Spinacia oleracea L.) is centered in California and Arizona in the US, where downy mildew caused by Peronospora effusa is the most destructive disease. Nineteen typical races of P. effusa have been reported to infect spinach, with 16 identified after 1990. The regular appearance of new pathogen races breaks the resistance gene introgressed in spinach. We attempted to map and delineate the RPF2 locus at a finer resolution, identify linked single nucleotide polymorphism (SNP) markers, and report candidate downy mildew resistance (R) genes. Progeny populations segregating for RPF2 locus derived from resistant differential cultivar Lazio were infected using race 5 of P. effusa and were used to study for genetic transmission and mapping analysis in this study. Association analysis performed with low coverage whole genome resequencing-generated SNP markers mapped the RPF2 locus between 0.47 to 1.46 Mb of chromosome 3 with peak SNP  showing a LOD value of 61.6 in the GLM model in TASSEL, which was within 1.08 Kb from Spo12821, a gene that encodes CC-NBS-LRR plant disease resistance protein. In addition, a combined analysis of progeny panels of Lazio and Whale segregating for RPF2 and RPF3 loci delineated the resistance section in chromosome 3 between 1.18–1.23 and 1.75–1.76 Mb. This study provides valuable information on the RPF2 resistance region in the spinach cultivar Lazio compared to RPF3 loci in the cultivar Whale. The RPF2 and RPF3 specific SNP markers, plus the resistant genes reported here, could add value to breeding efforts to develop downy mildew resistant cultivars in the future.Commercial production of spinach ( Spinacia oleracea L.) is a leafy vegetable crop cultivated on 58, 000 acres in the US valued at more than 500 million dollars in farmgate value [Spinach  loci in hybrid seeds. Commercial seeds of spinach are produced in geographical regions with long days, moderate-cool temperatures, and dry weather during critical stages of pollination and seed set [Spinach, a diploid crop comprised of six chromosome pairs, is primarily a dioecious crop, although some other sex forms naturally occur. Selfing is not uncommon in female spinach plants, especially in the absence of pollen, which generates inbreed seeds lacking the desired combination of complementing seed set . OptimalPeronospora effusa, formerly Peronospora farinosa, causes downy mildew disease [P. effusa races are currently known in spinach [P. effusa races have been overcoming newly introgressed resistance genes in spinach cultivars. Thus, managing downy mildew disease is a major agenda of public and commercial breeders. Multiple RPF loci are hypothesized to provide resistance to different P. effusa races [RPF loci from two inbred parents that offer resistance against many pathogen races. Despite the development of spinach cultivars with resistance to specific downy mildew races, no cultivar is known to be resistant to all races of the pathogen except for Sunangel, which is marketed as having resistance to races 1 through 19, although exhibiting intermediate resistance to race 10. Developing a spinach cultivar that can resist all available pathogen races would significantly benefit sustainable production until the appearance of new pathogen races. The search for new RPF genes that can resist new races of P. effusa remains a routine task of spinach breeders to minimize yield loss from downy mildew pathogens. A large number of germplasm comprising both cultivated and wild species are maintained in the National Plant Germplasm System of the United States Department of Agriculture (NPGS-USDA) and the Centre for Genetic Resources, the Netherlands (CGN), Wageningen University and Research (WUR) [R) genes deployed in spinach cultivars that are kept confidential by commercial breeders.Downy mildew infection makes plants unsalable. Obligate oomycete  disease , 3 and i spinach , with 16sa races . Most spch (WUR) , 9. StriRPF1 locus in chromosome 3 [RPF1, RPF2, and RPF3 were later mapped to a 1.5 Mb of spinach chromosome 3, and diagnostic markers to determine resistant-susceptible alleles were reported [RPF1 locus was further narrowly mapped to 0.89 Mb of Sp75 chromosome 3 between 0.34–1.23 Mb [RPF1 locus in a multi-parent progeny population to 0.84 Mb of Sp75 assembly [P. effusa race 16 to a 0.57 Mb region of Sp75 assembly [RPF3 locus in Whale was located at 1.25 Mb and at 2.73–2.74 Mb in Monoe-Viroflay genome assembly, and three regions of Sp75 genome assembly located at 1.19, 1.22–1.23, and 1.75–1.76 Mb [RPF2 locus was recently reported to be between 1.11 to 1.72 Mb on chromosome 3 of Sp75 genome assembly [Marker DM1 was established to locate 1.7 cM away from the mosome 3 . Additioreported . The RPF–1.23 Mb . Genotypassembly . Similarassembly . Downy massembly . The RPFassembly ., plus deep molecular and genomic studies of genetic resistance mechanisms, may provide new tools to support precise R gene pyramiding. The downy mildew pathogen-resistant RPF genes have been breaking down with regularly emerging new races of P. effusa. This scenario has urged an in-depth characterization of the spinach-downy mildew pathogen interaction in disease development that may enable optimum use of host genetic resistance. Genome wide association studies (GWAS) are commonly used to identify chromosomal regions associated with trait expression in self-pollinated and cross-pollinated crop species. GWAS have been used to map the disease resistance regulating genomic regions and have identified single nucleotide polymorphism (SNP) markers that are associated with many traits in spinach [Host genetic resistance continues to be the primary method for managing downy mildew disease in spinach, especially in organic production, despite the widespread use of chemical fungicides for managing various crop diseases. Identification of additional unique resistance materials effective against many races of downy mildew pathogens spinach , 18, 19. spinach  because  spinach , 14, 20, spinach .RPF2 and RPF4 loci that resist P. effusa races 1–10 and 15. Whale has an RPF3 locus that provides resistance to races 1, 3, 5, 8–9, 11–12,14, 16, and 19, while Viroflay is entirely susceptible to all known races of downy mildew pathogen [RPF2 and RPF4 loci in Lazio, only the RPF2 locus resist race 5 of P. effusa, while the RPF4 locus is susceptible; thus, the progenies of Lazio segregating for race 5 will uniquely map the RPF2 locus in Lazio. Cross-bred progeny of Lazio and Viroflay screened for resistance to race 5 of P. effusa were used to map the RPF2 locus. In addition, progenies of Viroflay x Lazio plus Viroflay x Whale populations were combined in order to map the overall resistance regulating region. This work identifies markers and genes associated with RPF2 and RPF3 loci and adds genomic resources to facilitate molecular-guided breeding in spinach.Spinach differential Lazio constitutes pathogen , 25. Of P. effusa race 5 with no sporulation on cotyledon and true leaves, while the Viroflay and NIL4 were susceptible. The F2 seedling progenies from the cross of Viroflay x Lazio segregated upon inoculation, with 234 scored as resistant and 94 as susceptible. The segregation of Viroflay x Lazio progeny for P. effusa resistance in this experiment fit a 3:1 Mendelian segregation ratio  which is expected for a trait regulated by a single dominant gene. For the Viroflay x Lazio panel, 192 seedlings (comprising 142 resistant and 48 susceptible seedlings and two parents) were sequenced to generate genotype datasets. In addition, 192 progeny panels segregating from Viroflay x Whale for race 5 of P. effusa reported earlier [In all inoculation experiments, the parental lines Lazio, NIL2, and NIL3 showed resistant reactions to  earlier  were incIllumina sequencing of 192 Viroflay x Lazio progeny population generated 173.79 Gb sequence data. There were 1158.57 million raw reads, averaging 6.03 million reads per sample, equaling 1.01x average genome coverage. High-quality nucleotide bases with a Q score of 30 (>Q30) comprising 120.48 Gb data containing 810.06 million sequence reads were aligned against Sp75 reference genome assembly by implementing Illumina Dynamic Read Analysis for GENomics (DRAGEN) pipeline (v3.8.4), and for SNP calling. Raw SNP datasets were filtered for read depth to retain a minimum depth of coverage of 3 (DP 3), minimum genotype quality value of 9 (GQ 9), minor allele frequency (MAF) value of 0.05, and SNP with missing rates >75% using BCFtools  that retApart from Viroflay x Lazio progeny panel, SNPs were also discovered for the 384 progeny by merging another progeny panel of Viroflay x Whale reported previously , and we Genetic diversity assessment revealed two main subpopulations in the Viroflay x Lazio progeny panel . In contRPF2 locus. Twenty-three SNPs were identified to associate with the RPF2 locus with a mean LOD value >18 across four GWAS models implemented in TASSEL and GENESIS programs  showed the LOD values of 62.5, 61.6, 59.1 in TASSEL SMR, GLM, and MLM models and 13.6 in the GENESIS logistic mixed model. The mean LOD values of the 23 SNPs associated with the RPF2 locus ranged from 18.02 to 49.21 and were located at 0.478, 0.809, 0.879, 1.00–1.06, 1.16–1.19, 1.22–1.23, 1.36, and 1.46 Mb of Sp75 chromosome 3 (2 %) explained by the RPF2-associated SNPs in the SMR, GLM, MLM, and LMM GWAS models was 54.5–86.1, 54.4–85.8, 25.7–84.8, and 27.7–69.3 respectively  of 47.0–75.6, 43.9–72.8, 18.8–55.8, and 40.2–67.9 in the SMR, GLM, MLM, and LMM GWAS models. Two peak-associated SNPs, Chr3_1 221 009 and Chr3_1 222 211, explained 75.6 and 71.6% of