Background: The phenomenon of codon usage bias is known to exist in many genomes and is mainly determined by mutation and selection. Codon usage bias analysis is a suitable strategy for identifying the principal evolutionary driving forces in different organisms. Sunflower (Helianthus annuus L.) is an annual crop that is cultivated worldwide as ornamentals, food plants and for their valuable oil. The WRKY family genes in plants play a central role in diverse regulation and multiple stress responses. Evolutionary analysis of WRKY family genes of H. annuus can provide rich genetic information for developing hybridization resources of the genus Helianthus. Results: Bases composition analysis showed the average GC content of WRKY genes of H. annuus was 43.42%, and the average GC3 content was 39.60%, suggesting that WRKY gene family prefers A/T(U) ending codons. There were 29 codons with relative synonymous codon usage (RSCU) greater than 1 and 22 codons ending with A and U base. The effective number of codons (ENC) and codon adaptation index (CAI) in WRKY genes ranged from 43.47–61.00 and 0.14–0.26, suggesting that the codon bias was weak and WRKY genes expression level was low. Neutrality analysis found a significant correlation between GC12 and GC3. ENC-plot showed most genes on or close to the expected curve, suggesting that mutational bias played a major role in shaping codon usage. The Parity Rule 2 plot (PR2) analysis showed that the usage of AT and GC was disproportionate. A total of three codons were identified as the optimal codons. Conclusion: Apart from natural selection effects, most of the genetic evolution in the H. annuus WRKY genome might be driven by mutation pressure. Our results provide a theoretical foundation for elaborating the genetic architecture and mechanisms of H. annuus and contributing to enrich H. annuus genetic resources.

Many plant pathogen secretory proteins are known to be elicitors or pathogenic factors,which play an important role in the host-pathogen interaction process. Bioinformatics approaches make possible the large scale prediction and analysis of secretory proteins from the Puccinia helianthi transcriptome. The internet-based software SignalP v4.1, TargetP v1.01, Big-PI predictor, TMHMM v2.0 and ProtComp v9.0 were utilized to predict the signal peptides and the signal peptide-dependent secreted proteins among the 35,286 ORFs of the P. helianthi transcriptome. 908 ORFs (accounting for 2.6% of the total proteins) were identified as putative secretory proteins containing signal peptides. The length of the majority of proteins ranged from 51 to 300 amino acids (aa), while the signal peptides were from 18 to 20 aa long. Signal peptidase I (SpI) cleavage sites were found in 463 of these putative secretory signal peptides. 55 proteins contained the lipoprotein signal peptide recognition site of signal peptidase II (SpII). Out of 908 secretory proteins, 581 (63.8%) have functions related to signal recognition and transduction, metabolism, transport and catabolism. Additionally, 143 putative secretory proteins were categorized into 27 functional groups based on Gene Ontology terms, including 14 groups in biological process, seven in cellular component, and six in molecular function. Gene ontology analysis of the secretory proteins revealed an enrichment of hydrolase activity. Pathway associations were established for 82 (9.0%) secretory proteins. A number of cell wall degrading enzymes and three homologous proteins specific to Phytophthora sojae effectors were also identified, which may be involved in the pathogenicity of the sunflower rust pathogen. This investigation proposes a new approach for identifying elicitors and pathogenic factors. The eventual identification and characterization of 908 extracellularly secreted proteins will advance our understanding of the molecular mechanisms of interactions between sunflower and rust pathogen and will enhance our ability to intervene in disease states.

