Genome-Wide Identification of the Brassinosteroid Signal Kinase Gene Family and Its Profiling under Salinity Stress.

Alfalfa (Medicago L.) is a high-quality perennial leguminous forage with the advantages of salt tolerance, mowing tolerance, high protein content, and other economically valuable characteristics. As the sixth class of plant hormones, brassinosteroids (BRs) play indispensable roles in modulating a variety of plant growth, maturation, and environmental adaptation processes, thereby influencing vegetal expansion and development. Brassinosteroid signal kinases (BSKs) are key cytoplasmic receptor kinases downstream of the BR signaling transduction pathway, participating in plant growth, development, and stress regulation. However, the phylogenetic and expression pattern analyses of the BSK gene family among the five alfalfa species have rarely been reported; in this study, 52 BSK family members were found in the genomes of the five subspecies, and phylogenetic trees were constructed according to protein sequences, allowing us to categorize all BSKs into seven distinct groups. Domain, conserved motif, and exon-intron structural analyses showed that most BSK members were relatively conserved, except for MtBSK3-2, MtBSK7-1, and MtBSK7-2, which may be truncated members. Intra-species collinearity and Ka/Ks analyses showed that purifying selection influenced BSK genes during evolution; most of the cis-acting elements in the promoter region were associated with responses, such as light, defense, and stress, anaerobic induction, MeJA, and abscisic acid. Expression pattern analysis indicated that the majority of alfalfa genes exhibited downregulation after reaching a peak at 0.5 h after treatment with 250 mM NaCl, especially for MsBSK14, MsBSK15, MsBSK17, MsBSK19, and MsBSK21; meanwhile, MsBSK4, MsBSK7, and MsBSK9 increased and were highly expressed at 12 h, demonstrating significantly altered expression patterns under salt stress; furthermore, MsBSK4, MsBSK7, and MsBSK9 exhibited expression specifically in the leaves. qRT-PCR analysis confirmed the expression trends for MsBSK4, MsBSK7, MsBSK9, MsBSK14, MsBSK15, and MsBSK16 matched the transcriptome data. However, the trends for MsBSK17, MsBSK19, and MsBSK21 diverged from the transcriptome data. Our study may provide a foundation for further functional analyses of BSK genes in growth, development, and salt stress tolerance in alfalfa.

Exploring the role of CDCA4 in liver hepatocellular carcinoma using bioinformatics analysis and experiments.

Liver hepatocellular carcinoma (LIHC) encompasses diverse therapeutic approaches, among which targeted therapy has gained significant prominence in recent years. The identification of numerous targets and the increasing clinical application of targeted drugs have greatly improved LIHC treatment. However, the precise role of CDCA4 (Cell Division Cycle Associated 4), as well as its underlying mechanisms and prognostic implications in LIHC, remains unclear. CDCA4 expression levels in LIHC were analyzed using multiple databases including the cancer genome atlas (TCGA), gene expression profiling interactive analysis (GEPIA), and ULCAN, as well as the datasets E_TABM_36, GSE144269, GSE14520, and GSE54236. The prognostic value of CDCA4 was then evaluated. Subsequently, the association between CDCA4 and immune cells was investigated. Enrichment analysis (GSEA) was utilized to investigate the functional roles and pathways linked to CDCA4. Additionally, the methylation patterns and drug sensitivity of CDCA4 were examined. A predictive model incorporating immune genes related to CDCA4 was developed. The TISCH dataset was used to investigate the single-cell expression patterns of CDCA4. Finally, validation of CDCA4 expression levels was conducted through RT-PCR, Western blotting, and immunohistochemistry. CDCA4 exhibited significant overexpression in LIHC and demonstrated significant correlations with clinical features. High expression of CDCA4 is associated with a poorer prognosis. Analysis of immune infiltration and enrichment revealed its association with the immune microenvironment. Furthermore, its expression is correlated with methylation and mutation patterns. CDCA4 is associated with 19 drugs. Prognostic models utilizing CDCA4 demonstrate favorable effectiveness. T cell subtypes were found to be associated with CDCA4 through single-cell analysis. The conclusive experiment provided evidence of significant upregulation of CDCA4 in LIHC. The high expression of CDCA4 in LIHC is associated with prognostic significance and is highly expressed in T cell subtypes, providing a new therapeutic target and potential therapeutic strategy for LIHC.