the total phenotypic variance in the SMR model and averaged 68.0 and 65.1 across four tested models  genes in the proximity of the 23 RPF2-associated SNPs identified in the Viroflay x Lazio progeny revealed three genes within 10 Kb of the associated SNPs, plus Spo12908, located at 14–16 Kb away from the peak SNPs  in Sp75 assembly. Gene Spo12916 that encodes Leucine-rich repeat (LRR) was 8 Kb from the SNP marker Chr3_1 162 051. Gene Spo12821, a CC-NBS-LRR gene annotated to encode disease resistance protein, was within 1–2 Kb of SNPs Chr3_1 221 009, Chr3_1 222 101, and Chr3_1 222 211. The RPF3-associated SNPs between 1.22–1.23 Mb of chromosome 3 were at a distance of 2.41–2.65 Kb of the NBS-LRR gene Spo12821 [RPF2 locus, as presented in Searching for resistance  inoculated with the same pathogen race (P. effusa race 5), we mapped the RPF2 and RPF3 loci at fine resolution and differentiated the resistance-regulating region by individual RPF2 and RPF3 locus. The combined analyses showed associations for RPF2 and RPF3 loci at 1.18–1.23 Mb and 1.75–1.76 Mb. The RPF3 locus was reported to localize on 1.19–1.23 and 1.75–1.76 Mb [RPF loci, we concluded that the RPF2 locus extends through 0.47 to 1.06 Mb together with the 1.19–1.23 Mb region, the latter region associated even with the RPF3 loci. The RPF1 locus was mapped between 0.34–1.23 Mb [RPF3 locus was assigned to three physical regions in 0.66–0.69, 1.05, and 1.22–1.23 Mb [RPF loci  seem to be tightly linked, as all three loci were not stacked into one line by conventional crossing and have not been separated with the absence of recombination events in the region. The SNP markers reported here are helpful for marker assisted selection, especially in combination with other RPF genes. Further, incorporating RPF loci along with the field resistance QTLs [RPF loci are underway to provide practical molecular tools for selection.This study first mapped the  studies , 14, 16.–1.23 Mb  and 0.39–1.23 Mb . The RPFR genes within the RPF-associated regions that accommodate six NBS-LRR genes between 0.6 and 1.3 Mb of Sp75 chromosome 3 [RPF loci  are localized. This study mapped the RPF2 locus in close proximity Spo12821 gene that encodes CC-NBS-LRR protein encoding, which was located at 1.08 Kb, 2.17 Kb, and 2.28 Kb of RPF2-associated SNPs: Chr3_1 221 009, Chr3_1 222 101, and Chr3_1 222 211. Similarly, other disease resistance genes were identified near the RPF2 associated regions, such as Spo12793 encoding Serine/threonine-protein kinase was 5.96–5.08 Kb from SNP markers at 0.87 Mb, Spo12908 annotated as disease resistance protein was 14.11 Kb from SNP Chr3_1 053 892, and another gene Spo12916 with Leucine-rich repeat units was 8.04 Kb from SNP Chr3_1 162 051. Spo12821, an NBS-LRR encoding gene identified in the RPF2-associated region, was also reported as a potential candidate gene for RPF3 locus [RPF2 locus [P. effusa. The NBS-LRR is the most predominant class of R gene in plants that are known to act as a receptor of plant pathogen effector proteins and induces effector triggered immunity (ETI) by activating the downstream defense response to inhibit pathogen infection [Hyaloperonospora arabidopsidis (formerly P. parasitica) [Magnaporthe grisea [RPF1-RPF6 have been established in spinach, plus molecular markers to select for RPF1-RPF3 loci have been developed. However, the R genes have not been functionally validated. These genes reported in this study, most notably the Spo12821 consistent with both RPF2 and RPF3 loci, should be studied for structural and functional variation to elucidate the downy mildew disease resistance mechanism along with the involvement of other complementing genes in regulating resistance phenomena. New research aiming to characterize the functions of genes with gene editing and over-expression studies may explain the effective genes involved in resistance to downy mildew pathogens.The spinach genome assembly shows clusters of mosome 3 , the samnfection . Recent asitica)  and ricee grisea . The RPFLow coverage genome sequencing (~1x) is a cost-effective approach to sequence a sample at a low coverage depth, typically between 1x and 3x, which can significantly reduce sequencing costs while still providing complete genome coverage and the ability to detect a greater amount of genetic variation. However, it is important to note that this approach is known to produce higher levels of missing data compared to higher coverage sequencing methods , 33. To RPF genes, discovering markers, and gaining insights into their regulatory mechanism could present new and improved choices for breeding resistant cultivars. Such efforts are necessary to address the regularly emerging pathogen races that break the resistance loci. Overall, this study reports new sets of SNP markers to distinguish and select RPF2 and the RPF3 loci that can potentially accelerate the breeding process. The novel QTL regions and SNP markers identified here and the previously identified QTLs may have the potential to pyramid resistant genes when developing resistant spinach germplasm and breeding lines [Spinach cultivars containing multiple resistant genes may provide more durable resistance. Continued identification of new resistance sources, mapping new ng lines , 16–18. RPF2 locus for resistance to downy mildew in the spinach cultivar Lazio within 0.47 to 1.46 Mb of chromosome 3, identifying 23 associated SNP markers with a mean LOD value >18 across four tested GWAS models. The peak associated SNP with the RPF2 locus was located 2.41–3.65 Kb to the CC-NBS-LRR gene Spo12821, and other SNPs associated with the RPF2 locus were found in proximity to genes Spo12793, Spo12908, and Spo12916, which are known to have disease resistance functions in plants. These RPF2-associated genes, especially Spo12821, offer promising prospects for future research to explore their role in regulating resistance against downy mildew pathogens and developing new tools and options for breeding resistant cultivars.In conclusion, resistance to downy mildew pathogens is a key target trait in spinach breeding programs, but the frequent breakdown of resistance genes has been a major setback for spinach breeders. In this study, we successfully mapped the P. effusa, while Viroflay is susceptible to all races of P. effusa. The F1 male and female plants were allowed to inter-cross with F2 seeds harvested from female plants and used for inoculation and genetic analyses.The differential cultivars Lazio and Whale were crossed with Viroflay to generate F1 seeds. Lazio and Whale are resistant to race 5 of P. effusa (isolate UA201715) at the University of Arkansas. After initial screening and understanding of the segregation pattern from the small set of seedlings, the remaining F2 progenies of Viroflay x Lazio (n = 328) were inoculated. In all inoculation trials, parents, six near isogenic line (NIL) differentials (NIL1 through NIL6), and Viroflay were inoculated as controls along with the segregating progeny population. Seeds were sown in plastic trays (25 x 50 cm) filled with a potting mix . Around 10–15 seeds were sown in a greenhouse plant tray in ten rows. Seedlings were later thinned to 6–8 seedlings per row, and each seedling was labeled. Plants in trays were grown in the greenhouse (25°C) for two weeks.In the beginning, 10–20 F2 plants of Viroflay x Lazio plus parent lines were evaluated for disease reaction against race 5 of P. effusa race 5 in our previous study [RPF resistance region.In addition, 192 F2 seedlings of Viroflay x Whale segregating for resistance to us study  were merOne leaf from every F2 seedling was excised before inoculation and stored for DNA extraction. All two-week-old seedlings in plant trays were spray inoculated using the previously reported whole-plant inoculation method , 5, 25. Sequencing and SNP variant calling were performed as previously described . GenomicNext, the SNP dataset from six spinach chromosomes was extracted using BCFtools . The genWe swiftly assessed population structure and principal component analysis (PCA) using all SNPs in GAPIT3 , 36. TheGWAS analysis was initially performed in TASSEL 5.2.85 by implementing single marker regression (SMR), general linear model (GLM), and mixed linear model (MLM) . The GLMP. effusa race 5 by merging the Viroflay x Lazio population (described here) with the previous report of Viroflay x Whale population [RPF2 and RPF3 associated regions following combined analysis and potentially identify unique R gene regions compared with the individual GWAS panels of Viroflay x Lazio (reported here) and the previous study comprising Viroflay x Whale progeny population [A meta-GWAS analysis was planned for a multi-parent population segregating for pulation . This mepulation . For 38410 or the LOD score > 18 was employed to control false positives in Viroflay x Lazio progeny population. For the combined population of Viroflay x Lazio and Virolflay x Whale, a higher LOD score > 32 was set to consider the significance of the association.Manhattan plots and QQ plots were drawn in the R program using the CMplot package. A GWAS significance threshold of -logRPF-associated SNPs identified across tested GWAS models, genes were searched around 20 Kb of associated SNPs in the Sp75 reference sequences [RPF-associated SNPs were considered candidate genes with likely involvement in providing resistance to the downy mildew pathogen. Predicted functions of such potential candidate genes in proximity (20 Kb) of RPF-associated SNPs were described.For all equences . Genes aWeb_Material_uhad076Click here for additional data file.


