromosomes that were associated with LS resistance. One SNP (S6_17854595) was located within the HORVU6Hr1G010050 gene model that encodes a protein kinase domain-containing protein . A TaqMan marker (0751D06 F6/R6) for the Un8 gene was tested in the diverse collection. The results indicated that none of the Egyptian genotypes had the Un8 gene. The result of this study provided new information on the genetic control of LS resistance. Moreover, good resistance genotypes were identified and can be used for breeding cultivars with improved resistance to Egyptian LS. Loose smut (LS) disease is a serious problem that affects barley yield. Breeding of resistant cultivars and identifying new genes controlling LS has received very little attention. Therefore, it is important to understand the genetic basis of LS control in order to genetically improve LS resistance. To address this challenge, a set of 57 highly diverse barley genotypes were inoculated with Egyptian loose smut race(s) and the infected seeds/plants were evaluated in two growing seasons. Loose smut resistance (%) was scored on each genotype. High genetic variation was found among all tested genotypes indicating considerable differences in LS resistance that can be used for breeding. The broad-sense heritability (H Hordeum vulgare L.) is one of the most important cereal grains grown in temperate climates. It has been used for animal feed (as a grain or as fodder) and human nutrition (as a component of various foods). During its life cycle, barley suffers from many biotic and abiotic stresses which affect its yield. Loose smut (LS) (caused by the basidiomycete pathogen Ustilago nuda (Jens.) Rostr. (U. nuda)) is one of these important diseases. This disease has been reported in 1.3–11.7% of fields in Egypt [Triticum aestivum L.). Barley  examine the genetic variation among Egyptian and spring barley genotypes in their resistance to Egyptian LS races, (2) identify putative SNP markers and genomic regions associated with LS resistance to be used in marker-assisted selection for loose smut resistance in barley, and (3) select the most resistant genotypes which could be used in breeding programs to genetically improve LS resistance for Egyptian barley production.A total of 62 highly diverse spring barley genotypes were included in this study. The seeds of 60 genotypes were obtained from the Agriculture Research Center (ARC), Egypt, and two from the United States Department of Agriculture (USDA), USA. The complete list of the genotypes and the pedigree is represented in U. nuda spores collected from the Egyptian fields in the previous years with 1 L of distilled water [The genotypes were inoculated with the Egyptian race(s) of LS in the greenhouse of the Plant Pathology Department, Assiut University, Egypt, in 2017/2018. An inoculation liquid was prepared by mixing 1 gm of ed water . For eaced water . The infijkY is the disease reaction of genotype i in replication j planted in year k, µ is the general mean; ig, jr, and ky are the main effects of genotypes (fixed effects), replications, and years (random effects), respectively. ikgy is genotype × year interaction and; ijke is the error. The broad-sense heritability (H2) was calculated as follows:r is the number of replicates within the experiment, and y is the number of years.An analysis of variance (ANOVA) of LS resistance was conducted using R software  Data froPstI and MspI, for genotyping-by-sequencing as described in [DNA was extracted from all the 60 genotypes by collecting 4–5 leaves from five-day-old barley seedlings. The extraction protocol was conducted as described in Mourad et al. . DNA conribed in . Single ribed in . IdentifY is equal to the trait value, µ is equal to the population mean, and f (marker) is a function of the significant markers. The phenotypic variation explained by each significant SNP marker was estimated using TASSEL 5.0 software [The phenotypic data , as well as the available SNP markers, were used to perform a single-marker analysis (SMA) to identify SNP markers significantly associated with resistance. Single marker analysis was performed using PowerMarker software V 3.25 [software .r2) was calculated using TASSEL 5.0 and visualized as a heatmap using “Ldheatmap” R package [For significant SNP markers located on the same chromosome, linkage disequilibrium . The functional annotation of the identified gene models was retrieved from the genome annotation provided by IBSC_V2 and examined for their association with disease resistance. The expression of candidate genes was investigated from the Expression Atlas database .To further confirm the SMA results, we investigated if any of the significant SNPs were located within gene models identified in the reference genome assembly published by the International Barley Genome Consortium (IBSC V.2) available on Ensemblplants . The analysis of variance for loose smut resistance is presented in r = 0.78 **) for LS resistance (The 57 genotypes displayed different degrees of infected heads ranging from 0 to 64% based on the average of both years. All genotypes could be classified into six groups: immune (20 genotypes), highly resistant (12 genotypes), resistant (seven genotypes), moderately resistant (nine genotypes), moderately susceptible (four genotypes), susceptible (three genotypes), and highly susceptible (two genotypes) a. A set sistance c. The hisistance a, the susistance b, while sistance c,d. p-value < 0.001) (2) ranged from 0.55 % for SNP S3_4158424 (3H) to 47.70% for SNP S2_6903688 (2H). The four significant SNPs identified on chromosome 2H were found to have the highest R2, with values ranging from 16.12% to 47.70%. The target alleles of the significant SNPs decrease the symptoms of loose smut in the genotypes with a percentage ranging from 1.71% for SNP S3_4158424 to 23.57% for SNPs S3_546788379, S3_546788391, and S3_546788395.Genotyping-by-sequencing generated a set of 25,700 SNPs. After filtration, the number decreased to 16,966 SNPs used for SMA and further genetic analysis. Due to the absence of the genotypes x year interaction, average LS values obtained from both years were used in the SMA analysis. The SMA identified 27 SNP markers significantly associated with the resistance (< 0.001) a. These 2r) between each pair of significant SNPs located on the same chromosome was calculated. The highest number of high LD genomic regions was found on chromosome 3H among the 13 significant SNPs  has been conducted. Up to our knowledge, our study could be considered