A novel diagnostic model based on lncRNA PTPRE expression, neutrophil count and red blood cell distribution width for diagnosis of seronegative rheumatoid arthritis.

Diagnosis of seronegative rheumatoid arthritis (SNRA) is difficult due to the lack of diagnostic markers. The study aims to construct a novel diagnostic model based on long noncoding RNAs (lncRNAs) expression and laboratory indicators to provide a new idea for diagnostic methods of SNRA. Differentially expressed lncRNAs in peripheral blood cells of RA patients were screened through eukaryotic long noncoding RNA sequencing and validated by quantitative real-time PCR. Meanwhile, the correlation between lncRNAs expression and laboratory indicators was analyzed. The diagnostic value was evaluated by receiver operating characteristic curve analysis. Finally, combined with laboratory indicators, a diagnostic model for SNRA was constructed based on logistic regression and visualized by nomogram. Expression of ADGRE5, FAM157A, PTPN6 and PTPRE in peripheral blood was significantly increased in RA than healthy donors. Meanwhile, we analyzed the relationship between lncRNAs and erythrocyte sedimentation rate, C-reactive protein and CD4 + T cell-related cytokines and transcription factors. Results showed that FAM157A and PTPN6 were positively related to RORγt, and negatively related to GATA3. Moreover, PTPRE has potential discrimination ability between SNRA and healthy donor (AUC = 0.6709). Finally, we constructed a diagnostic model based on PTPRE, neutrophil count and red blood cell distribution width (RDW). The AUC of the model was 0.939 and well-fitted calibration curves. Decision curve analysis indicated the model had better predict performance in SNRA diagnosis. Our study constructed a novel diagnostic model based on PTPRE, neutrophil count and RDW which may serve as a potential tool for the diagnosis of SNRA.

Identification and Development of Synovial B-Cell-Related Genes Diagnostic Signature for Rheumatoid Arthritis.

Background: The aim of the study was to investigate the landscape of B-cell-related gene expression profiling in rheumatoid arthritis (RA) synovium and explore the biological and clinical significance of these genes in RA. Methods: Expression profiling of synovial biopsies from subjects with 152 RA patients, 22 osteoarthritis (OA) patients, and 28 healthy controls was downloaded from the Gene Expression Omnibus database. Single-sample gene set enrichment analysis (ssGSEA) was performed to evaluate the abundance of infiltrated immune cells, and the results were validated using immunohistochemical staining. GSEA was employed to decipher differences in B-cell-related biological pathways. B-cell-related differential expression genes (BRDEGs) were screened, and BRDEGs-based model was developed by machine learning algorithms and evaluated by an external validation set and clinical RA cohort, then biological functions were further analyzed. Results: High levels of immune cell infiltration and B-cell-related pathway activation were revealed in RA synovium. BRDEGs were screened, and three key molecular markers consisting of FAS, GPR183, and TFRC were identified. The diagnosis model was established, and these gene markers have good discriminative ability for RA. Molecular pathological evaluation confirmed RA patients with high-risk scores presented higher levels of B-cell activation and RA characteristics. In addition, a competitive endogenous RNA network was established to elucidate the molecular mechanisms of the posttranscriptional network. Conclusions: We described the B-cell-related molecular landscape of RA synovium and constructed a molecular diagnostic model in RA. The three genes FAS, GPR183, and TFRC may be potential targets for clinical diagnosis and immunoregulatory therapy of RA.

METTL14-Mediated m6A Modification of TNFAIP3 Involved in Inflammation in Patients With Active Rheumatoid Arthritis.

