Bemisia tabaci (BT) (Gennadius), often known as the sweet potato whitefly, is a group of whiteflies that are currently causing major damage to agricultural crops. More than 600 plant species are infected by BT, which thrives in a wide range of temperature conditions. In addition, it harms caused by extracting plant sap. It also serves as a carrier for many plant viruses. Heat-shock proteins are crucial in facilitating the insect's ability to expand its geographic range, endure various stressful circumstances, and reproduce. Using RNA sequencing and differential expression analysis, we identified a significant number of differentially expressed genes (DEGs). These DEGs are associated with metabolic pathways, energy production, protein synthesis, and nucleotide metabolism, which are crucial for cellular function and survival, particularly under conditions of heat stress. Our findings contribute to the understanding of gene expression through the functional annotation in various biological processes, including ion binding and metabolic pathways, likely contributing to heat stress response mechanisms. Validation of the expressed gene patterns using qRT-PCR for the confirmation of the differential expression of key genes associated with stress response pathways. Additionally, the study identified SSR markers for genetic characterization and provided insights into the genetic diversity.
{"title":"Unraveling the molecular response: Transcriptomics analysis of heat shocked Bemisia tabaci (Asia II 5 biotype)","authors":"Bulbul Ahmed , Subham Dutta , Kousik Atta , Mritunjoy Barman","doi":"10.1016/j.egg.2025.100386","DOIUrl":"10.1016/j.egg.2025.100386","url":null,"abstract":"<div><div><em>Bemisia tabaci</em> (BT) (Gennadius), often known as the sweet potato whitefly, is a group of whiteflies that are currently causing major damage to agricultural crops. More than 600 plant species are infected by BT, which thrives in a wide range of temperature conditions. In addition, it harms caused by extracting plant sap. It also serves as a carrier for many plant viruses. Heat-shock proteins are crucial in facilitating the insect's ability to expand its geographic range, endure various stressful circumstances, and reproduce. Using RNA sequencing and differential expression analysis, we identified a significant number of differentially expressed genes (DEGs). These DEGs are associated with metabolic pathways, energy production, protein synthesis, and nucleotide metabolism, which are crucial for cellular function and survival, particularly under conditions of heat stress. Our findings contribute to the understanding of gene expression through the functional annotation in various biological processes, including ion binding and metabolic pathways, likely contributing to heat stress response mechanisms. Validation of the expressed gene patterns using qRT-PCR for the confirmation of the differential expression of key genes associated with stress response pathways. Additionally, the study identified SSR markers for genetic characterization and provided insights into the genetic diversity.</div></div>","PeriodicalId":37938,"journal":{"name":"Ecological Genetics and Genomics","volume":"36 ","pages":"Article 100386"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144632778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01Epub Date: 2025-07-07DOI: 10.1016/j.egg.2025.100384
Diriba Shanko , Mebeaselassie Andargie
Sesame is an important oilseed crop recognized for its high oil content and superior quality, making it valuable to human consumption. The seed coat color is also an important agronomic trait affecting market value, nutritional quality, and seed physiology. Earlier studies have documented the quantitative trait loci (QTLs) associated with seed coat color has shown the most significant impact on the manifestation of this trait. Also, another study recognized a cross between two sesame accessions (white-seeded, P1) and (black-seeded, P2) has played a crucial role in QTL mapping within sesame. Furthermore, hybridization between parents which underwent successive self-fertilization up to the F6 generation, resulted in the identification of the genes, implicated in black pigment synthesis and the regulation of sesame seed coat color. However, there are significant gaps in the mapping of Quantitative Trait Loci (QTL) associated with sesame seed coat traits. This is largely due to the inadequate understanding of genetic architecture and the identification of candidate genes responsible for color variation, especially when considering diverse genetic backgrounds and varying environmental conditions. The primary problem is that complex inheritance, low mapping resolution, environmental variability, and lack of gene validation make it hard to identify stable and functional QTLs mapping for sesame seed coat color. The study aims to conduct a comprehensive synthesis of the existing knowledge, methodologies, and findings related to the genetic mapping of sesame seed coat color, identify current gaps and propose future research paths focused on marker-assisted selection and the discovery of functional genes.