FOXJ1, FOXK2, MBL2, TNFRSF4, SIRT1, NCF1) and meat quality  in the WECP population; these genes were a loss event in the WECP population. This study provides important information on CNV differences between foreign and indigenous pig breeds, making it possible to provide a reference for future improvement of these breeds and their production performance.Copy number variation (CNV) is an important class of genetic variations widely associated with the porcine genome, but little is known about the characteristics of CNVs in foreign and indigenous pig breeds. We performed a genome-wide comparison of CNVs between Anhui indigenous pig (AHIP) and Western commercial pig (WECP) breeds based on data from the Porcine 80K SNP BeadChip. After analysis using the PennCNV software, we detected 3863 and 7546 CNVs in the AHIP and WECP populations, respectively. We obtained 225  and 379  copy number variation regions (CNVRs) randomly distributed across the autosomes of the AHIP and WECP populations, accounting for 10.90% and 22.57% of the porcine autosomal genome, respectively. Functional enrichment analysis of genes in the CNVRs identified genes related to immunity ( Sus domesticus and determined that CNVs evolve approximately 2.5 times faster than SNPs. Therefore, studying CNVs in the genome is useful for understanding the genetic diversity of genomes, the genomic makeup of different species, and individual differences.With the development of DNA sequencing technology and other molecular biology techniques, different types of genetic variations can be investigated at the DNA level such as single nucleotide polymorphism (SNP), insertion-deletion (indel), microsatellite DNA, copy number variations (CNVs), and structural variations in large indels . These rIn previous studies, it was found that CNVs mainly occurred during meiosis. They were caused by chromosomal structural rearrangements resulting in non-allelic homologous recombination that could be passed to offspring , with soBecause CNVs cover a broader genomic region in domestic animals, many studies have reported that CNVs play an important role by potentially altering gene structure and dosage, exposing recessive alleles, alternating gene regulation, and affecting other mechanisms . For exaWestern commercial pig (WECP) breeds have advantages in growth rate, daily gain, and other features, whereas Anhui indigenous pig (AHIP) breeds have advantages in meat quality, disease resistance, and other traits. Our group previously evaluated runs of homozygosity and SNP signatures of selection, identifying many differential gene expression patterns between AHIP and WECP populations. Currently, there are no reports of CNVs between the AHIP and WECP populations, nor are there any reports of differences between the two populations caused by CNVs. This study used the Illumina Porcine 80K SNP BeadChip and Penn CNV software to identify autosomal CNVs in 320 pigs from the AHIP and WECP populations. We analyzed the distribution of CNVs in the pig genome and different populations to comprehensively determine the population genetic background differences and genetic diversity of AHIPs and WECPs, providing crucial information for the genetic improvement of these breeds through sustainable breeding programs.All experiments in this study were carried out in accordance with the recommendations of the Animal Care Committee of the Anhui Academy of Agricultural Sciences . The program was approved by the Animal Protection Committee of Anhui Provincial Agricultural Science .A total of 320 blood samples were collected from 10 breeds of pigs, including 5 foreign breeds (WECP): Yorkshire (n = 50), Landrace (n = 30), Duroc (n = 30), Pietrain (n = 30), Berkshire (n = 30), and 5 indigenous Anhui pig populations (AHIP): Anqing six-end-white pig , Wei pig , Wannan Spotted pig , Wannan Black pig , and Huai pig . We considered two different groups based on the results obtained in the previous study [p-values below 1e6 for Hardy-Weinberg equilibrium were eliminated. SNPs found on the sex chromosomes were also disregarded. Ultimately, 54,075 autosomal SNPs were retained for CNV analysis and detection.The Porcine SNP80k BeadChip  includes 68,528 SNPs with an average gap length of 38 kb on each chromosome and was used for individual genotyping. GenomeStudio version 2011  was used for genotype calling and SNP clustering, and tight quality control was applied to SNP filtering to improve the precision of CNV detection. SNPs with call rates below 90%, minor allele frequencies below 0.03, and http://may2015.archive.ensembl.org/index, accessed on 2 June 2022), the physical locations of SNPs on chromosomes were established. Using the gcmodel option in PennCNV, genomic waves were adjusted for the GC content in the 500 kb genomic region around each SNP on both sides. Subsequently, each sample was subjected to quality control before analysis to reduce the possibility of false-positive CNVs [To discover CNVs, the population frequency of the B allele (PFB) of SNPs and the log R ratio (LRR) and B allele frequency (BAF) at each SNP marker were incorporated into a hidden Markov model using the PennCNV software . Each SNive CNVs .The software CNVRuler was then used to integrate the overlapping CNVs to create CNVRs . We choshttp://www.biomart.org/, accessed on 15 October 2022) to identify genes overlapping with the CNVRs, including gene ID and gene type from the Ensembl gene 80 database based on the Sscrofa 10.2 genome assembly. Owing to the incomplete annotation of porcine genes in the Gene Ontology (GO) or Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, we first converted the pig Ensembl gene IDs to orthologous human Ensembl gene IDs using BioMart [https://metascape.org/, accessed on 3 November 2022) was used for gene enrichment analysis, including GO analysis and KEGG pathway analysis . In this study, we annotated gene sets according to the type of CNV, based on their formation mechanisms, and those with a corrected p-value of <0.05 were selected to explore the genes involved in biological processes. In addition, information from the pig quantitative trait loci (QTL) database was used to find QTL located in the identified CNVRs or QTL partially overlapping with the CNVRs (at least 50% inside the CNVs) for further analysis .We used BioMart  and 3863 CNVs in the AHIP population . A total of 604 CNVRs were discovered by merging the CNV areas that had been determined to overlap, including 379 and 225 events in the WECP and AHIP populations, respectively. The statistical mapping of CNVRs in autosomes of the AHIP and WECP populations is shown in Among these 604 CNVRs, we found 133 gain and 471 loss events. The distribution of CNVRs in pig autosomes is shown in In the AHIP and WECP populations, we retrieved 720 and 1749 genes within or overlapping CNVRs, respectively, using the Ensembl genes 80 databases , regulation of secretion , regulation of immune effector process , and actin cytoskeleton organization . The KEGG pathway analysis showed enrichment in inositol phosphate metabolism , cAMP signaling pathway , and pathways of neurodegeneration-multiple diseases  that were loss events in the WECP populations (p = 2.78 × 10−2), the regulation of centrosome duplication , regulation of mitotic cell cycle  and the sensory perception of umami taste . These were identified as loss events in the AHIP populations  and Forkhead Box K2 (FOXK2) are among the Forkhead Box (Fox) family members [FOXK2 was found to be associated with central nervous system abnormalities and intellectual disability [FOXK2, as factors causing ARM disease. The mannose-binding lectin 2 (MBL2) gene is one of the members of the C-type (Ca2+ dependent) lectin gene superfamily and plays an important role in the first line of defense against pathogen infection [MBL2 gene is an important component of the innate immune lectin pathway and functions to mediate immune regulation and phagocytosis [MBL2 is an important component of the innate immune response and a key gene regulating the resistance or susceptibility of livestock to pathogens [MBL2 underlies a QTL for immunoglobulin A levels on OAR22 of Djallonké lambs and confirms a signature of resistance to infection with gastrointestinal parasites [TNFRSF4 [TNFRSF4 is one of the major members of the TNF receptor-family member 4 (TN-FRSF4) and is mainly inducibly expressed in activated CD4+ and CD8+ cells [TNFRSF4 was lost in WECP populations. Similarly, sirtuin 1 . TNFRSF8+ cells . TNFRSF48+ cells , and pla8+ cells . In our 1 (SIRT1 ), a nico1 (SIRT1 . SIRT1 ifunction . In studn sepsis . The neuis [NCF1 ) gene waDGAT1) gene belongs to the family of cholesterol acyltransferases (ACAT) and has been shown to significantly increase intramuscular fat content in domestic animals, such as pigs [DGAT1 elevates intramuscular fat (IMF) content in transgenic mice generated by pronuclear microinjection with a muscle-specific promoter of porcine muscle creatine kinase (MCK). Liu et al. [DGAT1 CNVs in seven Chinese goat populations and found significant associations with important economic traits such as meat, dairy, and fiber goats. In a porcine study, Wang et al. [DGAT1 and DGAT2, in the Duroc population. In our study, we identified ten QTLs, including average daily gain (ID = 18712441), average backfat thickness (ID = 8134840), water holding capacity (ID = 15473302), and linoleic acid content (ID = 17965327) by gene mapping to the CNVs in the WECPs_loss group and by using functional analysis of the location of the CNVR in DGAT1 using the PigQTLdatabase version 10.2. Domestic animals undergo a series of changes in meat quality over a period of time after being slaughtered. Among them, the concentration of inosine 5′-monophosphate (IMP) has been suggested to be an important factor affecting meat quality [NT5E) gene encodes the enzyme NT5E for the extracellular degradation of IMP to inosine, and several studies have simultaneously reported that NT5E affects the overall concentration balance of IMPs and their degradation products [NT5E genotype. The results showed that the heritability of IMP at seven days post-mortem decreased from 0.32 to 0.08 when the NT5E genotype was included in the model. Similarly, NT5E, which is involved in the biological process of lipid deposition, has been identified as a candidate gene for selecting markers to control IMF formation in Chaohu ducks [Our team have previously reported significant differences in meat quality traits and fat deposition ability between WECP and AHIP populations ,56,57. T as pigs , cattle  as pigs , and she as pigs . Li et a as pigs  found thu et al.  were theg et al.  found so quality  because  ID = 179327 by ge quality . Related quality . The ectproducts . Komatsuproducts  estimatehu ducks . In thisAlthough we found some interesting information in WECP and AHIP populations, our study did have some limitations. We used the Porcine 80K SNP BeadChip, which has limitations that cannot be avoided by showing the specific locations of all CNVs somatically. Fortunately, the beadchip employed in our study was large enough for its loci to be mapped relative to other beadchips on pigs. However, the number of groups we studied was not very large, owing to the presence of African pig fever, which affected the number of our groups. Therefore, in future experiments, we plan to expand the study population and obtain phenotypic data to validate the effect of CNVs.In this study, we evaluated CNV differences between the WECP and AHIP populations, based on the Porcine 80K SNP BeadChip. We found 225 and 379 CNVRs in the WECP and AHIP populations, respectively, accounting for 22.57% and 10.90% of the porcine autosomal genome. Statistically, the number of CNVRs was greater and their length was longer in the WECP than in the AHIP population. We performed enrichment analysis separately by CNVR event type and found several immunity and meat quality-related candidate genes in the WECP-loss group. Our analyses found that these genes overlapped with important economic traits in pigs. These results can help us understand the reasons for the differences in phenotype between the WECP and AHIP populations and help to effectively improve the performance of these breeds.


