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Background Species in genus Amomum always have important medicinal and economic values. Classification of Amomum using morphological characters has long been a challenge because they exhibit high similarity. The main goals of this study were to mine genetic markers from cp genomes for Amomum species identification and discover their evolutionary history through comparative analysis. Results Three species Amomum villosum , Amomum maximum and Amomum longipetiolatum were sequenced and annotated for the complete chloroplast (cp) genomes, and the cp genomes of A. longipetiolatum and A. maximum were the first reported. Three cp genomes exhibited typical quadripartite structures with 163,269-163,591 bp in length. Each genome encodes 130 functional genes including 79 protein-coding, 26 tRNAs and 3 rRNAs genes. 113-152 SSRs and 99 long repeats were identified in the three cp genomes. By designing specific primers, we amplified the highly variable loci and the mined genetic marker ccs A exhibited a relatively high species identification resolution in Amomum . The nonsynonymous and synonymous substitution ratios (Ka/Ks) in Amomum and Alpinia showed that most genes were subjected to a purifying selection. Phylogenetic analysis revealed the evolutionary relationships of Amomum and Alpinia species and proved that Amomum is paraphyletic. In addition, the sequenced sample of A. villosum was found to be a hybrid, becoming the first report of natural hybridization of this genus. Meanwhile, the high-throughput sequencing-based ITS2 analysis was proved to be an efficient tool for interspecific hybrid identification and with the help of the chloroplast genome, the hybrid parents can be also be determined. Conclusion The comparative analysis and mined genetic markers of cp genomes were conducive to species identification and evolutionary relationships of Amomum .

Premise of the study: Simple sequence repeat (SSR) markers were developed for Plasmopara obducens, the causal agent of the newly emergent downy mildew disease of Impatiens walleriana. Methods and Results: A 202-Mb draft genome assembly was generated from P. obducens using Illumina technology and mined to identify 13,483 SSR motifs. Primers were synthesized for 62 marker candidates, of which 37 generated reliable PCR products. Testing of the 37 markers using 96 P. obducens samples showed 96% of the markers were polymorphic, with 2–6 alleles observed. Observed and expected heterozygosity ranged from 0.000–0.892 and 0.023–0.746, respectively. Just 17 markers were sufficient to identify all multilocus genotypes. Conclusions: These are the first SSR markers available for this pathogen, and one of the first molecular resources. These markers will be useful in assessing variation in pathogen populations and determining the factors contributing to the emergence of destructive impatiens downy mildew disease.

Generally, chloroplast genomes of angiosperms are always highly conserved but carry a certain number of variation among species. In this study, chloroplast genomes of 13 species from Datureae tribe that are of importance both in ornamental gardening and medicinal usage were studied. In addition, seven chloroplast genomes from Datureae together with two from Solanaceae species retrieved from the National Center for Biotechnology Information (NCBI) were integrated into this study. The chloroplast genomes ranged in size from 154,686 to 155,979 and from 155,497 to 155,919 bp for species of Datura and Brugmansia , respectively. As to Datura and Brugmansia , a total of 128 and 132 genes were identified, in which 83 and 87 protein coding genes were identified, respectively; Furthermore, 37 tRNA genes and 8 rRNA genes were both identified in Datura and Brugmansia. Repeats analysis indicated that the number and type varied among species for Simple sequence repeat (SSR), long repeats, and tandem repeats ranged in number from 53 to 59, 98 to 99, and 22 to 30, respectively. Phylogenetic analysis based on the plastid genomes supported the monophyletic relationship among Datura and Brugmansia and Trompettia , and a refined phylogenic relationships among each individual was resolved. In addition, a species-specific marker was designed based on variation spot that resulted from a comparative analysis of chloroplast genomes and verified as effective maker for identification of D. stramonium and D. stramonium var. inermis . Interestingly, we found that 31 genes were likely to be under positive selection, including genes encoding ATP protein subunits, photosystem protein subunit, ribosome protein subunits, NAD(P)H dehydrogenase complex subunits, and clp P, pet B, rbc L, rpo Cl, ycf 4, and cem A genes. These genes may function as key roles in the adaption to diverse environment during evolution. The diversification of Datureae members was dated back to the late Oligocene periods. These chloroplast genomes are useful genetic resources for taxonomy, phylogeny, and evolution for Datureae.

In systematic botany, species delimitations are addressed most frequently. The desert date Balanites is a plant with the controversial membership in the Balanitaceae and Zygophyllaceae families. The morphological characters of Balanites showed close relationship with the members of Zygophyllaceae while barcode genes showed relatedness with the members of Celastraceae. On the other hand, Gymnosporia montana, a Celastraceae plant, showed close relatedness with Zygophyllaceae. In this study, cpDNAs (plastomes) of Balanites aegyptiaca and G. montana were extracted, sequenced, and annotated for the detailed analysis. These plastomes were compared and contrasted with plastomes of other members of allied groups from the NCBI databases. The comparative genomics study revealed that B. aegyptiaca related more with family Zygophyllaceae than Celastraceae. Detailed studies performed for molecular marker analysis showed distinction in marker patterns. It is concluded that B. aegyptiaca, assigned in a separate family, may be justifiable at genomic level, and screened markers can be used for identification and authentication. The nucleotide probes identified can be used for identification and authentication of these medicinally important plants.

