Metabolomics of early blight (Alternaria solani) susceptible tomato (Solanum lycopersicum) unfolds key biomarker metabolites and involved metabolic pathways.

Tomato (Solanum lycopersicum) is among the most important commercial horticultural crops worldwide. The crop quality and production is largely hampered due to the fungal pathogen Alternaria solani causing necrotrophic foliage early blight disease. Crop plants usually respond to the biotic challenges with altered metabolic composition and physiological perturbations. We have deciphered altered metabolite composition, modulated metabolic pathways and identified metabolite biomarkers in A. solani-challenged susceptible tomato variety Kashi Aman using Liquid Chromatography-Mass Spectrometry (LC-MS) based metabolomics. Alteration in the metabolite feature composition of pathogen-challenged (m/z 9405) and non-challenged (m/z 9667) plant leaves including 8487 infection-exclusive and 8742 non-infection exclusive features was observed. Functional annotation revealed putatively annotated metabolites and pathway mapping indicated their enrichment in metabolic pathways, biosynthesis of secondary metabolites, ubiquinone and terpenoid-quinones, brassinosteroids, steroids, terpenoids, phenylpropanoids, carotenoids, oxy/sphingolipids and metabolism of biotin and porphyrin. PCA, multivariate PLS-DA and OPLS-DA analysis showed sample discrimination. Significantly up regulated 481 and down regulated 548 metabolite features were identified based on the fold change (threshold ≥ 2.0). OPLS-DA model based on variable importance in projection (VIP scores) and FC threshold (> 2.0) revealed 41 up regulated discriminant metabolite features annotated as sphingosine, fecosterol, melatonin, serotonin, glucose 6-phosphate, zeatin, dihydrozeatin and zeatin-ß-D-glucoside. Similarly, 23 down regulated discriminant metabolites included histidinol, 4-aminobutyraldehyde, propanoate, tyramine and linalool. Melatonin and serotonin in the leaves were the two indoleamines being reported for the first time in tomato in response to the early blight pathogen. Receiver operating characteristic (ROC)-based biomarker analysis identified apigenin-7-glucoside, uridine, adenosyl-homocysteine, cGMP, tyrosine, pantothenic acid, riboflavin (as up regulated) and adenosine, homocyctine and azmaline (as down regulated) biomarkers. These results could aid in the development of metabolite-quantitative trait loci (mQTL). Furthermore, stress-induced biosynthetic pathways may be the potential targets for modifications through breeding programs or genetic engineering for improving crop performance in the fields.

Transcriptomics reveals key genes responsible for functional diversity in pectoralis major muscles of native black Kadaknath and broiler chicken.

RNA sequencing-based expression profiles from pectoralis major muscles of black meat (Kadaknath) and white meat (broiler) chicken were compared to identify differentially expressed genes. A total of 156 genes with log2 fold change ≥ ± 2.0 showed higher expression in Kadaknath and 68 genes were expressed at a lower level in comparison to broiler. Significantly enriched biological functions of up-regulated genes in Kadaknath were skeletal muscle cell differentiation, regulation of response to reactive oxygen, positive regulation of fat cell differentiation and melanosome. Significant ontology terms up-regulated in broiler included DNA replication origin binding, G-protein coupled receptor signaling pathway and chemokine activity. Highly inter-connected differentially expressed genes in Kadaknath (ATFs, C/EPDs) were observed to be important regulators of cellular adaptive functions, while in broiler, the hub genes were involved in cell cycle progression and DNA replication. The study is an attempt to get an insight into the transcript diversity of pectoralis major muscles of Kadaknath and broiler chicken. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03682-0.

Revelation of genes associated with energy generating metabolic pathways in the fighter type Aseel chicken of India through skeletal muscle transcriptome sequencing.

In this study, comparative analysis of skeletal muscle transcriptome was carried out for four biological replicates of Aseel, a fighter type breed and Punjab Brown, a meat type breed of India. The profusely expressed genes in both breeds were related to muscle contraction and motor activity. Differential expression analysis identified 961 up-regulated and 979 down-regulated genes in Aseel at a threshold of log2 fold change ≥ ±2.0 (padj<0.05). Significantly enriched KEGG pathways in Aseel included metabolic pathways and oxidative phosphorylation, with higher expression of genes associated with fatty acid beta-oxidation, formation of ATP by chemiosmotic coupling, response to oxidative stress, and muscle contraction. The highly connected hub genes identified through gene network analysis in the Aseel gamecocks were HNF4A, APOA2, APOB, APOC3, AMBP, and ACOT13, which are primarily associated with energy generating metabolic pathways. The up-regulated genes in Punjab Brown chicken were found to be related to muscle growth and differentiation. There was enrichment of pathways such as focal adhesion, insulin signaling pathway and ECM receptor interaction in these birds. The results presented in this study help to improve our understanding of the molecular mechanisms associated with fighting ability and muscle growth in Aseel and Punjab Brown chicken, respectively.