{"title":"Quantitative trait loci (QTLs) mapping of seed coat colors in sesame (Sesamum indicum L.): A review","authors":"Diriba Shanko , Mebeaselassie Andargie","doi":"10.1016/j.egg.2025.100384","DOIUrl":"10.1016/j.egg.2025.100384","url":null,"abstract":"<div><div>Sesame is an important oilseed crop recognized for its high oil content and superior quality, making it valuable to human consumption. The seed coat color is also an important agronomic trait affecting market value, nutritional quality, and seed physiology. Earlier studies have documented the quantitative trait loci (QTLs) associated with seed coat color has shown the most significant impact on the manifestation of this trait. Also, another study recognized a cross between two sesame accessions (white-seeded, P1) and (black-seeded, P2) has played a crucial role in QTL mapping within sesame. Furthermore, hybridization between parents which underwent successive self-fertilization up to the F6 generation, resulted in the identification of the genes, implicated in black pigment synthesis and the regulation of sesame seed coat color. However, there are significant gaps in the mapping of Quantitative Trait Loci (QTL) associated with sesame seed coat traits. This is largely due to the inadequate understanding of genetic architecture and the identification of candidate genes responsible for color variation, especially when considering diverse genetic backgrounds and varying environmental conditions. The primary problem is that complex inheritance, low mapping resolution, environmental variability, and lack of gene validation make it hard to identify stable and functional QTLs mapping for sesame seed coat color. The study aims to conduct a comprehensive synthesis of the existing knowledge, methodologies, and findings related to the genetic mapping of sesame seed coat color, identify current gaps and propose future research paths focused on marker-assisted selection and the discovery of functional genes.</div></div>","PeriodicalId":37938,"journal":{"name":"Ecological Genetics and Genomics","volume":"36 ","pages":"Article 100384"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144588631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The pseudostem weevil Odoiporus longicollis, a major pest of banana confers serious crop losses. The cellulose- and terpene-rich diet requires a high reliance on gut microbiome for nutrition. While Puranik et al. (2024) explored the whole gut bacteriome (16S) of this pest, spatial distribution of microbiome across gut sections remained uncharacterized. Here we present the region-specific microbiome of foregut, midgut and hindgut of O. longicollis, encompassing bacteria, fungi and other eukaryotes. Among bacteria, Firmicutes (Bacilli) predominated in the foregut while Proteobacteria (Gammaproteobacteria) dominated midgut and hindgut. Erysipelotrichia was notably higher in the hindgut. The Enterobacteriaceae (Klebsiella, Enterobacter) subjugated all sections with differential distribution of Raoultella, Citrobacter and Escherichia. Lactobacillaceae (Leuconostoc, Lactiplantibacillus) were prominent in foregut while Streptococcaceae (Lactococcus) dominated the mid- and hindgut. Notably, the primary endosymbiont Candidatus Nardonella was restricted to the foregut. Fungal phyla Ascomycota and Basidiomycota were abundant. Debaryomycetaceae (Scheffersomyces, Millerozyma, Candida) dominated the foregut and hindgut, whereas Saccharomycodaceae (Hanseniaspora, Yarrowia) characterized the midgut. Other eukaryotes i.e., Alveolata, Apicomplexa, Oomycota, Discoba, Amoebozoa, Chloroplast-Stramenopile (CS) clade, Euglenozoa, Heterolobosea and Perkinsozoa were distributed differentially. The hindgut emerged as the species-rich and taxonomically diverse region. Fungal species were rich in foregut and midgut, and diverse in hindgut and foregut. Gene profiling revealed distinct patterns in carbohydrate metabolism, terpene degradation and nitrogen cycle, uncovering dependent and independent modes of cellulolysis in O. longicollis. The findings improved the understanding of the spatial dynamics and functional potential of the O. longicollis gut microbiome, offering implications for microbiome-based pest control strategies.