Choosing the best subset of markers for the best linear unbiased prediction (BLUP) for improved prediction ability (PA) has become an interesting issue. However, when dealing with many traits having the same marker information, the p-values’ themselves cannot be used as an obvious solution for having a confidence in GWAS and BLUP. We thus suggest a genomic estimated breeding value-assisted reduction method of the single nucleotide polymorphism (SNP) set (GARS) to address these difficulties. GARS is a BLUP-based SNP set decision presentation. The samples were Landrace pigs and the traits used were back fat thickness (BF) and daily weight gain (DWG). The prediction abilities (PAs) for BF and DWG for the entire SNP set were 0.8 and 0.8, respectively. By using the correlation between genomic estimated breeding values (GEBVs) and phenotypic values, selecting the cutoff threshold in GWAS and the best SNP subsets in BLUP was plausible as defined by GARS method. 6,000 SNPs in BF and 4,000 SNPs in DWG were considered as adequate thresholds. Gene Ontology (GO) analysis using the GARS results of the BF indicated neuron projection development as the notable GO term, whereas for the DWG, the main GO terms were nervous system development and cell adhesion.Traditionally, the  Genome-wide association studies (GWAS) aim to detect variants of genomic loci associated with complex traits in the population, and common single nucleotide polymorphisms (SNPs) are the main source of these variants. SNPs are used to describe genetic variability and identify candidate genes, and GWAS examine significant SNPs  is a technique used to estimate genetic ability. BLUP estimates the realized values of random variables (random effects) Robinson . AlthougThe Landrace pig is a long white pig variety utilized as the grandparents when producing F1 parent stock females in terminal crossbreeding. It outperforms other pigs in terms of litter size as well as birth and weaning weight. In Korea, Landrace pigs are typically used for commercial pork production  and the best linear unbiased prediction (BLUP) for BF and DWG. Determining significant markers in a GWAS allow the identification of notably associated genes and guide improved pig breeding programs. Furthermore, GWAS require multiple tests to determine significance. Currently, multiple hypothesis tests focus on the dependence among the hypotheses, specifically at the level of P-value < 1.0E-6. SNP genotypes were imputed using the Beagle program  and backfat thickness (BF) were analyzed. BF was measured from the longissimus dorsi muscle between the 10th and 11th ribs. The genomic DNA of Landrace pigs was genotyped using an Illumina Porcine 60 K SNP BeadChip  following the standard protocol. The total number of single nucleotide polymorphisms (SNPs) was 55,167; after quality control (QC), 46,992 SNPs remained in the autosomes  is used to determine an adequate number of SNPs. We determined the number of SNPs with significance in GWAS with the best prediction of breeding values in BLUP using GARS. The predictive ability (PA) correlation difference was calculated as follows:where (i*step) represents the number of SNPs, and PA[i*step] indicates that it was derived from the SNP subset obtained from 1-i*step SNPs.In our GWAS and BLUP analyses, 1,000 SNPs were used. The region immediately before the continuous negligible correlation difference was selected as the cut-off value. The R package ‘rrBLUP’ was used to determine the breeding values Endelman . The selwww.ensembl.org) was used as the gene catalogue, and GO analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery   were further surveyed using GO analysis. The Ensembl database (The numbers according to sex and parity in Landrace pigs and the mean and standard deviation (SD) of the traits are presented in In linear regression, the covariates used were sex and parity, and the phenotypes were BF and DWG. Histograms of phenotypic values and beta effects were plotted using a normal distribution curve . This ilp-values confirmed the GWAS results. The p-values were adjusted using the Benjamini-Hochberg correction in the Q-Q plot.p-value was adjusted according to the sample size. In contrast, GARS and the statistic used (Equation (2)) are heuristic. Using GARS, we determined the cut-off thresholds for GWAS and BLUP. For BF and DWG, the Manhattan plot showed that Bonferroni correction resulted in a common cutoff p-value of 2.0*E-7, but respective p-values of 5.0*E-4  and 2.5*E-9 , respectively , Benjamini-Hochberg (BH) method, and Bonferroni correction were used to identify significant variants. In the Bonferroni correction, the The highly significant SNPs and encompassing genes in the GWA test were demonstrated with gene ontologies  and molecular function [MF]) . We also determined whether GOs for BF and DWG overlapped.p-value < 1.0E-06) using the BF-associated genes, neuron projection development was a notable BP term, and ion binding was a notable MF term. The notable GOs for DWG (p < 1.0E-05) were nervous system development, cell adhesion (BP), and ion binding (MF) . Among the 19 top GO terms for BF, eight overlapped with the Bonferroni correction results (e.g. GO:0030182∼neuron differentiation). In addition, 12 of the 16 GO terms in the DWG overlapped with Bonferroni correction .According to GO analysis , have been used for association tests , regression using total SNPs is prevalent. Recently, BLUP has been performed using a subset of SNPs  , Xenotropic and polytropic retrovirus receptor 1 (XPR1), and Neuregulin 3 . Previous studies have reported that upregulated LAMC2 activates CD44 and positively regulates docosanoic acid, palmitic acid, and trans-oleic acid content, while negatively regulating tridecanoic acid, stearic acid, and cis-5,8 11, 14-eicosapentaenoic acid contents , Rubicon autophagy regulator (RUBCN), and FERM domain-containing 5 (FRMD5). The IGFs system is a family that includes two ligands (IGF-1 and IGF-2), two cell surface receptors (IGF1R and IGF2R), and at least six high-affinity IGF-binding proteins (IGFBPs 1-6). This system plays an essential role in normal human and animal development, including embryogenesis, pre- and postnatal growth, and maintenance of tissue homeostasis -assisted reduction of single nucleotide polymorphism (SNP) sets (GARS) is an alternative to traditional methods. The correlation difference (CD) predicted between GEBV and phenotypic values can guide the cutoff thresholds in GWAS and BLUP analyses. We observed a decreased CD in some SNP subsets and determined that the subset containing more SNPs was negligible because of the rapid loss of capability as a significant variant. The results of GARS and Bonferroni correction differed from each other, such that GARS was more congenital than Bonferroni correction in the BF trait, but was harsher in the DWG trait. Despite being a novel approach, the GARS results can be limited by extant association studies. However, we expect that GARS will play an important role in determining the number of SNPs and genes in GWAS and BLUP.Click here for additional data file.


However, a fundamental understanding of the origin of Ni5P4(0001) activity is still lacking. In this work,density functional theory (DFT) calculations were employed for a comprehensiveinvestigation. The calculation results indicate that the Ni5P4(0001) surface exposing Ni3P4 terminationgains the highest stability, on which a nearly thermoneutral hydrogenadsorption was found at the P3-hollow sites, providinga high activity for HER. The activity was also observed to be maintainedover a wide H-coverage. HER occurs via the Volmer–Heyrovskymechanism as evidenced from the optimal hydrogen adsorption free energy,but unlikely through the Tafel reaction due to its large energy barrier.Furthermore, the P3-hollow sites also exhibit a low kineticbarrier for water dissociation, promoting HER in alkaline media. Aseries of electronic structure analyses were performed in gaininginsights into the origin of the HER activity. First, the density ofstates (DOS) and crystal orbital Hamilton population (COHP) analysesrevealed a favorable interaction of electronic states between P andH atoms, leading to stable H adsorption at P3-hollow sites.In addition, the Bader charge analysis demonstrates that the strengthof H adsorption at P3-hollow sites linearly increases withthe electrons carried by the latter. The optimal net charge on theP3-hollow sites leads to a desired ΔGH that is close-to-zero. Finally, a highly efficient electrontransfer was observed between the P3-hollow sites and theirneighboring atoms, facilitating the HER.Hydrogen evolution reaction (HER) is directly relevantto greenhydrogen production from water splitting. Recently, a low-cost Ni It requires high-performance electrocatalyststo proceed expeditiously, particularly under alkaline media whereHER is more difficult but oxygen evolution reaction  is much more facile than thosein acidic media. It has been recognized that the noble metals exhibitan excellent capability of efficiently catalyzing the HER.9 However, their high cost and low earth abundance limit their applicationin large-scale green hydrogen production.11 Therefore, it is essential to develop low-cost high-performanceHER electrocatalysts.Hydrogen can serve asthe primary energy carrier of future energysystems due to its several distinct advantages such as high energydensity and zero-carbon emission.16 In particular, due to their excellent electronic conductivity andstability, nickel phosphides (NixPy) have been widely investigated as a potentialsubstitute for noble metal catalysts for HER.18 There have been a variety of phases obtainedfor nickel phosphides, such as Ni3P,19 Ni5P2,20 Ni12P5,21 Ni2P,22 and Ni5P4.23 The nickel phosphides with differentNi/P ratios have exhibited different catalytic properties for HER.For instance, Pan et al. synthesized Ni12P5,Ni2P, and Ni5P4 by a thermal decompositionapproach, and found that their HER activity followed the order ofNi5P4 > Ni2P > Ni12P5 in acidic conditions.24 Infact,Ni5P4 has drawn great attention since it hasbeen demonstrated to have HER activity comparable to the Pt. As reportedby Laursen et al., in 1 M H2SO4 solution, theNi5P4 exhibits a Tafel slope of 33 mV dec–1 and an overpotential of 62 mV at 100 mA cm–2, which are close to the values given by Pt.23 The high activity was also found on the highly ordered Ni5P4 nanosheets with largely exposed surfaces synthesizedby Ledendecker et al.25 Besides, Ni5P4 was even observed to be highly active underalkaline conditions where the HER is in fact more difficult comparedto acidic media.26 Moreover, it has been theoretically and experimentally indicatedthat the catalytic performance of Ni5P4 is superiorto that of other Ni-based compounds, e.g., Ni3S2 and Ni3N.27Recently, the earth-abundant and inexpensivetransition metalsand their carbides, nitrides, phosphides, and chalcogenides have attractedconsiderable attention in the development of HER catalysts.5P4, extensive efforts have been made to explore the originof its activity for HER. One explanation given by a few researchersis that the Ni5P4 has a higher positive chargeover Ni atoms and a stronger ensemble effect of P atoms, which leadsto an increased binding to the first H atom, and in turn enhancesthe affinity to the second proton.28 However, therecent theoretical study has shown that the superior activity of Ni5P4(0001) is provided by the surface P atoms producingnearly optimal H adsorption, instead of the Ni atoms that bind stronglyto the H adsorbates.29 In a systematicstudy of the activity of Ni5P4 surfaces forHER, Hu et al. confirmed the high activity of P atoms, and revealeda close correlation between the activity and the structural propertieson an atomic scale.30 However, there isstill a