Marine bacteria of the genus Cobetia, which are promising sources of unique enzymes and secondary metabolites, were found to be complicatedly identified both by phenotypic indicators due to their ecophysiology diversity and 16S rRNA sequences because of their high homology. Therefore, searching for the additional methods for the species identification of Cobetia isolates is significant. The species-specific coding sequences for the enzymes of each functional category and different structural families were applied as additional molecular markers. The 13 closely related Cobetia isolates, collected in the Pacific Ocean from various habitats, were differentiated by the species-specific PCR patterns. An alkaline phosphatase PhoA seems to be a highly specific marker for C. amphilecti. However, the issue of C. amphilecti and C. litoralis, as well as C. marina and C. pacifica, belonging to the same or different species remains open.

Background Single-cell RNA sequencing (scRNA-seq) allows the detection of rare cell types in complex tissues. The detection of markers for rare cell types is useful for further biological analysis of, for example, flow cytometry and imaging data sets for either physical isolation or spatial characterization of these cells. However, only a few computational approaches consider the problem of selecting specific marker genes from scRNA-seq data. Results Here, we propose sc2marker, which is based on the maximum margin index and a database of proteins with antibodies, to select markers for flow cytometry or imaging. We evaluated the performances of sc2marker and competing methods in ranking known markers in scRNA-seq data of immune and stromal cells. The results showed that sc2marker performed better than the competing methods in accuracy, while having a competitive running time.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer mainly caused by hepatitis viral infection. Early stage diagnosis is still challenging due to its asymptomatic behavior so there is an urgent need for effective biomarkers. This study aimed to identify effective diagnostic biomarker or therapeutic target for HCC. Label-free quantitative mass spectrometry was performed to analyze protein expression in HCC and control tissues. Protein-protein interaction (PPI) analysis was done using the STRING database and hub proteins were identified by Cytohubba. The survival analysis and expressions profiling of hub proteins were performed by using GEPIA. Functional and pathway enrichment analysis were carried out using Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG). A total of 1539 proteins were identified, of which 116 were differentially expressed proteins (DEPs). PPI network analysis revealed 10 hub proteins; EGFR, GAPDH, HSP90AA1, MMP9, PTPRC, CD44, ANXA5, PECAM1, MMP2, and CDK1. Among these, GAPDH, MMP9, ANXA5, HSP90AA1, and CDK1 were significantly associated with low survival rate (  ⩽ .05). Moreover, MMP9 and CDK1 were showed significantly increased expression in tumor tissues as compared to control (  ⩽ .05). The GO analysis based on biological process, cellular components and molecular function indicated that DEPs were enriched in stress response, vesicle and extracellular space, protein binding and enzyme activity. The KEGG pathway analysis showed that the thyroid hormone synthesis pathway is the most enriched. The hub proteins GAPDH, HSP90AA1, MMP9, ANXA5, and CDK1 demonstrated significant prognostic potential, could be used as promising theragnostic biomarkers for HCC.

Microsatellites are one of the important genome characterizations that can be a valuable resource for variety identification, genetic diversity, phylogenetic analysis, as well as comparative and conservation genomics research. Here, we developed comprehensive microsatellites through genome-wide mining for the threatened cetacean Indo-Pacific humpback dolphin (Sousa chinensis). We found 87,757 microsatellites with 2–6 bp nucleotide motifs, showing that about 32.5 microsatellites per megabase comprises microsatellites sequences. Approximately 97.8% of the markers developed in this study were consistent with the published identified markers. About 75.3% microsatellites were with dinucleotide motifs, followed by tetranucleotide motifs (17.4%), sharing the same composition pattern as other cetaceans. The microsatellites were not evenly distributed in the S. chinensis genome, mainly in non-coding regions, with only about 0.5% of the markers located in coding regions. The microsatellite-containing genes were mainly functionally enriched in the methylation process, probably demonstrating the potential impacts of microsatellites on biological functions. Polymorphic microsatellites were developed between different genders of S. chinensis, which was expected to lay the foundation for genetic diversity investigation in cetaceans. The specific markers for a male Indo-Pacific humpback dolphin will provide comprehensive and representative male candidate markers for sex identification, providing a potential biomolecular tool for further analysis of population structure and social behavior of wild populations, population trend evaluation, and species conservation management.

Determining the tumor origin in humans is vital in clinical applications of molecular diagnostics. Metastatic cancer is usually a very aggressive disease with limited diagnostic procedures, despite the fact that many protocols have been evaluated for their effectiveness in prognostication. Research has shown that dysregulation in miRNAs (a class of non-coding, regulatory RNAs) is remarkably involved in oncogenic conditions. This research paper aims to develop a machine learning model that processes an array of miRNAs in 1097 metastatic tissue samples from patients who suffered from various stages of breast cancer. The suggested machine learning model is fed with miRNA quantitative read count data taken from The Cancer Genome Atlas Data Repository. Two main feature-selection techniques have been used, mainly Neighborhood Component Analysis and Minimum Redundancy Maximum Relevance, to identify the most discriminant and relevant miRNAs for their up-regulated and down-regulated states. These miRNAs are then validated as biological identifiers for each of the four cancer stages in breast tumors. Both machine learning algorithms yield performance scores that are significantly higher than the traditional fold-change approach, particularly in earlier stages of cancer, with Neighborhood Component Analysis and Minimum Redundancy Maximum Relevance achieving accuracy scores of up to 0.983 and 0.931, respectively, compared to 0.920 for the FC method. This study underscores the potential of advanced feature-selection methods in enhancing the accuracy of cancer stage identification, paving the way for improved diagnostic and therapeutic strategies in oncology.