{"title":"Microbiome of different gut compartments of banana pseudostem weevil Odoiporus longicollis (Coleoptera: Curculionidae) offers an understanding of site-specific diversity and metabolism: Whole-metagenome shotgun sequencing approach","authors":"Sreeramulu Bhuvaragavan , Kannan Sruthi , Akshaya Panigrahi , Sundaram Janarthanan","doi":"10.1016/j.egg.2025.100397","DOIUrl":"10.1016/j.egg.2025.100397","url":null,"abstract":"<div><div>The pseudostem weevil <em>Odoiporus longicollis</em>, a major pest of banana confers serious crop losses. The cellulose- and terpene-rich diet requires a high reliance on gut microbiome for nutrition. While Puranik et al. (2024) explored the whole gut bacteriome (16S) of this pest, spatial distribution of microbiome across gut sections remained uncharacterized. Here we present the region-specific microbiome of foregut, midgut and hindgut of <em>O. longicollis</em>, encompassing bacteria, fungi and other eukaryotes. Among bacteria, Firmicutes (Bacilli) predominated in the foregut while Proteobacteria (Gammaproteobacteria) dominated midgut and hindgut. Erysipelotrichia was notably higher in the hindgut. The Enterobacteriaceae (<em>Klebsiella</em>, <em>Enterobacter</em>) subjugated all sections with differential distribution of <em>Raoultella</em>, <em>Citrobacter</em> and <em>Escherichia</em>. Lactobacillaceae (<em>Leuconostoc</em>, <em>Lactiplantibacillus</em>) were prominent in foregut while Streptococcaceae (<em>Lactococcus</em>) dominated the mid- and hindgut. Notably, the primary endosymbiont <em>Candidatus</em> Nardonella was restricted to the foregut. Fungal phyla Ascomycota and Basidiomycota were abundant. Debaryomycetaceae (<em>Scheffersomyces</em>, <em>Millerozyma</em>, <em>Candida</em>) dominated the foregut and hindgut, whereas Saccharomycodaceae (<em>Hanseniaspora</em>, <em>Yarrowia</em>) characterized the midgut. Other eukaryotes i.e., Alveolata, Apicomplexa, Oomycota, Discoba, Amoebozoa, Chloroplast-Stramenopile (CS) clade, Euglenozoa, Heterolobosea and Perkinsozoa were distributed differentially. The hindgut emerged as the species-rich and taxonomically diverse region. Fungal species were rich in foregut and midgut, and diverse in hindgut and foregut. Gene profiling revealed distinct patterns in carbohydrate metabolism, terpene degradation and nitrogen cycle, uncovering dependent and independent modes of cellulolysis in <em>O. longicollis</em>. The findings improved the understanding of the spatial dynamics and functional potential of the <em>O. longicollis</em> gut microbiome, offering implications for microbiome-based pest control strategies.</div></div>","PeriodicalId":37938,"journal":{"name":"Ecological Genetics and Genomics","volume":"36 ","pages":"Article 100397"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01Epub Date: 2025-08-05DOI: 10.1016/j.egg.2025.100393
Abu Feyisa Meka , Ebisa Chaluma Abdeta , Gessesse Kebede Bekele , Musin Kelel Abas , Mesfin Tafesse Gemeda
Sof Umer Cave represents a unique and understudied ecosystem that harbors bacteria of significant industrial relevance. Despite its potential, the culturable bacteria from this cave with antimicrobial and antioxidant properties remain unexplored. This study aimed to isolate and characterize such bacteria using a several types of culture media. A total of 40 isolates were selected based on morphological distinctiveness from rock, sediment, and soil samples, with respective distribution rates of 52.36 %, 32.62 %, and 15.02 %. These isolates exhibited diverse morphological features, including differences in colony appearance and pigment production. Primary screening revealed that 45 % of the isolates were showed antimicrobial activity against reference pathogens. Among these, four isolates, AsucR1, AsucR2, AsucR5, and AsucR9, exhibited particularly strong antimicrobial activity. Antioxidant activity, assessed via the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, revealed varying degrees of free radical scavenging potential, as indicated by their half maximal inhibitory concentration (IC50) values. Molecular identification using 16S-rRNA partial gene sequencing confirmed that the four potent isolates were closely related to Stenotrophomonas maltophilia, Chryseobacterium shigense, and Cupriavidus alkaliphilus, all of which are known producers of bioactive compounds. These findings highlight the Sof Umer Cave untapped potential for novel drug discovery and underscore the need for further investigation into its microbial diversity.