lack of in-depth knowledge of the origin of this activity.In particular, there exist limited theoretical studies of the HERactivity of Ni5P4 in alkaline media and theunderlying mechanism is still poorly understood. Although it is well-knownthat the electrocatalytic properties of materials are strongly relatedto the electronic structures of their surface atoms,33 in the previous theoretical studies, the electronic nature of Ni5P4 and its role in the HER activity have not beenelucidated fully. Therefore, it is necessary to perform a comprehensiveinvestigation to gain a deeper fundamental understanding of the inherentreasons underlying the high activity of Ni5P4 for HER.Motivatedby the excellent catalytic performance of Ni5P4 activity for HER throughdensity functional theory (DFT) calculations. The low index (0001)facet of Ni5P4 was chosen for the activity investigationbecause it has been experimentally demonstrated to be uniformly exposed.34 The HER activity of Ni5P4(0001) was systematicallyevaluated, and the results show that the surface P atoms act as theactive sites rather than Ni. This is in fact in good agreement withthe previous finding. Through the transition state analysis, the reactionmechanism of HER on Ni5P4(0001) was determinedand the performance of Ni5P4(0001) toward waterdissociation was also explored. Furthermore, the role of the electronicstructure of Ni5P4(0001) in the HER activityhas been interpreted.Herein, a comprehensive study has been conductedto understandthe origin of the Ni236 The exchange-correlation energywas calculated by the generalized gradient approximation (GGA) ofPerdew–Burke–Ernzerhof (PBE).37 The interaction between electrons and ions (nucleus) was depictedwith the projector augmented wave (PAW) method.38 The van der Waals (vdW) interactions were described throughthe DFT-D3 method.39 A high cutoff kineticenergy of 500 eV was applied for the plane-wave basis set to approximatethe valence electron densities. The convergence criteria for energyand force were set to 10–5 eV and 0.02 eV/Å,respectively. A (√3 × √3) R30° supercell ofNi5P4(0001) consisting of 108 atoms was constructedto explore the HER process on the surface. The vacuum layer thicknesswas set to 20 Å in the z-direction to eliminatethe vertically periodic interaction. The slab dipole correction wasapplied to avoid the electrostatic effects along the z-direction. During structure relaxation, the atoms in the bottomNi–P layers were frozen, and the number of frozen atoms variedwith different surface terminations (Table S1). According to the Monkhorst–Pack scheme, the Brillouin zonewas sampled by Γ-centered k-point meshes of 9 × 9 ×3 and 3 × 3 × 1 for the geometry optimization of the unitcell and supercells, respectively, while in the electronic structurecalculations for them denser k-point meshes of 12 × 12 ×5 and 5 × 5 × 1 were used, respectively. The climbing imagenudged elastic-band method (CI-NEB) was employed to search transitionstates.41 The vibrational frequency analysis was subsequentlyperformed to confirm that only one imaginary frequency existed forthe structures of the obtained transition states.The Vienna Abinitio Simulation Package (VASP) code based on densityfunctional theory (DFT) was employed to perform the first-principlescalculations.5P4(0001) beingasymmetric, the surface energy (γ) was calculated by the followingexpression:42sunrelax and Esrelax are the total energy of the unrelaxedand relaxed surface slabs, respectively; Eb is the totalenergy of a unit cell of bulk Ni5P4; N is thenumber of the unit cells contained in the surface slab; and A is thesurface area of the slab model. The first term represents the energyconsumed to cleave the bulk Ni5P4 into two surfaceslabs, and the second term is the energy generated from the surfacerelaxation. The surface energy is the sum of the cleavage energy andthe relaxation energy.42Due to thesurface slabs of NiGH) is an excellent descriptor to evaluate the HER performanceof one catalyst.43 It can be obtained throughthe equation below:EH is the hydrogen adsorption energy, ΔZPE represents the zero-pointenergy correction of H adsorption, T is the temperature of 298 K,and ΔSH is the loss of entropy dueto the adsorption of the hydrogen atoms on the catalyst surface. TheΔSH is approximated as ΔSH ≈ −1/2(SH20), where the SH20 is the entropy of H2 in gas phase at standard conditions . The ΔEH can be calculated by the following equation:(n+1)H* and EnH* represent the total energy of the surface slabs with n+1 and n adsorbedH atoms, respectively; E2H is the energy ofa hydrogen molecule in gas phase. The ΔZPE can be determinedfrom(n+1)H* and ZPEnH* are the zero-point energy of the surfaces adsorbed by n+1 and nH atoms, respectively; and ZPE2H is the zero-pointenergy of H2 in gas phase. The zero-point energy can becalculated from vibrational frequency calculations as follows:h is the Planck constantand v is the calculated vibrational frequency ofH adsorbates.The Gibbsfree energy for H adsorption (ΔEa) was computed fromTS and EIS representthe total energy of the transition state and initial state, respectively.In the electronic structure analysis, the net charge (Qnet) carried by an atom is defined asbader and Qval are the calculated Bader charge and the number of valence electronsthat the DFT calculations assume for the atom, respectively. A positiveor negative value of the net charge represents that the atom losesor gains electrons (positively and negatively charged). The chargedensity difference (Δρ) for the H adsorption is definedas Δρ = ρH+surf. – ρsurf. – ρH, where ρH+surf., ρsurf., and ρH are the chargedensities of the H-adsorbed surface, the clean surface, and the Hatom, respectively.For transition state analysis, the activationenergy  axis with respectto the other one. In half a unit cell, the atoms have a complex arrangementin the [0001] direction and the delineation of atomic layers is lessclear. By removing the outermost atoms or atomic layers from the surfacein the [0001] direction, as illustrated in Figure S1, five possible surface terminations were obtained. Accordingto the composition of the exposed surface atoms, they are referredto as Ni3P4, Ni3P3, Ni7P3, Ni4P3, and Ni3P5 surface terminations, respectively. 5P4(0001)with different terminations. It is clearly demonstrated that the Ni3P4-terminated Ni5P4(0001)has the lowest surface energy, which implies that Ni3P4 is the most stable termination. By energetics consideration,it is predicted that the Ni3P4 termination hasa high probability of being exposed to the reactant during HER catalysis.44 Therefore, the Ni3P4 terminationwas selected to investigate the catalytic activity of Ni5P4(0001) for HER.Analysis of surface stability was carried out todetermine themost stable surface termination of Ni3.23P4-terminated Ni5P4(0001)surface consists of repeating triangular Ni3 connectedwith each other by tetrahedral P4. The P corners of threeadjacent tetrahedral P4 gather around a common point, creatinga P3 hollow. We have considered all possible sites on theNi3P4 termination to identify stable hydrogenadsorption sites. After full structure relaxation, the H adsorptionwas finally stabilized at three types of sites, i.e., Ni3-hollow sites, P-top sites , and P3-hollow sites. The optimized geometryof H adsorption for each kind of site is schematically demonstratedin 3-hollowsite can accommodate three H atoms, each of which bonds to one P atomthere, while a Ni3-hollow site can stabilize only one Hatom, bonding to the three Ni atoms, over their center. Accordingto the calculated H adsorption energy (ΔE)listed in Table S3, the Ni3-hollowsites are identified as the preferable sites for H adsorption withthe largest negative ΔE value of −0.732eV, whereas the P3-hollow sites and P-top sites exhibitrelatively weaker adsorption toward H atoms than the Ni3-hollow sites, with much smaller negative ΔE value of −0.276 eV and −0.422 eV, respectively.As shownin GH) has been generally perceived as a suitabledescriptorfor evaluating HER performance. The ΔGH should be close to zero on excellent HER electrocatalysts,which indicates an ideal trade-off between adsorption and releaseof H atoms during surface electrocatalysis. Either too weak or toostrong binding of H atoms to the catalyst surface can lead to an inefficientHER process. Table S3 show the calculated ΔGH for the Ni3P4-terminatedNi5P4(0001) surface. The P3-hollowsites have a nearly thermoneutral H-adsorption with a ΔGH value of 0.012 eV that is close-to-zero, signifyingthat the P3-hollow sites can deliver near-optimal HER catalyticactivity. The P-top sites are also highly active for HER (ΔGH = −0.121 eV), but their activity islower than P3-hollow sites. The biggest negative ΔGH (−0.484 eV) was found for Ni3-hollow sites. With such a large negative ΔGH, the H atoms can be readily adsorbed at the Ni3-hollow sites, but the release of H atoms from these sites is verydifficult, leading to an inefficient HER process. In addition, giventhat each P3-hollow site can adsorb two additional H atoms,we investigated the effect of the number of adsorbed H atoms at oneP3-hollow site on its HER activity. As shown in GH. However, when one more H atom is adsorbed at the site, the ΔGH is increased to 0.046 eV, more positive than that of theadsorption of only one H atom. This indicates that the activity ofthe P3-hollow site is diminished due to the interactionsamong adsorbed H atoms when the site is fully occupied by three Hatoms. Despite that, this ΔGH valueof 0.046 eV remains close to zero, demonstrating that the high catalyticactivity of the P3-hollow site for HER can be maintainedwith the increasing number of the adsorbed H atoms at the site.The Gibbs free energy of H adsorption (Δ3P4-terminated Ni5P4(0001) surface on H coverage. The H coverage is defined as the ratioof the number of adsorbed H atoms to the number of surface adsorptionsites. Since the above results suggest that the interaction of theadsorbed H atoms at the P3-hollow sites can affect theΔGH, we considered two pathways(A and B) for increasing the H coverage at the P3-hollowsites, as schematically illustrated in Figure S2. In pathway A, the H atoms are adsorbed at one P3-hollow site until the latter is fully occupied, then another P3-hollow site begins to adsorb H atoms, while in pathway B,the adsorption of the next H atom always occurs at another P3-hollow site. At a same H coverage (at least two H atoms are adsorbedat the same P3-hollow site), there are different interactionsof H atoms at P3-hollow sites in the pathways A and B. Table S4 show the calculated ΔGH values under various H coverages in the pathways A andB. The yellow region in GH | < 0.2 eV).45 Clearly, pathway A has greater ΔGH values than pathway B between 7/15 and 9/15H-coverage due to the stronger interaction of adsorbed H atoms atthe P3-hollows in pathway A. Subsequently, at 10/15 H-coverage,the ΔGH value of pathway A is greatlyreduced to a value lower than that of pathway B. This is because,for 10/15 H-coverage, the H-adsorption via pathway A occurs at thenonoccupied P3-hollow site, while in pathway B the P3-hollow site is already occupied by one H atom. This leadsto stronger interaction between the adsorbed H atoms in pathway Bthan in A, weakening the H adsorption. Between 10/15 and 13/15 H-coverage,pathway A has greater ΔGH valueat P3-hollow sites than pathway B. It is noted that theΔGH values are increased to over0.2 eV at 12/15 H-coverage for pathway A (ΔGH = 0.209 eV) and 11/15 H-coverage for pathway B (ΔGH = 0.209 eV), respectively, but at a similarcoverage of 13/15, they are reduced back to below 0.2 eV. When H-coverageis over 14/15, the HER activity becomes low with the ΔGH being greater than 0.2 eV. Therefore, it isevidenced that the HER is more facile over a wider range of H coveragesvia pathway