OBJECTIVE: The aim of the study was to investigate the role of N6 -methyladenosine (m6A) modification in the progression of rheumatoid arthritis (RA). METHODS: Peripheral blood mononuclear cells (PBMCs) from patients with RA and healthy controls were collected. The expression of m6A modification-related proteins and m6A levels were detected using polymerase chain reaction (PCR), western blot, and m6A enzyme-linked immunosorbent assay (ELISA). The roles of methyltransferase-like 14 (METTL14) in the regulation of inflammation in RA was explored using methylated RNA immunoprecipitation (MeRIP) sequencing and RNA immunoprecipitation assays. Collagen antibody-induced arthritis (CAIA) mice were used as an in vivo model to study the role of METTL14 in the inflammation progression of RA. RESULTS: We found that m6A writer METTL14 and m6A levels were decreased in PBMCs of patients with active RA and correlated negatively with the disease activity score using 28 joint counts (DAS28). Knockdown of METTL14 downregulated m6A and promoted the secretion of inflammatory cytokines interleukin 6 (IL-6) and IL-17 in PBMCs of patients with RA. Consistently, METTL14 knockdown promoted joint inflammation accompanied by upregulation of IL-6 and IL-17 in CAIA mice. MeRIP sequencing and functional studies confirmed that tumor necrosis factor α induced protein 3 (TNFAIP3), a key suppressor of the nuclear factor-κB inflammatory pathway, was involved in m6A-regulated PBMCs. Mechanistic investigations revealed that m6A affected TNFAIP3 expression by regulation of messenger RNA stability and translocation in TNFAIP3 protein coding sequence. CONCLUSIONS: Our study highlights the critical roles of m6A on regulation of inflammation in RA progression. Treatment strategies targeting m6A modification may represent a new option for management of RA.

CCN1 Promotes Inflammation by Inducing IL-6 Production via α6ß1/PI3K/Akt/NF-κB Pathway in Autoimmune Hepatitis.

Autoimmune hepatitis (AIH) is a chronic inflammatory liver disease with unknown etiology. CCN1, an extracellular matrix-associated protein, is associated with carcinoma, inflammation, liver fibrosis, and even autoimmune diseases. However, the role that CCN1 plays in AIH has remained undetermined. In this study, expression of CCN1 in liver was detected by real-time PCR, western blot and immunohistochemistry (IHC). CCN1 level in serum was detected by ELISA. Diagnostic value of CCN1 was determined by receiver operating characteristic (ROC) curve analysis. CCN1 conditional knockout (CCN1 fl/fl Cre+) mice were generated by mating CCN1 fl/fl C57BL/6J and CAG-Cre-ERT C57BL/6J mice. Autoimmune hepatitis mice model was induced by concanavalin A (ConA). IKKα/ß, IκBα, NF-κB p65 and Akt phosphorylation were determined by western blot. NF-κB p65 nuclear translocation was examined by immunofluorescence. Here, we found that CCN1 was over-expressed in hepatocytes of AIH patients. CCN1 level also increased in serum of AIH patients compared to healthy controls (HC). ROC curve analysis results showed that serum CCN1 was able to distinguish AIH patients from HD. In ConA induced hepatitis mice model, CCN1 conditional knockout (CCN1 fl/fl Cre+) attenuated inflammation by reducing ALT/AST level and IL-6 expression. In vitro, CCN1 treatment dramatically induced IL-6 production in LO2 cells. Moreover, the production of IL-6 was attenuated by CCN1 knockdown. Furthermore, we showed that CCN1 could activate IL-6 production via the PI3K/Akt/NF-κB signaling pathway by binding to α6ß1 receptor. In summary, our results reveal a novel role of CCN1 in promoting inflammation by upregulation of IL-6 production in AIH. Our study also suggests that targeting of CCN1 may represent a novel strategy in AIH treatment.

Identification of circulating miR-22-3p and let-7a-5p as novel diagnostic biomarkers for rheumatoid arthritis.

