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Peas (Pisum sativum L.) serve as a vital model for plant development and stress research. The kinesin (KIN) gene family, encoding essential motor proteins, remains understudied in peas. Our research conducted a comprehensive genomic analysis of the KIN genes in peas, identifying 105 genes categorized into seven subfamilies based on evolutionary relationships, gene structures, conserved motifs, and interaction networks. A comparative analysis with Arabidopsis and soybean KIN gene families showed a non-uniform distribution of PsKIN genes across subfamilies. Homology analysis revealed that the PsKIN family has undergone segmental duplication and is under negative selection pressures, with conserved genes on chromosomes Ps5, Ps6, and Ps7 playing a significant role in pea evolution. Transcriptomics revealed 38 PsKIN genes with distinct tissue-specific expression, with PsKIN76, PsKIN96, PsKIN82, and PsKIN103 showing significant levels in roots, lateral roots, stems, petals, and seeds, respectively. Differential expression under drought and saline stress was observed, with PsKIN8, PsKIN11, PsKIN54 upregulated under drought, and PsKIN47 and PsKIN51 under saline stress. These genes are potential candidates for improving plant stress tolerance. This study offers insights into the pea KIN gene family, highlighting their potential in enhancing plant stress tolerance and setting a stage for future research.

Abstract Background Vegetable soybean is an important vegetable crop in world. Seed size and soluble sugar content are considered crucial indicators of quality in vegetable soybean, and there is a lack of clarity on the molecular basis of grain quality in vegetable soybean. Results In this context, we performed a comprehensive comparative transcriptome analysis of seeds between a high-sucrose content and large-grain variety (Zhenong 6, ZN6) and a low-sucrose content and small-grain variety (Williams 82, W82) at three developmental stages, i.e. stage R5 (Beginning Seed), stage R6 (Full Seed), and stage R7 (Beginning Maturity). The transcriptome analysis showed that 17,107 and 13,571 differentially expressed genes (DEGs) were identified in ZN6 at R6 (vs. R5) and R7 (vs. R6), respectively, whereas 16,203 and 16,032 were detected in W82. Gene expression pattern and DEGs functional enrichment proposed genotype-specific biological processes during seed development. The genes participating in soluble sugar biosynthesis such as FKGP were overexpressed in ZN6, whereas those responsible for lipid and protein metabolism such as ALDH3 were more enhanced in W82, exhibiting different dry material accumulation between two genotypes. Furthermore, hormone-associated transcriptional factors involved in seed size regulation such as BEH4 were overrepresented in ZN6, exhibiting different seed size regulation processes between two genotypes. Conclusions Herein, we not only discovered the differential expression of genes encoding metabolic enzymes involved in seed composition, but also identified a type of hormone-associated transcriptional factors overexpressed in ZN6, which may regulate seed size and soluble content. This study provides new insights into the underlying causes of differences in the soybean metabolites and appearance, and suggests that genetic data can be used to improve its appearance and textural quality.

This study aimed to explore the role of the trehalose-6-phosphate synthase (TPS) gene family in the adaptation of peas to environmental stress. A comprehensive analysis of the PsTPS gene family identified 20 genes with conserved domains and specific chromosomal locations. Phylogenetic analysis delineated evolutionary relationships, while gene structure analysis revealed compositional insights, and motif analysis provided functional insights. Cis-regulatory element identification predicted gene regulation patterns. Tissue-specific and stress-induced expression profiling highlighted eight genes with ubiquitous expression, with PsTPS15 and PsTPS18 displaying elevated expression levels in roots, nodules, and young stems, and PsTPS13 and PsTPS19 expression downregulated in seeds. Transcriptome analysis identified a differential expression of 20 PsTPS genes, highlighting the significance of 14 genes in response to drought and salinity stress. Notably, under drought conditions, the expression of PsTPS4 and PsTPS6 was initially upregulated and then downregulated, whereas that of PsTPS15 and PsTPS19 was downregulated. Salinity stress notably altered the expression of PsTPS4, PsTPS6, and PsTPS19. Taken together, these findings elucidate the regulatory mechanisms of the PsTPS gene family and their potential as genetic targets for enhancing crop stress tolerance.