A than B, i.e., the H-coverage of 4/15 to 11/15 for pathwayA and of 4/15 to 10/15 for pathway B. Overall, the Ni3P4-terminated Ni5P4(0001) surface canmaintain a high activity for HER over a large H-coverage range.Furthermore, we explored the dependence of the HER activity ofNi3.32 through eitherthe Heyrovsky step or Tafel step. Under acidic conditions, these threesteps can be expressed as below:3P4-terminatedNi5P4(0001) surface, the HER can proceed veryfast through the Volmer–Heyrovsky pathway at the P3-hollow sites since their ΔGH valuesare nearly zero.46 The Volmer–Heyrovskypathway is also viable at P-top sites, but their HER rates are relativelylower than the P3-hollow sites since the P-top sites havea less favorable Heyrovsky step. Regarding the Ni3-hollowsites, their strong binding to the H atoms favors the Volmer stepbut in the meantime makes it difficult to release the adsorbed H atomto produce H2, hindering the Heyrovsky step.The HER process can proceed through two distinctmechanisms, the Volmer-Heyrovsky mechanism and the Volmer–Tafelmechanism. Both mechanisms start with the Volmer step producing thekey reactive intermediate H* (* represents the hydrogen adsorptionsite), followed by the production of H2 molecule. One of the reasons for the excellent HERperformance of Pt catalysts is that they have a fast Tafel step;47 thus, we explored the viability of the Tafelstep on the Ni3P4-terminated Ni5P4(0001) surface. Due to the P3-hollow sites beingthe main active sites for HER, we calculated the energy barriers ofthe Tafel reactions at the P3-hollow sites. As shown in 3-hollow sitesas the beginning of the Tafel reaction. One is the P3-hollowsite partially occupied by two H atoms, while the other is fully occupiedby three H atoms, two of which subsequently combine to form H2. However, both cases were found to possess high energy barriersof 1.235 and 1.222 eV, suggesting the sluggish kinetics of H2 generation at the P3-hollow sites through Tafel reactions.A previous study by Ling et al.48 has shownthat a greatly reduced H–H distance between two neighboringadsorbed H atoms can lead to a low energy barrier for the Tafel reaction.In their study, a very low energy barrier of 0.48 eV for the Tafelreaction was obtained at those active sites where the two adsorbedH atoms are about 1.5 Å apart, while, in our work, the H–Hdistances are found to be much greater, 2.20 and 2.19 Å for bothH adsorption configurations, respectively. Therefore, we believe thatthe long H–H distance between two adjacent adsorbed H atomsat the P3-hollow sites is a crucial factor causing theirhigh kinetic barriers for Tafel reactions. Overall, it can be concludedthat in acidic environments the energetically favorable Volmer–Heyrovskypathway is the dominant mechanism for the HER on the Ni3P4-terminated Ni5P4(0001) surface.This is in agreement with the experimental result that a Volmer–Heyrovskymechanism for Ni5P4 was indicated by the obtainedTafel slope of 40 mV dec–1.25TheTafel step is a process in which two adsorbed H atoms combine to producea H2O + e– → H* + OH–), becomesthe main source providing H intermediates. Therefore, the kineticbarrier for water dissociation was examined for the Ni3P4-terminated Ni5P4(0001) surface.It was found that on the surface there were two kinds of sites forstable adsorption of molecular water, i.e., P3-hollow andNi3-hollow sites. 3-hollow and Ni3-hollow sites, respectively. The adsorption energy was calculatedto be −0.183 eV and −0.289 eV on the P3-hollowand Ni3-hollow sites, respectively, suggesting that theNi3-hollow sites have a stronger adsorption for H2O than the P3-hollow sites. At the P3-hollowsite, the H2O molecule is stabilized by one P atom witha P–O bond length of 3.097 Å. Meanwhile, another P atomat the site tends to attract the H atom of H2O, givinga shorter P–H bond length of 2.728 Å. For the H2O adsorption at the Ni3-hollow site, the H atom of H2O is attracted to the hollow center with an average Ni–Hbond length of 2.748 Å, whereas the O atom of H2Ois at a distance of 3.248 Å from the nearest Ni atom. This indicatesthat the Ni3-hollow site has a greater binding affinityfor the H atoms of H2O than the O atom during water adsorption.Besides, as shown in Table S5, in comparisonto the free molecular water in vacuum (0.972 Å), the O–Hbonds of the adsorbed H2O were observed to be slightlyelongated, i.e., 0.977 and 0.981 Å for P3-hollow andNi3-hollow sites, respectively. This suggests that theO–H bonds in the water molecule were weakened. In addition,the longer O–H bond for the water at Ni3-hollowsites than that at the P3-hollow sites indicates a strongeractivation of the O–H bonds over the Ni3-hollowsites.Due to the scarcity of protons in alkaline electrolytes,waterdissociation, also known as the alkaline Volmer step  ismuch higher than at P3-hollow sites (0.404 eV). This isbecause at the P3-hollow site, the H and OH species generatedfrom water dissociation can be directly captured by the P3-hollow site at once. However, since the Ni3-hollow sitecan only adsorb one H atom, the generated OH specie needs to diffuseto the P3-hollow site to be stabilized. Although the Ni3-hollow site can activate the O–H bond in H2O more favorably during H2O adsorption, the diffusionof the OH species on the surface inevitably introduces an extra kineticbarrier, resulting in an increase in the energy barrier for H2O dissociation at the Ni3-hollow site. Therefore,the H adsorbate can be preferentially generated at P3-hollowsites during water dissociation, favoring the alkaline HER. Besides,the energy barrier for water dissociation on Ni5P4(0001) (0.404 eV) is much lower in comparison to that on Ni2P (0.82 eV) reported by Cross et al.49 This is in accordance with the experimental finding that Ni5P4 exhibits a higher catalytic activity for alkalineHER than Ni2P.23The transition state analysis was then performedto determine theenergy barriers for water dissociation at P3.43-hollow sites of the Ni3P4-terminatedNi5P4(0001) surface exhibit a superior activityfor HER. To gain insight into the origin of the activity of P3-hollow sites, a series of electronic structure analyses wereperformed. We first investigated the bonding characteristics of theP3-hollow site with H adsorbates. 3-hollow site before and after H adsorption.It can be seen that after H adsorption the total DOS is reduced aroundthe Fermi level. Besides, the total DOS below the Fermi level shiftsdownward to lower energy, while a localized peak is formed at a higherenergy above the Fermi level. These changes can be explained by theunderlying mechanism of bond formation. When the H atom approachesthe P3-hollow site on the surface, the coupling of electronicstates between them leads to the hybridized energy levels, shiftingdownward to form bonding states and shifting upward to form antibondingstates. The bonding states are well below the Fermi Level and thusfully filled, while the antibonding states are usually located acrossthe Fermi Level and thus partially filled. The adsorption strengthis strongly associated with the filling of antibonding states. Tointuitively demonstrate the bonding and antibonding states for theP–H bond, the projected crystal orbital Hamilton population(pCOHP) analysis was performed. As shown in 3-hollow site producingstable adsorption toward H atoms during the HER process.The above results have indicated that theP3-hollow site on its HER activity by means of Baderchargeanalysis. To adjust the net charge of the P3-hollow site,the strategy of exploring substitutional doping by nonmetal atomswas employed here. As illustrated in 4 on the Ni3P4 termination weresubstituted by various nonmetal atoms, i.e., B, C, N, O, Si, and S.The electronegativity of these nonmetal atoms follows the order ofO > N > S > C > P > B > Si. Figure S3 presentsthe optimized geometries of the doped Ni3P4-terminatedNi5P4(0001) surfaces. It can be seen that thestructures of these doped surfaces remain consistent with the pristinesurface, except for the O-doped surface, where a significant structuraldistortion occurs due to the strong electronegativity of O atoms.Therefore, doping of O atoms is not considered in the following analysis.As observed in 3-hollow site presents a clearlinear relationship with the electronegativity of the central atoms.This indicates that the electronegativity difference between the dopedatom and P successfully evokes the charge redistribution and modulatesthe net charge of the P3-hollow site. Specifically, thedopant atoms  with a higher electronegativity thanP make their surrounding P atoms at P3-hollow sites morepositively charged as they attract the electrons from the latter,and vice versa. The adjusted net charge ranges from −0.398to 0.478 e. The highest and lowest net charges are given by the dopingof Si and N atoms, respectively. The ΔGH of P3-hollow sites on the doped surface was calculatedto assess their HER activity. As shown in GH of −0.083 eVat P3-hollow sites while the most positive ΔGH (0.105 eV) is found for the N doping. Thisshows that the ΔGH values at theP3-hollow sites on the doped surfaces remain within thepreferable Gibbs free energy range (|ΔGH| < 0.2 eV) for the HER, as already mentioned above. Besides,the ΔGH is linearly correlated withthe net charge with a reasonable fitting factor R2 of 0.89. A larger negative net charge is observed togenerate a more negative value of ΔGH, which implies that the P3-hollow sites with more electronscan provide stronger adsorption toward H atoms. Importantly, it canbe seen that the P3-hollow sites on the pristine surfacehave an optimal net charge that leads to the nearly thermoneutralH adsorption. This is responsible for the superb activity of the pristineNi3P4-terminated Ni5P4(0001) surface for HER.Next, we investigated the effect of the net charge(defined by 3P4-terminated Ni5P4(0001) surface before and after H adsorption. It can be observedthat the H adsorption at the P3-hollow site triggers asignificant charge transfer; i.e., there is noticeable electron depletion(green) around the P3-hollow site and the H atom, whileelectron accumulation in the middle between the two atoms. This indicatesthe strong interaction between the two atoms and the formation ofthe P–H bond during H adsorption, in agreement with the DOSand pCOHP analyses described above. Another region of electron depletionis found under the P3-hollow site, and the electrons movetoward the P3-hollow site. The direction of this chargetransfer can be attributed to the P3-hollow site gainingelectrons from the surroundings to balance its reduced charge duringthe formation of the P–H bond. Besides, an obvious charge transferbetween the P3-hollow site and the surrounding Ni atomsalso occurs. This corresponds to the observed increase in the lengthsof the Ni–P bonds after H adsorption , which indicates the weakened strength of neighboring Ni–Pbonds.Furthermore, charge transfer analysis was alsoperformed to understandthe adsorbate–surface interaction. 