OBJECTIVES: Early and correct diagnosis would be beneficial for outcomes of rheumatoid arthritis (RA), but there are some limitations in current diagnostic tools. In this study, we aimed to evaluate the diagnostic value of circulating miR-22-3p and let-7a-5p in RA. METHODS: Seventy-six RA patients, 30 systemic lupus erythematosus patients, 32 Sjögren's syndrome patients and 36 healthy donors recruited at the First Affiliated Hospital of Fujian Medical University (China) were included in this study. Circulating miR-22-3p and let-7a-5p in plasma were measured using reverse transcriptase quantitative PCR and serum cytokines were detected by cytometric bead array. The participants' clinical materials were also collected. Receiver operating characteristic curve analysis and correlation analysis were performed to assess the potential value of circulating miRNAs in RA. RESULTS: Circulating miR-22-3p and let-7a-5p are significantly increased in RA patients and able to distinguish RA patients from other populations. Circulating let-7a-5p has been shown to improve the diagnostic ability of current laboratory indicators anti-cyclic citrullinated peptide antibodies and rheumatoid factor. Moreover, the discriminatory capacity of both circulating miRNAs contribute to complement the diagnosis for seronegative RA. Meanwhile, correlation analysis reveals that circulating miR-22-3p positively correlates with haemoglobin, serum bilirubin, albumin and IL-17 but negatively correlates with mean platelet volume as well as let-7a-5p. CONCLUSIONS: The increased circulating miR-22-3p and let-7a-5p levels in RA patients, especially in seronegative RA patients, may provide potential promising diagnostic biomarkers for RA in clinical practice.

iTRAQ-based proteomic analysis of differentially expressed proteins in sera of seronegative and seropositive rheumatoid arthritis patients.

OBJECTIVE: The diagnosis of seronegative rheumatoid arthritis (SNRA) is often difficult due to the unavailability of reliable laboratory markers. The aim of this study was to identify differentially expressed proteins in sera of SNRA, seropositive RA (SPRA), and healthy donors (HD). METHODS: A total of 32 seropositive RA patients, 32 SNRA patients, and 35 HD were enrolled in our study. Differentially expressed proteins between 3 groups were identified via isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic analysis, and an ELISA test was used for the validation test. Correlation analysis was conducted by GraphPad Prism. RESULTS: Using iTRAQ quantitative proteomics, we identified 14 proteins were significantly different between SPRA and SNRA, including 4 upregulated proteins and 10 downregulated proteins. Four differentially expressed proteins were validated by ELISA test, and the results showed that SAA1 protein was significantly higher in SPRA and SNRA patients compared with HD, and PSME1 was elevated in SPRA patients. What's more, SAA1 was increased in the anti-CCP or RF high-level group in RA patients, and PSME1 was increased in the RF high-level group. Alternatively, SAA1 was positively correlated with inflammation indicators in RA patients, while PSME1 showed no correlation with inflammation indicators. CONCLUSIONS: iTRAQ proteomic approaches revealed variations in serum protein composition among SPRA patients, SNRA patients, and HD and provided new idea for advanced diagnostic methods and precision treatment of RA.

YY1 regulation by miR-124-3p promotes Th17 cell pathogenicity through interaction with T-bet in rheumatoid arthritis.

Th17 cells are involved in rheumatoid arthritis (RA) pathogenesis. Our previous studies have revealed that transcription factor Yin Yang 1 (YY1) plays an important role in the pathogenic mechanisms of RA. However, whether YY1 has any role in Th17 cell pathogenicity and what molecular regulatory mechanism is involved remain poorly understood. Here, we found the proportion of pathogenic Th17 (pTh17) cells was significantly higher in RA than in control individuals and showed a potential relationship with YY1 expression. In addition, we also observed YY1 expression was increased in pTh17, and the pTh17 differentiation was hampered by YY1 knockdown. Consistently, knockdown of YY1 decreased the proportion of pTh17 cells and attenuated joint inflammation in collagen-induced arthritis mice. Mechanistically, YY1 could regulate the pathogenicity of Th17 cells through binding to the promoter region of transcription factor T-bet and interacting with T-bet protein. This function of YY1 for promoting pTh17 differentiation was specific to Th17 cells and not to Th1 cells. Moreover, we found miR-124-3p negatively correlated with YY1 in RA patients, and it could bind to 3'-UTR regions of YY1 to inhibit the posttranscriptional translation of YY1. Altogether, these findings indicate YY1 regulation by miR-124-3p could specifically promote Th17 cell pathogenicity in part through interaction with T-bet, and these findings present promising therapeutic targets in RA.