{"title":"Isolation and characterization of antimicrobial and antioxidant-producing culturable bacteria from Sof Umer Cave, Ethiopia","authors":"Abu Feyisa Meka , Ebisa Chaluma Abdeta , Gessesse Kebede Bekele , Musin Kelel Abas , Mesfin Tafesse Gemeda","doi":"10.1016/j.egg.2025.100393","DOIUrl":"10.1016/j.egg.2025.100393","url":null,"abstract":"<div><div>Sof Umer Cave represents a unique and understudied ecosystem that harbors bacteria of significant industrial relevance. Despite its potential, the culturable bacteria from this cave with antimicrobial and antioxidant properties remain unexplored. This study aimed to isolate and characterize such bacteria using a several types of culture media. A total of 40 isolates were selected based on morphological distinctiveness from rock, sediment, and soil samples, with respective distribution rates of 52.36 %, 32.62 %, and 15.02 %. These isolates exhibited diverse morphological features, including differences in colony appearance and pigment production. Primary screening revealed that 45 % of the isolates were showed antimicrobial activity against reference pathogens. Among these, four isolates, AsucR1, AsucR2, AsucR5, and AsucR9, exhibited particularly strong antimicrobial activity. Antioxidant activity, assessed via the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, revealed varying degrees of free radical scavenging potential, as indicated by their half maximal inhibitory concentration (IC<sub>50</sub>) values. Molecular identification using 16S-rRNA partial gene sequencing confirmed that the four potent isolates were closely related to Stenotrophomonas maltophilia, Chryseobacterium shigense, and Cupriavidus alkaliphilus, all of which are known producers of bioactive compounds. These findings highlight the Sof Umer Cave untapped potential for novel drug discovery and underscore the need for further investigation into its microbial diversity.</div></div>","PeriodicalId":37938,"journal":{"name":"Ecological Genetics and Genomics","volume":"36 ","pages":"Article 100393"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144781319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01Epub Date: 2025-07-02DOI: 10.1016/j.egg.2025.100382
Precious Mutambara, Kabwe Nkongolo
Most studies on effects of temperature on biota conducted in field conditions are impacted by other factors such as soil pH, organic matter, moisture and pollution. The objective of this study was to examine the effects of increasing temperatures in controlled environments on soil enzymatic activities and bacterial and fungal composition and diversity. Soil samples were incubated at three temperatures (23 °C, 30 °C, and 37 °C). Fresh (untreated/unincubated) soil samples were used as references. Activities of β-glucosidase, β-N-acetylglucosaminidase, aryl sulfatase, acid phosphatase, alkaline phosphatase, and peroxidase exhibited strong responses to temperature variations with activities peaking at 30 °C and declining at 37 °C. Bacterial and fungal communities were analyzed using the Illumina MiniSeq system. The abundance of the top five bacterial genera (with the exception of Bradyrhizobium) revealed an inverse relationship between temperature and abundance that decreases as the temperatures increase. For Fungi, Trichomas was the most dominant genus in fresh soil with 40 % of relative abundance while Umbelopsis was dominant in soils incubated at 23 °C, 30 °C, and 37 °C) with values ranging from 20 % to 34 %). Shannon diversity entropy for samples treated at 23 °C and 30 °C were identical (5.1) in fungal communities while fresh samples and those at 37 °C had values of 4.2 and 4.7, respectively. This closeness between 23 °C and 30 °C was confirmed by Principal Coordinate Analyses based on the weighted UniFrac distance matrix for both bacterial and fungal communities. Overall, the data indicate that elevated temperatures significantly alter microbial function and community composition, with specific genera responding to temperature changes.