Real-time RT-PCR has become a common and robust technique to detect and quantify low-abundance mRNA expression and is a prefered tool when examining fungal gene expression in infected host tissues. However, correct evaluation of gene expression data requires accurate and reliable normalization against a reference transcript. Thus, the identification of reference genes with stable expression during different conditions is of paramount importance. Here, we present a study where in vitro and in planta experiments were used to validate the expression stability of reference gene candidates of Puccinia helianthi Schw., an obligate pathogen that causes rust in sunflower (Helianthus annuus). Eleven reference genes of P. helianthi were validated at different growth stages. Excel-based software geNorm, BestKeeper and NormFinder were used to evaluate the reference gene transcript stabilities. Of eleven reference gene candidates tested, three were stably expressed in urediniospores, germinating growth stage and in planta. Two of these genes (UBC, EF2), encoding ubiquitin-conjugating enzyme and elongation factor 2, proved to be the most stable set of reference genes under the experimental conditions used. We found that UBC and EF2 are suitable candidates for for the standardization of gene expression studies in the plant pathogen P. helianthi and potentially other related pathogens.

Background: Plague, caused by the bacterium Yersinia pestis, is a zoonotic disease that poses considerable threats to human health. Nucleic acid tests are crucial for plague surveillance and the rapid detection of Y. pestis. However, inhibitors in complex samples such as soil and animal tissues often hamper nucleic acid detection, leading to a reduced rate of identifying low concentrations of Y. pestis. To address this challenge, we developed a sensitive and specific droplet digital polymerase chain reaction (ddPCR) assay for detecting Y. pestis DNA from soil and animal tissue samples. Methods: Three genes (ypo2088, caf1, and pla) from Y. pestis were used to develop a multi-target ddPCR assay. The limits of detection (LoD), reproducibility, and specificity were assessed for bacterial genomic DNA samples. The ability of the assay to detect low concentrations of Y. pestis DNA from simulated soil and mouse liver tissue samples was respectively evaluated and compared with that of quantitative real-time PCR (qPCR). Results: The results showed that the ddPCR LoDs ranged from 6.2 to 15.4 copies/reaction for the target genes, with good reproducibility and high specificity for Y. pestis. By testing 130 soil and mouse liver tissue samples spiked with Y. pestis, the ddPCR assay exhibited a better sensitivity than that of the qPCR assay used in the study, with LoDs of 10² colony forming units (CFU)/100 mg soil and 10³ CFU/20 mg liver. Moreover, the assay presented good quantitative linearity (R² = 0.99) for Y. pestis at 10³–10⁶ CFU/sample for soil and liver samples. Conclusion: The ddPCR assay presented good performance for detecting Y. pestis DNA from soil and mouse tissue samples, showing great potential for improving the detection rate of low concentrations of Y. pestis in plague surveillance and facilitating the early diagnosis of plague cases.

Background: Sunflower (Helianthusannuus) is one of the most important economic crops in oilseed production worldwide. The different cultivars exhibit variability in their resistance genes. The NAC transcription factor (TF) family plays diverse roles in plant development and stress responses. With the completion of the H. annuus genome sequence, the entire complement of genes coding for NACs has been identified. However, the reference genome of a single individual cannot cover all the genetic information of the species. Results: Considering only a single reference genome to study gene families will miss many meaningful genes. A pangenome-wide survey and characterization of the NAC genes in sunflower species were conducted. In total, 139 HaNAC genes are identified, of which 114 are core and 25 are variable. Phylogenetic analysis of sunflower NAC proteins categorizes these proteins into 16 subgroups. 138 HaNACs are randomly distributed on 17 chromosomes. SNP-based haplotype analysis shows haplotype diversity of the HaNAC genes in wild accessions is richer than in landraces and modern cultivars. Ten HaNAC genes in the basal stalk rot (BSR) resistance quantitative trait loci (QTL) are found. A total of 26 HaNAC genes are differentially expressed in response to Sclerotinia head rot (SHR). A total of 137 HaNAC genes are annotated in Gene Ontology (GO) and are classified into 24 functional groups. GO functional enrichment analysis reveals that HaNAC genes are involved in various functions of the biological process. Conclusions: We identified NAC genes in H. annuus (HaNAC) on a pangenome-wide scale and analyzed S. sclerotiorum resistance-related NACs. This study provided a theoretical basis for further genomic improvement targeting resistance-related NAC genes in sunflowers.