Suppression of Rice Planthopper Populations by the Entomopathogenic Fungus Metarhizium anisopliae without Affecting the Rice Microbiota.

Entomopathogenic fungi can regulate insect populations and function as crucial biological control agents against insect pests, but their impacts on nontarget microorganisms are poorly understood. In this study, we investigated the potential of the fungal strain Metarhizium anisopliae CQMa421 to control rice planthoppers under field conditions and its effects on rice microbiota. This fungus suppressed rice planthoppers during this period, and its control efficiency was more than 60% 7 days after application and did not significantly differ from that of the chemical treatment except in 2019. Both treatments showed a smaller population of rice planthoppers than the controls. After application, M. anisopliae was maintained on rice plants for approximately 14 days, showing a decreasing trend over time. Furthermore, the results showed that the bacterial and fungal richness (operational taxonomic units) and diversity (Shannon index) did not significantly differ between the fungal treatment and the controls after application. The major bacterial taxa of Proteobacteria (including Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, and Deltaproteobacteria), Actinobacteria, Bacteroidetes, and Cyanobacteria accounted for more than 80% of the bacterial community after fungal application, and the major fungal taxa Ascomycota (including Eurotiomycetes, Dothideomycetes, and Sordariomycetes) and Basidiomycota (including Ustilaginomycetes) represented more than 90% of the fungal community. However, the microbial communities of the rice phyllosphere did not significantly change after entomopathogenic-agent application, indicating that the indigenous microbial communities may adapt to fungal insecticide application. Taken together, the results suggest that this fungal agent has good potential for rice planthopper control with no substantial effects on rice microbial communities.IMPORTANCE Entomopathogenic fungi may be used as crucial biocontrol agents for the control of insect pests, but few effective fungal strains have been reported for the control of the rice planthopper, a major pest of rice. More importantly, the impacts of fungal insecticide application on nontarget microorganisms have not been well evaluated, especially under field conditions. Therefore, in this study, we investigated the effects of the fungal strain M. anisopliae CQMa421 on rice planthopper populations from 2017 to 2019 and evaluated its potential impacts on the microbiota of rice plants after application. The results suggested that this fungal agent has good potential for use in the control of rice planthoppers with no significant effects on rice microbial communities, representing an alternative strategy for the control of rice pests.

Alteration of the gut microbiota in tumor necrosis factor-α antagonist-treated collagen-induced arthritis mice.

AIM: Gut microbiota play an important role in rheumatoid arthritis (RA). Biological therapies targeting tumor necrosis factor-α (TNF-α) have been used for treatment in RA patients. However, whether TNF-α antagonist has some influence on gut microbiota is still unknown. This study aims to investigate the distribution of gut microbiota in collagen-induced arthritis (CIA) mice treated with the TNF-α antagonist etanercept. METHODS: Collagen-induced arthritis mice were induced by type II collagen. Cytokine expression was detected by real-time polymerase chain reaction. 16S ribosomal RNA sequencing was performed to characterize the gut microbiota in CIA mice treated with vehicle or etanercept. Sequencing reads were processed by Microbial Ecology software program. RESULTS: Compared with vehicle-treated mice, we showed that CIA mice treated with etanercept led to attenuation of inflammation and reduced expression of TNF-α, interferon (IFN)-γ, interleukin (IL)-6 and IL-21. Meanwhile, results showed operational taxonomic units, richness estimators and the diversity indices of gut microbiota in etanercept-treated mice were lower than that in vehicle-treated mice. Moreover, bacterial abundance analyses showed that genus Escherichia/Shigella was more abundant in etanercept-treated mice, and Lactobacillus, Clostridium XlVa, Tannerella were less abundant. The altered bacterial genus was correlated with TNF-α, IFN-γ, IL-6, IL-21 and IL-10. CONCLUSION: Our results revealed that TNF-α antagonist treatment can reduce the abundance and diversity of gut microbiota in CIA mice. Targeted gut microbiota may be a new therapeutic strategy for the treatment of RA.