ABSTRACT Ascochyta blight caused by Ascochyta pisi is a major constraint to pea (Pisum sativum L.) production worldwide. Deciphering the pathogenic mechanism of A. pisi on peas will help in breeding resistant pea varieties and developing effective approaches for disease management. However, little is known about the genomic features and pathogenic factors of A. pisi. In this study, we first report that A. pisi is one of the causal agents of ascochyta blight disease of pea in China. The genome of the representative isolate A. pisi HNA23 was sequenced using PacBio and Illumina sequencing technologies. The HNA23 genome assembly is almost 41.5 Mb in size and harbors 10,796 putative protein-encoding genes. We predicted 555 carbohydrate-active enzymes (CAZymes), 1,008 secreted proteins, 74 small secreted cysteine-rich proteins (SSCPs), and 26 secondary metabolite biosynthetic gene clusters (SMGCs). A comparison of A. pisi genome features with the features of 6 other available genomes of Ascochyta species showed that CAZymes, the secretome, and SMGCs of this genus are considerably conserved. Importantly, the transcriptomes of HNA23 during infection of peas at three stages were further analyzed. We found that 245 CAZymes and 29 SSCPs were upregulated at all three tested infection stages. SMGCs were also trigged, but most of them were induced at only one stage of infection. Together, our results provide important genomic information on Ascochyta spp. and offer insights into the pathogenesis of A. pisi. IMPORTANCE Ascochyta blight is a major disease of legumes worldwide. Ascochyta pisi and other Ascochyta species have been identified as pathogens of ascochyta blight. Here, we first report that A. pisi causes ascochyta blight of pea in China, and we report the high-quality, fully annotated genome of A. pisi. Comparative genome analysis was performed to elucidate the differences and similarities among 7 Ascochyta species. We predict abundant CAZymes (569 per species), secreted proteins (851 per species), and prolific secondary metabolite gene clusters (29 per species) in these species. We identified a set of genes that may be responsible for fungal virulence based on transcriptomes in planta, including CAZymes, SSCPs, and secondary metabolites. The findings from the comparative genome analysis highlight the genetic diversity and help in understanding the evolutionary relationship of Ascochyta species. In planta transcriptome analysis provides reliable information for further investigation of the mechanism of the interaction between Ascochyta spp. and legumes.

Background and purpose: Approximately 60% of patients with hepatocellular carcinoma (HCC) are diagnosed at an advanced stage, therefore cannot receive timely and effective treatment. At present, the sensitivity of serum biomarkers commonly used in the diagnosis of HCC is low. In this paper, through the differential expression analysis of plasma exosomal proteome, the candidate exosome protein markers which may be used in the diagnosis of HCC were identified. Methods: First, we performed shot-gun proteome mass spectrometry assays in the plasma exosomes from the discovery cohort [including 4 healthy control (HC) group and 4 HCC patients group], and identified differentially expressed proteins by qualitative and quantitative analyses. Then, we carried out enzyme-linked immunosorbent assay (ELISA) in plasma samples of an independent verification cohort [including 56 HCC patients group, 20 liver cirrhosis (LC) patients group and 48 HC group], and evaluated the diagnostic value of the candidate protein in HCC. Results: In the discovery cohort, we identified a total of 1 434 exosomal proteins, of which CD48 exhibited higher levels in HCC than in HC. We further verified in the validation cohort by ELISA that CD48 was markedly higher in HCC compared with LC and HC groups, with the area under receiver operating characteristic (ROC) curve (AUC) of 0.886. When combined with plasma alpha-fetoprotein (AFP), the AUC reached 0.970. Conclusion: The plasma exosomal CD48 protein can be used as a candidate diagnostic biomarker for HCC, and its combination with AFP may further improve the clinical diagnostic ability for HCC.