Untargeted Metabolomics of Alternaria solani-Challenged Wild Tomato Species Solanum cheesmaniae Revealed Key Metabolite Biomarkers and Insight into Altered Metabolic Pathways.

Untargeted metabolomics of moderately resistant wild tomato species Solanum cheesmaniae revealed an altered metabolite profile in plant leaves in response to Alternaria solani pathogen. Leaf metabolites were significantly differentiated in non-stressed versus stressed plants. The samples were discriminated not only by the presence/absence of specific metabolites as distinguished markers of infection, but also on the basis of their relative abundance as important concluding factors. Annotation of metabolite features using the Arabidopsis thaliana (KEGG) database revealed 3371 compounds with KEGG identifiers belonging to biosynthetic pathways including secondary metabolites, cofactors, steroids, brassinosteroids, terpernoids, and fatty acids. Annotation using the Solanum lycopersicum database in PLANTCYC PMN revealed significantly upregulated (541) and downregulated (485) features distributed in metabolite classes that appeared to play a crucial role in defense, infection prevention, signaling, plant growth, and plant homeostasis to survive under stress conditions. The orthogonal partial least squares discriminant analysis (OPLS-DA), comprising a significant fold change (≥2.0) with VIP score (≥1.0), showed 34 upregulated biomarker metabolites including 5-phosphoribosylamine, kaur-16-en-18-oic acid, pantothenate, and O-acetyl-L-homoserine, along with 41 downregulated biomarkers. Downregulated metabolite biomarkers were mapped with pathways specifically known for plant defense, suggesting their prominent role in pathogen resistance. These results hold promise for identifying key biomarker metabolites that contribute to disease resistive metabolic traits/biosynthetic routes. This approach can assist in mQTL development for the stress breeding program in tomato against pathogen interactions.

Study on the muscle transcriptome of two diverse Indian backyard poultry breeds acclimatized to different agro-ecological conditions.

OBJECTIVE: Free-range (FR) poultry production systems are associated with quality products and improved welfare. All the 19 diverse chicken breeds of India have evolved under the FR system and are adapted to different agro-climatic conditions. It is vital to explore indigenous germplasm with modern genomic tools to have insights into genomic characteristics of production traits and adaptation. METHODS: In this study, breast tissue transcriptome profiles were generated and analyzed from four biological replicates of two indigenous backyard poultry breeds of India-Ankaleshwar, a breed of the mainland, and Nicobari, a breed adapted to islands. The read quality of sequences was checked by FASTQC and processed reads were aligned to the reference genome (bGalGal1). RESULTS: More than 94% mapping to the reference genome was observed for all samples. A total of 12,790 transcripts were common across both groups, while 657 were expressed only in Ankaleshwar and 169 in Nicobari. The highest expressed genes across both groups were associated mainly with muscle structure, contraction, and energy metabolism. The highly expressed genes identified in Ankaleshwar were involved in fatty acid catabolism and oxidative stress mitigation. Functional terms, pathways, and hub genes in Nicobari participated in muscle fiber growth, adipogenesis, and fatty acid anabolism. A key hub gene (RAC1) in Nicobari is a potential candidate affecting the laying rate in chickens. The qRT-PCR results also substantiate the RNA-seq results. CONCLUSION: The findings provide a precious molecular resource to advance understanding of the genetic basis of adaptation, meat quality, and egg production in backyard chickens.

Expression analysis of genes responsible for amino acid biosynthesis in halophilic bacterium Salinibacter ruber.

The degeneracy of the genetic code allows for multiple codons to encode the same amino acid. However, alternative codons and amino acids are used unevenly among genes, a phenomenon termed codon-usage bias. Genes regulating amino acid biosynthesis of Salinibacter ruber, an extremely halophilic bacterium were studied in order to determine the synonymous codon usage patterns. Factors responsible for codon usage variation among the genes were investigated using codon usage indices and multi-variate statistical approach. Overall codon usage data analysis indicated that codons ending in G and/or C were predominant among the genes. Multi-variate statistical analysis showed that there was a single major trend in the codon usage variation among the genes, which had a strong positive correlation (r = 0.93, P < 0.01) with (G + C) content of the genes. Further, correlation analysis indicated that genes with higher expression level and showing a greater degree of codon usage bias were GC-rich and preferred codons with C or G nucleotides at the third position. A set of thirteen codons were identified through Chi-square test as optimal codons, which were preferred in highly expressed genes. It could be concluded that mutational bias had a profound effect on codon usage pattern. In addition, translational selections also operated with a proper balance, making the genes translationally more efficient. The frequency of these codons appeared to be correlated with the level of gene expression and might be a useful indicator in the case of genes (or open-reading-frames) whose expression levels are unknown.