Transcriptomic Analysis of the Brown Planthopper, Nilaparvata lugens, at Different Stages after Metarhizium anisopliae Challenge.

: Nilaparvata lugens is one of the major pests of rice and results in substantial yield loss every year. Our previous study found that the entomopathogenic fungus Metarhizium anisopliae showed effective potential for controlling this pest. However, the mechanisms underlying M. anisopliae infection of N. lugens are not well known. In the present study, we further examined the transcriptome of N. lugens at 4 h, 8 h, 16 h, and 24 h after M. anisopliae infection by Illumina deep sequencing. In total, 174.17 Gb of data was collected after sequencing, from which 23,398 unigenes were annotated by various databases, including 3694 newly annotated genes. The results showed that there were 246 vs 75, 275 vs 586, 378 vs 1055, and 638 vs 182 up- and downregulated differentially expressed genes (DEGs) at 4 h, 8 h, 16 h, and 24 h after M. anisopliae infection, respectively. The biological functions and associated metabolic processes of these genes were determined with the Clusters of Orthologous Groups (COG), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The DEGs data were verified using RT-qPCR. These results indicated that the DEGs during the initial fungal infection appropriately reflected the time course of the response to the fungal infection. Taken together, the results of this study provide new insights into the molecular mechanisms underlying the insect host response to fungal infection, especially during the initial stage of infection, and may improve the potential control strategies for N. lugens.

Correlation between albumin to fibrinogen ratio, C-reactive protein to albumin ratio and Th17 cells in patients with rheumatoid arthritis.

BACKGROUND: The albumin to fibrinogen ratio (AFR) and the C-reactive protein to albumin ratio (CAR) have been served as inflammatory markers. However, their roles in RA remain unclear. We investigated the association of AFR/CAR with the concentration of autoantibodies and Th17 cells in RA. METHODS: A total of 196 RA patients, 200 patients with systemic lupus erythematosus (SLE), and 200 healthy donors (HD) who were admitted to the First Affiliated Hospital of Fujian Medical University were enrolled. The results of FIB, ALB, CRP, anti-cyclic citrullinated peptide antibodies (anti-CCP), rheumatoid factor (RF) and erythrocyte sedimentation rate (ESR) from RA patients and SLE patients were retrospectively analyzed. The percentage of Th17 cells in peripheral blood of RA patients was detected by flow cytometry, and the relative expression of TNF-α, IL-6 and IL-17A was detected by RT-qPCR. Correlation analysis of AFR/CAR and Th17 cells, CRP, ESR, TNF-α, IL-6 and IL-17A in RA was conducted. RESULTS: Compared with SLE patients and healthy donors (HD), AFR concentration was significantly lower (P < 0.01) in RA patients, while CAR concentration was significantly increased (P < 0.01) in RA patients. AFR showed negative correlation with CRP (r = -0.7103), ESR (r = -0.6542), RF (-0.2219), Th17 cells (r = -0.5952) and IL-17A (r = -0.4681). CAR was positively correlated with CRP (r = 0.9899), ESR (r = 0.605), RF (0.1867), Th17 cells (r = 0.6818), TNF-α (r = 0.3388), and IL-17A (r = 0.2046). CONCLUSIONS: The concentration of AFR in RA patients was reduced, while CAR concentration was increased. AFR and CAR are associated with CRP, ESR, RF, and Th17 cell ratios in RA patients, which can be used as potential indicators for determining RA inflammation.

Genome sequence of the progenitor of wheat A subgenome Triticum urartu.