大多数在野外条件下进行的温度对生物群影响的研究都受到土壤pH、有机质、湿度和污染等其他因素的影响。本研究的目的是研究在受控环境中温度升高对土壤酶活性、细菌和真菌组成和多样性的影响。土壤样品在23°C、30°C和37°C三个温度下孵育。新鲜（未经处理/未孵育）土壤样品作为参考。β-葡萄糖苷酶、β- n -乙酰氨基葡萄糖苷酶、芳基硫酸盐酶、酸性磷酸酶、碱性磷酸酶和过氧化物酶的活性对温度变化有较强的响应，在30℃时活性达到峰值，在37℃时活性下降。使用Illumina MiniSeq系统分析细菌和真菌群落。前5个细菌属（除缓生根瘤菌外）的丰度与温度呈反比关系，随温度升高而降低。在新鲜土壤中，滴虫属（Trichomas）的相对丰度为40%，而伞形opsis （Umbelopsis）在23°C、30°C和37°C的土壤中相对丰度为20% ~ 34%。在23°C和30°C处理的样品中，真菌群落的Shannon多样性熵相同（5.1），而新鲜样品和37°C处理的样品分别为4.2和4.7。基于细菌和真菌群落加权UniFrac距离矩阵的主坐标分析证实了23°C和30°C之间的这种接近性。总体而言，这些数据表明，温度升高会显著改变微生物的功能和群落组成，特定的属会对温度变化做出反应。
{"title":"Effects of elevated temperatures on soil enzymatic activities and bacterial and fungal community composition and diversity","authors":"Precious Mutambara, Kabwe Nkongolo","doi":"10.1016/j.egg.2025.100382","DOIUrl":"10.1016/j.egg.2025.100382","url":null,"abstract":"<div><div>Most studies on effects of temperature on biota conducted in field conditions are impacted by other factors such as soil pH, organic matter, moisture and pollution. The objective of this study was to examine the effects of increasing temperatures in controlled environments on soil enzymatic activities and bacterial and fungal composition and diversity. Soil samples were incubated at three temperatures (23 °C, 30 °C, and 37 °C). Fresh (untreated/unincubated) soil samples were used as references. Activities of β-glucosidase, β-N-acetylglucosaminidase, aryl sulfatase, acid phosphatase, alkaline phosphatase, and peroxidase exhibited strong responses to temperature variations with activities peaking at 30 °C and declining at 37 °C. Bacterial and fungal communities were analyzed using the Illumina MiniSeq system. The abundance of the top five bacterial genera (with the exception of <em>Bradyrhizobium</em>) revealed an inverse relationship between temperature and abundance that decreases as the temperatures increase. For Fungi, <em>Trichomas</em> was the most dominant genus in fresh soil with 40 % of relative abundance while <em>Umbelopsis</em> was dominant in soils incubated at 23 °C, 30 °C, and 37 °C) with values ranging from 20 % to 34 %). Shannon diversity entropy for samples treated at 23 °C and 30 °C were identical (5.1) in fungal communities while fresh samples and those at 37 °C had values of 4.2 and 4.7, respectively. This closeness between 23 °C and 30 °C was confirmed by Principal Coordinate Analyses based on the weighted UniFrac distance matrix for both bacterial and fungal communities. Overall, the data indicate that elevated temperatures significantly alter microbial function and community composition, with specific genera responding to temperature changes.</div></div>","PeriodicalId":37938,"journal":{"name":"Ecological Genetics and Genomics","volume":"36 ","pages":"Article 100382"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144564011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-16DOI: 10.1016/j.egg.2025.100351
Osiel Silva Gonçalves , Mateus Ferreira Santana
Soil bacteria play a fundamental role in maintaining soil ecosystem functions, yet their genetic and metabolic adaptations to complex environments remain underexplored. To address this question, we analyzed the genomes of four soil bacteria isolated from tropical savanna soil, uncovering key insights into their metabolic potential and ecological roles. Our findings indicate that these bacteria represent novel species, including new strains of Bosea, Nocardioides, Cupriavidus, and Enterobacter roggenkampii. Their genomes encode essential genes and pathways related to central metabolism, particularly those involved in sugar and amino acid metabolism, highlighting their adaptive strategies for survival in soil environments. These strains also play important roles in biogeochemical cycles, including carbon, nitrogen, and sulfur cycling, as well as plant growth promotion. Furthermore, we identified 164 defense genes across 32 defense families, along with at least one antimicrobial resistance (AMR) gene in each strain. Additionally, twelve biosynthetic gene clusters were identified in three strains. The diverse genetic arsenal of these bacteria, including defense mechanisms, antimicrobial resistance genes, and secondary metabolite biosynthesis, may enhance their ability to survive and compete in the complex and dynamic soil environment.