3-hollow sites, we now discuss the Ni3P4-terminated Ni5P4(0001̅)surface since we found that the activity of P3-hollow siteson this surface suffers from poor charge transfer. It is worth notingthat although the Ni5P4(0001) and Ni5P4(0001̅) surfaces have the same termination ofNi3P4 composition, they are still structurallydistinct, due to the bulk Ni5P4 lacks mirrorsymmetry along the [0001] direction, as illustrated in Figure S5. We refer to the two surfaces as (0001)-Ni3P4 and (0001̅)-Ni3P4 in the following discussion, respectively. The net charge of theP3-hollow site on the (0001̅)-Ni3P4 is calculated to be −0.151 e, more negative than thaton the (0001)-Ni3P4 (−0.075 e). However,the P3-hollow site on the (0001̅)-Ni3P4 (ΔGH = 0.317 eV) exhibitsa much weaker ability toward H adsorption than the (0001)-Ni3P4 (ΔGH = 0.012 eV),which is apparently inconsistent with the above result that the highernet charge of the P3-hollow site can generate strongerH adsorption. After examining the charge distribution on the surface,we found that the central P atom of the tetrahedral P4 onthe (0001)-Ni3P4 is positively charged witha net charge of 0.069 e. This leads to the central P atom, as a nonmetalelement, having stronger attraction to electrons. For instance, 3-hollow site withthe neighboring atoms after H adsorption. The Bader analysis , weakening the attractionof the central P atom toward electrons. Thus, upon the adsorptionof the second H atom, the central P atom attracts fewer electrons-Ni3P4 surface, the (0001)-Ni3P4 surface has a favorable charge distribution,benefiting the charge transfer. For example, the central P atom isnegatively charged with the net charge of −0.012 e on the clean(0001)-Ni3P4 surface. After the adsorption ofone H atom, the net charge is increased to −0.005 e and thecentral P atom remain negatively charged. This demonstrates that thecentral P atom can remain as an electron donor to the P3-hollow site to promote the H adsorption. Therefore, the (0001)-Ni3P4 surface has a favorable charge transfer, facilitatingthe HER process.To further understand the effect of charge transferon the HERactivity of P45P4(0001) modelcatalyst. The results show that the lowest surface energy was obtainedon the Ni5P4(0001) surface exposing Ni3P4 termination. The P3-hollow sites providethermoneutral hydrogen adsorption, thus contributing to the high HERactivity of Ni5P4(0001). It has also been observedthat the surface remains catalytically active over a wide H coverage.The optimal free energy for hydrogen adsorption suggests that HERis facile via the Volmer–Heyrovsky mechanism, while the Tafelreaction is kinetically unfavorable due to its large energy barrier.The P3 hollow sites were also found to provide a low energybarrier toward water dissociation, favoring the alkaline HER. A seriesof electronic structure analyses performed have gained a deeper understandingof the activity origin. The results indicate that the superior HERactivity of Ni5P4(0001) can be attributed tothree main factors. First, the DOS and COHP analyses revealed a favorableinteraction of electronic states, leading to stable adsorption ofP atoms toward H atoms. Second, from the Bader charge analysis, itwas found that the strength of H adsorption at P3-hollowsites linearly increases with the electrons carried by them. The appropriatenet charge at P3-hollow sites leads to the optimal close-to-zeroΔGH. Third, highly efficient electrontransfer between the P3-hollow sites and their neighboringatoms also contributed to the facile HER process.DFT calculations were successfullyperformed to investigate theorigin of the HER activity of Ni


Fusarium oxysporum is a prevalent fungal pathogen that diminishes soybean yield through seedling disease and root rot. Preventing Fusarium oxysporum root rot (FORR) damage entails on the identification of resistance genes and developing resistant cultivars. Therefore, conducting fine mapping and marker development for FORR resistance genes is of great significance for fostering the cultivation of resistant varieties. In this study, 350 soybean germplasm accessions, mainly from Northeast China, underwent genotyping using the SoySNP50K Illumina BeadChip, which includes 52,041 single nucleotide polymorphisms (SNPs). Their resistance to FORR was assessed in a greenhouse. Genome-wide association studies utilizing the general linear model, mixed linear model, compressed mixed linear model, and settlement of MLM under progressively exclusive relationship models were conducted to identify marker-trait associations while effectively controlling for population structure.Glyma.06G088400 encoding a protein kinase family protein containing a leucine-rich repeat domain identified as a potential candidate gene in the reference genome of Williams82. Additionally, quantitative real-time reverse transcription polymerase chain reaction analysis evaluated the gene expression levels between highly resistant and susceptible accessions, focusing on primary root tissues collected at different time points after F. oxysporum inoculation. Among the examined genes, only this gene emerged as the strongest candidate associated with FORR resistance.The results demonstrated that these models effectively managed population structure. Eight SNP loci significantly associated with FORR resistance in soybean were detected, primarily located on Chromosome 6. Notably, there was a strong linkage disequilibrium between the large-effect SNPs ss715595462 and ss715595463, contributing substantially to phenotypic variation. Within the genetic interval encompassing these loci, 28 genes were present, with one gene Glyma.06G088400 improves our understanding of soybean resistance to FORR and the markers strongly linked to resistance can be beneficial for molecular marker-assisted selection in breeding resistant soybean accessions against F. oxysporum.The identification of this candidate gene The online version contains supplementary material available at 10.1186/s12870-023-04646-5. Glycine max (L.) Merrill) holds great significance globally as a major oil crop, owing to its remarkable ability to enhance human nutrition as a valuable source of food, protein, and oil [Fusarium oxysporum Schltdl is a particularly troublesome soil-borne fungal disease, causing soybean root rot and inflicting significant economic losses on soybean production. In the initial stages of the disease, the color of the root tip undergoes a visible change, eventually giving rise to dark plaques on the main root. These diseased lesions persist without shrinking, gradually expanding and accompanied by cortex blackening, ultimately leading to rot and necrosis [Cultivated soybean  resistance in soybeans. Therefore, the objectives of this study were twofold: (i) to employ GWAS to identify loci associated with FORR resistance and (ii) to investigate differential expression to determine candidate genes for the identified loci. These findings can enhance our understanding of the genetic basis of FORR resistance in cultivated soybeans, facilitating the diversification of resistance genes in cultivars, and enabling the identification and application of markers adjacent to resistance genes in marker-assisted selection (MAS).The “behavior , 6. It i America , 7. F. ont death , 9. Manareatment . Althougreatment . The comreatment . By levereatment . In compreatment , 14, 15,reatment , 16, 17,reatment , 18, Sclreatment –21, whitreatment –24, Phytreatment , 25, broreatment , 26, rooreatment  and soutreatment , bacterip-value = 0.002641), and there was no serious non-normal distribution   dropped to half of its maximum value, was determined to be 109 kb at r2 = 0.422 , Chr 20 exhibited the highest SNP density (15.06 kb/SNP), while Chr 13 had the lowest SNP density (42.42 kb/SNP). The distribution of SNPs throughout the soybean genome was irregular, with an average of 1530 SNPs per Chr. Chr 18 had the highest number of SNPs (2265), whereas Chr 11 had the lowest (980) , CMLM (Q + K), and SUPER (Q + K) models closely matched the expected P-values initially. However, as the -log10 P value increased to approximately 3.3, the observed P-values deviated significantly from the expected P-values  model were consistently higher than the expected values, indicating poor control of false positives and overestimation of significance  and kinship matrix (K) in the GWAS analysis . For theues Fig. B–D. Thisnce Fig. A. Hence,The significance threshold for the Bonferroni correction line employed in this study was determined as -log10 = 4.49. Eight SNPs (ss715595416-281.0kb-ss715595451-61.4kb-ss715595455-0.2kb-ss715595456-67.8kb-ss715595462-9.1kb-ss715595463-24.4kb-ss715595465-24.5kb-ss715595467) significantly associated with DSI were identified from the greenhouse evaluations (Table Glyma.06g087100–Glyma.06g089800), with only one gene containing leucine-rich repeat receptor-like kinase (LRR-RLK), which plays a crucial role in plants’ response to various external stimuli, including pathogens  and ss715595463 . These SNPs contributed the most to the phenotypic variation, as evidenced by their average DSI of 40.52, which was significantly lower than the mean DSI of the entire panel (51.01). The soybean plants carrying the favorable allele (TT) on ss715595462 exhibited noticeably higher FORR resistance (mean DSI = 40.52) compared to those carrying the unfavorable allele (CC) (mean DSI = 52.03)  and KOG functional annotation . This classification and annotation approach allowed us to assign the genes into different functional groups based on their putative roles. We observed that Glyma.06g088400 exhibited associations with protein phosphorylation (GO:0006468) and phosphorylation (GO:0016310) in the biological process category of gene ontology. In the molecular function category, it was linked to protein binding (GO:0005515), transferase activity (GO:0016740), kinase activity (GO:0016301), protein serine/threonine kinase activity (GO:0004674), ATP binding (GO:0005524), protein kinase activity (GO:0004672), and nucleotide binding (GO:0000166). Furthermore, in the cellular component category, it showed associations with integral component of membrane (GO:0016021) and membrane (GO:0016020)  with similar functional descriptions to Glyma.06g088400, encompassing ATP binding (GO:0005524), protein serine/threonine kinase activity (GO:0004674), protein kinase activity (GO:0004672), and protein phosphorylation (GO:0006468) in both the biological process and molecular function categories of gene ontology. These four genes  are primarily involved in cell cycle control, signal transduction mechanisms, chromosome partitioning, and cell division through the production of serine/threonine protein kinase , DNA methylation (GO:0006306), and cotranscriptional gene silencing by small RNA (GO:0033562) in the biological process category of gene ontology. It is also involved in chromatin binding (GO:0003682) in the molecular function category and is localized in the nucleus (GO:0005634) according to the cellular component category  and ZDD06827 (HS). These accessions carry favorable and unfavorable alleles, respectively, at the ss715595462 and ss715595463 loci. Using qRT-PCR, we found that among the 10 genes, only Glyma.06g088400 exhibited differential expression between ZDD00774 and ZDD06827. Following treatment with F. oxysporum, the expression of Glyma.06g088400 was upregulated in the highly resistant accession ZDD00774. Specifically, the expression level of Glyma.06g088400 in ZDD00774 (HR) showed a rapid increase at 6 h after treatment, reaching a maximum fold-change of approximately 43.2. This upregulation was significantly higher compared to ZDD06827 (HS), which exhibited an approximate fold-change of 9.8 during the same period. Subsequently, the expression of Glyma.06g088400 declined rapidly at 12, 24, 48, and 72 h after treatment , we determined that the large-effect SNP ss715595462  resides within the coding region of the Glyma.06g088400 (Chr 06_6851663–6857631). Additionally, the large-effect SNP ss715595463  is situated in the downstream region of the same gene. In a study by Lanubile et al. (2015), RNA sequencing was employed to investigate the molecular aspects of the interactions between a partially resistant genotype and FO36 (non-pathogenic) and FO40 (pathogenic) F. oxysporum isolates at 72 h post-inoculation. They observed that the expression of this gene increased to a certain extent compared to healthy controls during the same time period, with a fold change of approximately 3.4-fold for FO36 and 2.2-fold for FO40. Similarly, in this study, we found that the expression level of Glyma.06G088400 in ZDD00774 (HR) also