Triticum urartu (diploid, AA) is the progenitor of the A subgenome of tetraploid (Triticum turgidum, AABB) and hexaploid (Triticum aestivum, AABBDD) wheat1,2. Genomic studies of T. urartu have been useful for investigating the structure, function and evolution of polyploid wheat genomes. Here we report the generation of a high-quality genome sequence of T. urartu by combining bacterial artificial chromosome (BAC)-by-BAC sequencing, single molecule real-time whole-genome shotgun sequencing 3 , linked reads and optical mapping4,5. We assembled seven chromosome-scale pseudomolecules and identified protein-coding genes, and we suggest a model for the evolution of T. urartu chromosomes. Comparative analyses with genomes of other grasses showed gene loss and amplification in the numbers of transposable elements in the T. urartu genome. Population genomics analysis of 147 T. urartu accessions from across the Fertile Crescent showed clustering of three groups, with differences in altitude and biostress, such as powdery mildew disease. The T. urartu genome assembly provides a valuable resource for studying genetic variation in wheat and related grasses, and promises to facilitate the discovery of genes that could be useful for wheat improvement.

Indirect comparison of the efficacy and safety of gefitinib and cetuximab-based therapy in patients with advanced non-small-cell lung cancer.

The aim of this study was to systematically evaluate the efficacy and safety of gefitinib and cetuximab-based therapies in patients with advanced non-small-cell lung cancer (NSCLC). The studies to be used for the comparisons were selected from the available literature on gefitinib and cetuximab-based therapies compared to conventional chemotherapy in patients with advanced NSCLC. The meta-analysis was performed with RevMan 5.0 software and the Bucher approach was applied to conduct the indirect comparisons. A total of 4 studies, including 935 patients, on gefitinib therapy vs. conventional chemotherapy and 4 studies, including 1,015 patients, on cetuximab-based therapy vs. conventional chemotherapy, were used for indirect comparisons. As regards efficacy, the risk ratio (RR) of objective response rate and 1-year survival rate between gefitinib and cetuximab-based therapies in patients with advanced NSCLC were 0.99 [95% confidence interval (CI): 0.75-1.32; P=0.9584] and 0.85 (95% CI: 0.71-1.01; P=0.0696), respectively, and the mean difference of progression-free survival and overall survival (OS) were -0.15 (95% CI: -0.90 to 0.60; P=0.6946) and -1.84 (95% CI: -3.53 to -0.15; P=0.0331), respectively. As regards safety, the RR of grade 3/4 adverse events (AEs) was 0.29 (95% CI: 0.19-0.44; P=0.0001). The results demonstrated that cetuximab-based therapy was superior to gefitinib therapy in terms of OS and inferior to gefitinib therapy in terms of AEs, whereas there were no significant differences in terms of efficacy and safety between the two therapies on other endpoints adopted for advanced NSCLC. However, further well-designed randomized controlled trials and continuous studies are required to confirm our findings.

Sequence-based SNP genotyping in durum wheat.

Marker development for marker-assisted selection in plant breeding is increasingly based on next-generation sequencing (NGS). However, marker development in crops with highly repetitive, complex genomes is still challenging. Here we applied sequence-based genotyping (SBG), which couples AFLP®-based complexity reduction to NGS, for de novo single nucleotide polymorphisms (SNP) marker discovery in and genotyping of a biparental durum wheat population. We identified 9983 putative SNPs in 6372 contigs between the two parents and used these SNPs for genotyping 91 recombinant inbred lines (RILs). Excluding redundant information from multiple SNPs per contig, 2606 (41%) markers were used for integration in a pre-existing framework map, resulting in the integration of 2365 markers over 2607 cM. Of the 2606 markers available for mapping, 91% were integrated in the pre-existing map, containing 708 SSRs, DArT markers, and SNPs from CRoPS technology, with a map-size increase of 492 cM (23%). These results demonstrate the high quality of the discovered SNP markers. With this methodology, it was possible to saturate the map at a final marker density of 0.8 cM/marker. Looking at the binned marker distribution (Figure 2), 63 of the 268 10-cM bins contained only SBG markers, showing that these markers are filling in gaps in the framework map. As to the markers that could not be used for mapping, the main reason was the low sequencing coverage used for genotyping. We conclude that SBG is a valuable tool for efficient, high-throughput and high-quality marker discovery and genotyping for complex genomes such as that of durum wheat.

Whole Genome Profiling provides a robust framework for physical mapping and sequencing in the highly complex and repetitive wheat genome.