{"title":"Genomic blueprint of four soil bacteria with insights into their potential adaptation mechanisms in tropical savanna","authors":"Osiel Silva Gonçalves , Mateus Ferreira Santana","doi":"10.1016/j.egg.2025.100351","DOIUrl":"10.1016/j.egg.2025.100351","url":null,"abstract":"<div><div>Soil bacteria play a fundamental role in maintaining soil ecosystem functions, yet their genetic and metabolic adaptations to complex environments remain underexplored. To address this question, we analyzed the genomes of four soil bacteria isolated from tropical savanna soil, uncovering key insights into their metabolic potential and ecological roles. Our findings indicate that these bacteria represent novel species, including new strains of <em>Bosea</em>, <em>Nocardioides</em>, <em>Cupriavidus</em>, and <em>Enterobacter roggenkampii</em>. Their genomes encode essential genes and pathways related to central metabolism, particularly those involved in sugar and amino acid metabolism, highlighting their adaptive strategies for survival in soil environments. These strains also play important roles in biogeochemical cycles, including carbon, nitrogen, and sulfur cycling, as well as plant growth promotion. Furthermore, we identified 164 defense genes across 32 defense families, along with at least one antimicrobial resistance (AMR) gene in each strain. Additionally, twelve biosynthetic gene clusters were identified in three strains. The diverse genetic arsenal of these bacteria, including defense mechanisms, antimicrobial resistance genes, and secondary metabolite biosynthesis, may enhance their ability to survive and compete in the complex and dynamic soil environment.</div></div>","PeriodicalId":37938,"journal":{"name":"Ecological Genetics and Genomics","volume":"35 ","pages":"Article 100351"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143859451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-14DOI: 10.1016/j.egg.2025.100349
Hossein Zeinalzadeh-Tabrizi , Leyla Nazari
Sweet corn stands as a crucial staple in the food industry, offering consumers a nutritious and diverse option. However, understanding its response to density stress remains pivotal for enhancing its resilience and productivity. We employed Weighted Gene Co-expression Network Analysis (WGCNA), differential gene expression analysis, and Least Absolute Shrinkage and Selection Operator (LASSO) regression to dissect its molecular mechanisms. Four key genes (GRMZM2G129246, GRMZM2G143602, GRMZM2G162670, and GRMZM5G851026) and six hub genes (GRMZM2G162175, GRMZM2G155746, GRMZM2G092325, GRMZM2G328612, AC218148.2_FGT008, and GRMZM5G879127) were identified. Gene expression prediction under density stress was performed using various classifiers including Naïve Bayes, Simple Logistic, KStar, MultiClassClassifier, JRip, LMT, and RandomForest. Utilizing Simple Logistic and LMT models, we achieved an impressive overall accuracy of 100 % in predicting density stress response based on hub gene expression profiles. This highlights the robustness and reliability of our findings, paving the way for developing targeted interventions and breeding strategies to bolster sweet corn's resilience to density stress. Key genes include glycolate oxidase 1, essential for oxidative stress tolerance, and CK2 alpha subunit, involved in signaling pathways for abiotic stress adaptation. Other important proteins, like those from the phosphatidylinositolglycan synthase family, contribute to lipid metabolism and stress signaling. Additionally, uncharacterized genes, LOC103635295 and LOC100274670, are highlighted for their potential roles in stress regulation. The study emphasizes the need for continued research on these genes to enhance crop resilience and productivity.