increased to a certain extent, reaching an approximate change of 9.7-fold at 72 h after treatment [Glyma.06G088400 is a strong candidate gene that may play crucial roles in the response of soybean roots to F. oxysporum infection. However, further investigations and biological studies are needed to elucidate the specific mechanisms by which this candidate gene, with its LRR-RLK domain, participates in the plant defense response following F. oxysporum infection. Despite this need for further research, our results demonstrated the effectiveness of GWAS analysis in mapping soybean FORR resistance genes and provided the SNP markers that are tightly associated with FORR resistance. Moreover, these markers can be valuable tools for MAS.The host–pathogen interaction in the context of FORR is characterized by a highly intricate collaboration among multiple genes that trigger molecular signals and subsequent responses . Understsistance . By refeGlyma.06G088400 on Chr 06 is positioned distantly from neighboring LRR-RLK genes (Glyma.06G086800-126kb-Glyma.06G088400-190kb-Glyma.06G090700), constituting an independent region without tandem duplication clusters with other LRR-RLK genes [Glyma.06G088400 gene [Glyma.06G088400 in cultivated soybean populations was estimated to be approximately 0.15 on average, significantly lower than that in wild soybean populations (approximately 0.49). Moreover, the average FST value (0.28) for Glyma.06G088400 loci exceeded 0.15, indicating that, compared to their wild ancestors, cultivated soybeans experienced a decrease in genetic diversity and underwent selection pressures [F. oxysporum damage and curbing the spread of the disease in soybean varieties. These significant findings provide valuable insights for breeding programs, directing future efforts towards enhancing F. oxysporum resistance in elite soybean cultivars by exploiting the genetic resources present in wild soybean germplasm. As the cost of acquiring high-density genome-wide marker sets decreases and GWAS statistical methodologies continue to advance, future challenges lie in developing precise, cost-effective, high-throughput, and accurate phenotyping methods. Overcoming these challenges could usher in a new era of crop disease management and plant breeding [Nearly all living organisms possess sensory proteins that enable them to detect environmental signals and transmit them within cells . Among tLK genes . This sp400 gene , 46. Theressures . Given tbreeding , 48.Glyma.06G088400 showed differential patterns between highly susceptible and highly resistant accessions upon F. oxysporum infection, making it a potential candidate gene of interest. Further investigation of this gene, which potentially plays a crucial role in F. oxysporum resistance, is deemed necessary. The identification of these putative candidate genes and their corresponding significant SNPs holds great promise for unraveling the molecular mechanisms underlying FORR resistance and facilitating MAS in disease breeding programs aimed at developing soybean varieties with enhanced FORR resistance.In this study, GWAS was employed to identify SNP markers associated with FORR resistance, leading to the discovery of eight SNPs significantly linked to this trait. Notably, the expression of F. oxysporum (FO_DH-A1-9) isolates used in this study was isolated and identified from the roots of diseased soybean plants in the Dunhua soybean field located in Jilin Province, China. The isolates were then stored on potato dextrose agar (PDA) medium.The 350 SGAs utilized in this experiment were sourced from the National Genebank of China  and maintained by the Soybean Institute of Jilin Academy of Agricultural Sciences  supplemented with antibiotics (0.10 g/L of ampicillin and 0.10 g/L of streptomycin sulfate) dishes at 25°C in the dark for one week. Sterile sorghum kernels (Sorghum bicolor (L.) Moench) were used, which were sterilized by soaking in distilled water overnight and autoclaved in quart mason jars (500 g seeds/jar) for two consecutive days, each time for 60 min. Each jar containing sterile sorghum kernels was then inoculated with 10 pieces of 7-day-old mycelial plugs from each individual F. oxysporum isolate. The jars were incubated at 25°C in the dark for two weeks to allow for the infection of the sorghum kernels. The jars were shaken for 3 to 5 min daily to ensure uniform fungal growth. For the nutrient substrate, a mixture of fine-grained soil and sand in a 1:1 volume ratio (V:V) was sterilized under high pressure at 121°C for 30 min, allowed to cool, and then mixed with the crushed and infected sorghum kernels. The ratio of infected sorghum kernels to sterilized sand-soil mixture was 1:50 (V:V), and thorough mixing was done until they were completely blended. Healthy soybean seeds were selected and treated with a 1% NaClO solution for 2 min, followed by treatment with 75% alcohol. The seeds were rinsed with sterile water for 2 to 3 times. These treated seeds were placed in plastic petri dishes containing moist sterile filter paper to ensure proper moisture and germination for one day. From each SGA, as well as the resistant and susceptible controls, four seeds were planted in seedling bowls (250 mL) filled with the inoculum mixed soil-sand mixture. After emergence, the seedlings were thinned to three plants, and each treatment was replicated six times. The experimental design employed was a randomized complete block design. The inoculated soybeans were maintained in a greenhouse with a photoperiod of 8 h of darkness and 16 h of light. The temperature in the greenhouse ranged from approximately 18 to 25°C, corresponding to night and day temperatures, respectively.F. oxysporum was evaluated four weeks after inoculation. The evaluation criteria for resistance in this study were modified from the method described by Chang et al. (2018) [F. oxysporum). Based on the DSI, the FORR resistance of all SGAs was classified into the following categories: highly resistant , resistant , moderately susceptible , susceptible , or highly susceptible .The disease reaction of soybean roots to . 2018) . Each in . Each iGenomic DNA was extracted from fresh young leaves of soybean using the previously reported hexadecyl trimethyl ammonium bromide method . Genotypr2) with PLINK1.09. Subsequently, mean LD decay plots were generated using an R script [r2 values for SNPs with pairwise distances below 500 kb in either euchromatic or heterochromatic regions of each chromosome against physical distance. The chromosomal distance at which the mean r2 declined to half of its maximum value was used to calculate the LD decay rate relative to the population [Population stratification was assessed using PCA, neighbor-joining (NJ) trees, and population structure analysis. The PCA and evaluation of the kinship matrix were conducted using Tassel V5.2.60 software, based on 30,602 SNPs from the 350 SGAs. The NJ phylogenetic tree was constructed using the Maximum Composite likelihood model in MEGA-X, with 1000 replicates of Bootstrap values. Linkage SNP filtering was performed using PLINK V1.09, with a window size of 50 kb, SNP step size of 10, SNP correlation threshold of 0.2, and retention of unlinked SNPs. This resulted in a subset of 1643 SNPs for inferring population structure using STRUCTURE 2.3.4 , using tR script , plottinpulation . LD analpulation .P-values resulting from SNP-trait associations, along with the expected P-values assuming no associations between SNPs and traits, were used to generate Q-Q plots depicting the estimated log10(P) values. To mitigate the confounding effect of population structure, the model with observed P-values that were closest to the expected P-values was selected. The presence of significant association signals was determined using the Bonferroni threshold, with a threshold set at P ≤ 1/30,602, or -Log10(P) ≥ 4.49 [A total of 30,602 SNPs from 350 SGAs were employed in the GWAS analysis to identify associations between SNPs and DSI. The GWAS analysis was conducted using GAPIT with GLM, MLM , CMLM 5, and SUP) ≥ 4.49 .http://www.soybase.org/). By leveraging the soybean genome annotations, we predicted potential candidate genes associated with the identified regions. Furthermore, the functional annotations of genes located in the target genomic regions were retrieved from Phytozome (http://www.phytozome.net).To identify the candidate genes underlying the association signals, we focused on significant SNPs linked to large-effect quantitative trait nucleotides (QTNs) and conducted a targeted search within their genomic regions. The candidate regions were defined based on either the mean LD decay distance or the LD block. For gene identification, we obtained functional annotations of gene models (Glyma.Wm82.a2.v1) or known genes located within the target genomic regions from the Soybase Database  and ZDD00774  were disinfected following previously described methods. Then, the disinfected seeds were uniformly distributed in a germination machine and stored in a growth chamber at 25°C, 80% relative humidity, and a dark environment for cultivation. Soybean seedlings ZDD06827 and ZDD00774 exhibiting good growth were selected and placed on germinating paper soaked in aseptic distilled water. They were subsequently inoculated with 200 μl of 1 × 106 conidial suspension of FO_DH-A1-9 isolates using a pipette, while a control group received an inoculation of 200 ml of sterile water. The seedlings, along with the control, were placed vertically in a sterile 1000 ml beaker, and 300–500 ml of sterile water was added. The beaker was then kept in a growth chamber with conditions set at 25°C, 90% relative humidity, and a photoperiod of 16 h of light and 8 h of darkness.The inoculum for FO_DH-A1-9 isolates was cultivated on PDA for one week at 25°C in the dark. Conidia collection was performed through a meticulous process involving the thorough cleaning of the Petri dish with sterile water, followed by the scraping of the mycelium from the surface of the agar using an aseptic toothpick. Furthermore, the conidia suspension was filtered through sterile cloth and Miracloth to obtain the desired conidia. The concentration of FO_DH-A1-9 spore suspension was adjusted to 1 × 10−ΔΔCt method [Primary roots were sampled at 0, 6, 12, 24, 48, and 72 h after inoculation, and total RNA was extracted using the Easy Pure Plant RNA kit . Reverse transcription was performed using the PrimeScriptTM RT Reagent kit with gDNA Eraser  following a standardized protocol, with 1 μg of DNase-treated RNA. The qRT-PCR primers were designed using the Oligo7 software  . HistogrAdditional file 1: Table S1. Bioassay phenotypic results of resistance to FORR in 350 soybean germplasm accessions.Additional file 2: Figure S1. Frequency distribution plot and Q-Q plot of DSI of 350 SGAs. (A) The DSI frequency distribution plot of 350 SGAs. (B) The Q-Q plot fitted by the correlation between the DSI of 350 SGAs and the normal distribution.Additional file 3: Table S2. Summary of the polymorphic markers on the 20 chromosomes of Glycine max.Additional file 4:Table S3. The Geographical distribution of 350 soybean germplasm accessions from different subgroups.Additional file 5: Table S4. The Gene Ontology (GO) enrichment analysis of the candidate genes.Additional file 6: Table S5. The eukaryotic orthologous groups (KOG) annotated analysis of the candidate genes.Additional file 7: Table S6. Geographical sources of 350 soybean germplasm accessions.Additional file 8: Figure S2. F. oxysporum root rot scoring scheme. Scoring scheme of soybean F. oxysporum root rot. Pictures (A–E) displayed phenotypes with varying disease severity ratings for the soybean root rot, including 0, 1, 2, 3, and 4.Additional file 9: Table S7. Primer sequences used for expression profiling.