as the first report on the genetics of LS resistance against Egyptian LS. Understanding such an important point will accelerate the production of barley, not only in Egypt but also in the different parts of the world where LS disease occurs, and organic agriculture is practiced. In the current study, the presence of highly susceptible genotypes (with the percentage of infected heads >50%) in both years indicated the successfulness of the artificial infection and the validity of the results.2B = 0.95) also indicated that the phenotypic variation of LS resistance in the studied materials is stable and mainly due to genotypic variation. As a result, improving LS resistance in spring barley could be possible due to the successful selection of highly resistant genotypes, which will be very useful, especially for low input and organic fields where seed treatment with fungicides is not practiced. The different degrees of the partially infected spikes  or naked (14 genotypes), with six of them having both traits (naked 6-row type). It was known that 6-row barley genotypes are highly fertile and high-yielding due to the formation of kernels from all the spikelet’s flowers. Naked barley genotypes were also preferred as they are linked directly to dietary food uses . The preTo fully utilize the resistant genotypes identified in this study, it is very important to understand the genetic control of LS. In this study, the genotyping was undertaken using 16,966 SNP markers which were highly polymorphic and distributed across all genotypes.The genetic association can be carried out using different kinds of analysis, such as genome-wide association study (GWAS) and single-marker analysis (SMA). In this study, the 60 genotypes used were not appropriate for GWAS studies, which require at least 100 genotypes to be precise . However2 of the significant SNPs, all SNPs with R2 less than 10% were considered as marking minor effects (chromosomes 6H and 7H). The SNPs located on chromosomes 1H, 2H, 4H, and 5H could be considered as marking major effect loci (R2 > 10%) [Single-marker analysis identified a set of 27 SNP markers associated with LS resistance in the studied genotype materials based on the average of both years data. The chromosomal location of the identified SNPs indicated the presence of multiple genomic regions controlling resistance . Based o2 > 10%) ,36,37. THORVU3Hr1G002060 gene model was located near S3_4158424 and S3_4158440. These two SNPs were located before the gene model at a distance of 439 and 455 bp, respectively. O-acyltransferase (WSD1-like) family plays an important role in synthesizing different types of waxes [To further understand the genetic association between the identified significant SNPs and LS resistance, gene models harboring or located near significant SNPs were investigated. The annotation revealed 15 gene models. Out of the 15 gene models, three were identified to be located very near the significant SNPs on chromosome 1H (one gene model) and 3H (two gene models). The gene model identified on chromosome 1H was functionally annotated as fatty acyl-CoA reductase (FAR), an enzyme that is responsible for alcohol and fatty acid formation. Fatty acids were reported to be a very important regulator of plant defense against different microbes ,39, whilHORVU3Hr1G002060. This gene encodes a protein kinase domain-containing protein. Protein kinase domains can be divided into two phosphorylating groups, phosphorylating either serine/threonine or tyrosine residues on target proteins [Blumeria graminis f. sp. tritici) in wheat [HORVU6Hr1G010050 gene. The result of gene annotation of this SNP supports the power of genetic association performed in this study in detecting putative SNP associated with loose smut resistance. A KASP marker targeting this SNP can be designed and used for validation in other genetic backgrounds before using it for marker-assisted selection to improve resistance to LS in barley. The expression of the other candidate gene models did not associate with disease resistance.Of all significant SNPs identified, one SNP on chromosome 6H is located within a gene model of proteins . Serine/proteins . Such prin wheat , stem ruin wheat , bacteriin wheat , and strin wheat . HORVU6HUn1 to Un15, only the Un8 gene has a defined chromosomal location [As mentioned previously, among the 15 different LS resistance genes reported, location . Due to Un8 resistant gene was reported as an important gene that is very effective against all LS races in Europe and Canada [Un8-specific marker (A/G) was used to evaluate the 60 Egyptian genotypes, along with two resistant checks . All genotypes were found to be non-carriers of the Un8 gene. The immune genotypes thus appear to carry other genes for LS resistance. Further trials are needed to evaluate the effectiveness of this gene against the Egyptian race, as integrating this gene into the Egyptian barley gene pool could improve resistance to Egyptian LS races.The d Canada ,45. TherAccording to the phenotypic and genotypic criteria used in our selection, the best genotypes that can be used for crossing would be SCYT-33 and PNBYT15 for the following reasons; (I) the genetic distance between these two resistant genotypes was 0.88, (II) they were found to have 19 and 6 favorable marker alleles, respectively, and (III) a set of 19 different favorable alleles were found between them and shared three favorable alleles. Therefore, cultivars having 22 favorable alleles may be produced from crossing between these two genotypes. Although SCYT-33 and SC2-19 had the highest number of target alleles, they had the lowest genetic distance (0.43). The number of different alleles between the two genotypes was 9 and they shared 13 favorable alleles and were located in the same subpopulation . TherefoUn8 resistance genes demonstrated that this gene was not present in the Egyptian genotypes. Promising resistant genotypes were identified that could be used for future breeding programs to improve loose smut resistance in barley.The results of this study provide valuable information on the genetic improvement of loose smut resistance in barley, especially in the context of Egyptian barley production. A set of 27 SNPs were reported to be associated with loose smut resistance. Of the 27 SNPs, one SNP located on chromosome 6H could be a promising marker as it is within a gene model encoding a protein kinase previously associated with resistance to other plant pathogens. Moreover, the 0751D06 F6/R6 marker targeting the