BACKGROUND: Sequencing projects using a clone-by-clone approach require the availability of a robust physical map. The SNaPshot technology, based on pair-wise comparisons of restriction fragments sizes, has been used recently to build the first physical map of a wheat chromosome and to complete the maize physical map. However, restriction fragments sizes shared randomly between two non-overlapping BACs often lead to chimerical contigs and mis-assembled BACs in such large and repetitive genomes. Whole Genome Profiling (WGP™) was developed recently as a new sequence-based physical mapping technology and has the potential to limit this problem. RESULTS: A subset of the wheat 3B chromosome BAC library covering 230 Mb was used to establish a WGP physical map and to compare it to a map obtained with the SNaPshot technology. We first adapted the WGP-based assembly methodology to cope with the complexity of the wheat genome. Then, the results showed that the WGP map covers the same length than the SNaPshot map but with 30% less contigs and, more importantly with 3.5 times less mis-assembled BACs. Finally, we evaluated the benefit of integrating WGP tags in different sequence assemblies obtained after Roche/454 sequencing of BAC pools. We showed that while WGP tag integration improves assemblies performed with unpaired reads and with paired-end reads at low coverage, it does not significantly improve sequence assemblies performed at high coverage (25x) with paired-end reads. CONCLUSIONS: Our results demonstrate that, with a suitable assembly methodology, WGP builds more robust physical maps than the SNaPshot technology in wheat and that WGP can be adapted to any genome. Moreover, WGP tag integration in sequence assemblies improves low quality assembly. However, to achieve a high quality draft sequence assembly, a sequencing depth of 25x paired-end reads is required, at which point WGP tag integration does not provide additional scaffolding value. Finally, we suggest that WGP tags can support the efficient sequencing of BAC pools by enabling reliable assignment of sequence scaffolds to their BAC of origin, a feature that is of great interest when using BAC pooling strategies to reduce the cost of sequencing large genomes.

Sequence-based physical mapping of complex genomes by whole genome profiling.

We present whole genome profiling (WGP), a novel next-generation sequencing-based physical mapping technology for construction of bacterial artificial chromosome (BAC) contigs of complex genomes, using Arabidopsis thaliana as an example. WGP leverages short read sequences derived from restriction fragments of two-dimensionally pooled BAC clones to generate sequence tags. These sequence tags are assigned to individual BAC clones, followed by assembly of BAC contigs based on shared regions containing identical sequence tags. Following in silico analysis of WGP sequence tags and simulation of a map of Arabidopsis chromosome 4 and maize, a WGP map of Arabidopsis thaliana ecotype Columbia was constructed de novo using a six-genome equivalent BAC library. Validation of the WGP map using the Columbia reference sequence confirmed that 350 BAC contigs (98%) were assembled correctly, spanning 97% of the 102-Mb calculated genome coverage. We demonstrate that WGP maps can also be generated for more complex plant genomes and will serve as excellent scaffolds to anchor genetic linkage maps and integrate whole genome sequence data.

A pipeline for high throughput detection and mapping of SNPs from EST databases.

Single nucleotide polymorphisms (SNPs) represent the most abundant type of genetic variation that can be used as molecular markers. The SNPs that are hidden in sequence databases can be unlocked using bioinformatic tools. For efficient application of these SNPs, the sequence set should be error-free as much as possible, targeting single loci and suitable for the SNP scoring platform of choice. We have developed a pipeline to effectively mine SNPs from public EST databases with or without quality information using QualitySNP software, select reliable SNP and prepare the loci for analysis on the Illumina GoldenGate genotyping platform. The applicability of the pipeline was demonstrated using publicly available potato EST data, genotyping individuals from two diploid mapping populations and subsequently mapping the SNP markers (putative genes) in both populations. Over 7000 reliable SNPs were identified that met the criteria for genotyping on the GoldenGate platform. Of the 384 SNPs on the SNP array approximately 12% dropped out. For the two potato mapping populations 165 and 185 SNPs segregating SNP loci could be mapped on the respective genetic maps, illustrating the effectiveness of our pipeline for SNP selection and validation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11032-009-9377-5) contains supplementary material, which is available to authorized users.

Large-scale identification of polymorphic microsatellites using an in silico approach.

BACKGROUND: Simple Sequence Repeat (SSR) or microsatellite markers are valuable for genetic research. Experimental methods to develop SSR markers are laborious, time consuming and expensive. In silico approaches have become a practicable and relatively inexpensive alternative during the last decade, although testing putative SSR markers still is time consuming and expensive. In many species only a relatively small percentage of SSR markers turn out to be polymorphic. This is particularly true for markers derived from expressed sequence tags (ESTs). In EST databases a large redundancy of sequences is present, which may contain information on length-polymorphisms in the SSR they contain, and whether they have been derived from heterozygotes or from different genotypes. Up to now, although a number of programs have been developed to identify SSRs in EST sequences, no software can detect putatively polymorphic SSRs. RESULTS: We have developed PolySSR, a new pipeline to identify polymorphic SSRs rather than just SSRs. Sequence information is obtained from public EST databases derived from heterozygous individuals and/or at least two different genotypes. The pipeline includes PCR-primer design for the putatively polymorphic SSR markers, taking into account Single Nucleotide Polymorphisms (SNPs) in the flanking regions, thereby improving the success rate of the potential markers. A large number of polymorphic SSRs were identified using publicly available EST sequences of potato, tomato, rice, Arabidopsis, Brassica and chicken.The SSRs obtained were divided into long and short based on the number of times the motif was repeated. Surprisingly, the frequency of polymorphic SSRs was much higher in the short SSRs. CONCLUSION: PolySSR is a very effective tool to identify polymorphic SSRs. Using PolySSR, several hundred putative markers were developed and stored in a searchable database. Validation experiments showed that almost all markers that were indicated as putatively polymorphic by polySSR were indeed polymorphic. This greatly improves the efficiency of marker development, especially in species where there are low levels of polymorphism, like tomato. When combined with the new sequencing technologies PolySSR will have a big impact on the development of polymorphic SSRs in any species.PolySSR and the polymorphic SSR marker database are available from http://www.bioinformatics.nl/tools/polyssr/.

HaploSNPer: a web-based allele and SNP detection tool.

BACKGROUND: Single nucleotide polymorphisms (SNPs) and small insertions or deletions (indels) are the most common type of polymorphisms and are frequently used for molecular marker development. Such markers have become very popular for all kinds of genetic analysis, including haplotype reconstruction. Haplotypes can be reconstructed for whole chromosomes but also for specific genes, based on the SNPs present. Haplotypes in the latter context represent the different alleles of a gene. The computational approach to SNP mining is becoming increasingly popular because of the continuously increasing number of sequences deposited in databases, which allows a more accurate identification of SNPs. Several software packages have been developed for SNP mining from databases. From these, QualitySNP is the only tool that combines SNP detection with the reconstruction of alleles, which results in a lower number of false positive SNPs and also works much faster than other programs. We have build a web-based SNP discovery and allele detection tool (HaploSNPer) based on QualitySNP. RESULTS: HaploSNPer is a flexible web-based tool for detecting SNPs and alleles in user-specified input sequences from both diploid and polyploid species. It includes BLAST for finding homologous sequences in public EST databases, CAP3 or PHRAP for aligning them, and QualitySNP for discovering reliable allelic sequences and SNPs. All possible and reliable alleles are detected by a mathematical algorithm using potential SNP information. Reliable SNPs are then identified based on the reconstructed alleles and on sequence redundancy. CONCLUSION: Thorough testing of HaploSNPer (and the underlying QualitySNP algorithm) has shown that EST information alone is sufficient for the identification of alleles and that reliable SNPs can be found efficiently. Furthermore, HaploSNPer supplies a user friendly interface for visualization of SNP and alleles. HaploSNPer is available from http://www.bioinformatics.nl/tools/haplosnper/.