{"title":"Machine learning-based transcriptome mining to discover key genes for density stress in sweet corn","authors":"Hossein Zeinalzadeh-Tabrizi , Leyla Nazari","doi":"10.1016/j.egg.2025.100349","DOIUrl":"10.1016/j.egg.2025.100349","url":null,"abstract":"<div><div>Sweet corn stands as a crucial staple in the food industry, offering consumers a nutritious and diverse option. However, understanding its response to density stress remains pivotal for enhancing its resilience and productivity. We employed Weighted Gene Co-expression Network Analysis (WGCNA), differential gene expression analysis, and Least Absolute Shrinkage and Selection Operator (LASSO) regression to dissect its molecular mechanisms. Four key genes (GRMZM2G129246, GRMZM2G143602, GRMZM2G162670, and GRMZM5G851026) and six hub genes (GRMZM2G162175, GRMZM2G155746, GRMZM2G092325, GRMZM2G328612, AC218148.2_FGT008, and GRMZM5G879127) were identified. Gene expression prediction under density stress was performed using various classifiers including Naïve Bayes, Simple Logistic, KStar, MultiClassClassifier, JRip, LMT, and RandomForest. Utilizing Simple Logistic and LMT models, we achieved an impressive overall accuracy of 100 % in predicting density stress response based on hub gene expression profiles. This highlights the robustness and reliability of our findings, paving the way for developing targeted interventions and breeding strategies to bolster sweet corn's resilience to density stress. Key genes include glycolate oxidase 1, essential for oxidative stress tolerance, and CK2 alpha subunit, involved in signaling pathways for abiotic stress adaptation. Other important proteins, like those from the phosphatidylinositolglycan synthase family, contribute to lipid metabolism and stress signaling. Additionally, uncharacterized genes, LOC103635295 and LOC100274670, are highlighted for their potential roles in stress regulation. The study emphasizes the need for continued research on these genes to enhance crop resilience and productivity.</div></div>","PeriodicalId":37938,"journal":{"name":"Ecological Genetics and Genomics","volume":"35 ","pages":"Article 100349"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-05DOI: 10.1016/j.egg.2025.100347
Andrews Appiah , Richard Akromah , Alexander Wireko Kena , Benjamin Annor , Stephen Amoah , Emmanuel Yaw Owusu , Benjamin Karikari
Knowledge of genetic diversity among germplasm is a prerequisite in any crop improvement programme. The present study, therefore, aimed to determine the extent of genetic variability and relationship in Ghanaian okra genotypes using morphological and simple sequence repeats (SSR) markers. A total of 40 okra accessions were collected from all agro-ecological zones of Ghana and evaluated under optimal conditions in Ghana in 2020 using alpha lattice design. Analysis of variance revealed significant (p < 0.01) variations among the genotypes for all traits studied, indicating high variability among the genotypes studied which could be exploited to develop improved okra varieties. Genotypes: Avata, Ayigbe, Baabo, Sunyani aba and Ponana ponana were identified as the superior genotypes which could further be tested and promoted among farmers. The 40 okra accessions were classified into four (4) major clusters based on the morphological traits as well as the SSR markers. The most discriminating traits identified by the principal component analysis were days to first flowering, days to first fruiting, first flowering node, fruit width, fruit yield, plant height at first flowering, leaf breadth, leaf length and the number of internodes. The findings from this study provide valuable information for okra conservation, breeding, and utilization.
{"title":"Genetic diversity among Ghanaian Okra (Abelmoschus esculentus L.) Germplasm using Morphological and Molecular markers","authors":"Andrews Appiah , Richard Akromah , Alexander Wireko Kena , Benjamin Annor , Stephen Amoah , Emmanuel Yaw Owusu , Benjamin Karikari","doi":"10.1016/j.egg.2025.100347","DOIUrl":"10.1016/j.egg.2025.100347","url":null,"abstract":"<div><div>Knowledge of genetic diversity among germplasm is a prerequisite in any crop improvement programme. The present study, therefore, aimed to determine the extent of genetic variability and relationship in Ghanaian okra genotypes using morphological and simple sequence repeats (SSR) markers. A total of 40 okra accessions were collected from all agro-ecological zones of Ghana and evaluated under optimal conditions in Ghana in 2020 using alpha lattice design. Analysis of variance revealed significant (<em>p</em> < 0.01) variations among the genotypes for all traits studied, indicating high variability among the genotypes studied which could be exploited to develop improved okra varieties. Genotypes: Avata, Ayigbe, Baabo, Sunyani aba and Ponana ponana were identified as the superior genotypes which could further be tested and promoted among farmers. The 40 okra accessions were classified into four (4) major clusters based on the morphological traits as well as the SSR markers. The most discriminating traits identified by the principal component analysis were days to first flowering, days to first fruiting, first flowering node, fruit width, fruit yield, plant height at first flowering, leaf breadth, leaf length and the number of internodes. The findings from this study provide valuable information for okra conservation, breeding, and utilization.</div></div>","PeriodicalId":37938,"journal":{"name":"Ecological Genetics and Genomics","volume":"35 ","pages":"Article 100347"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143791350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-03-15DOI: 10.1016/j.egg.2025.100342
Manish Sharma, Prakashkumar R. Patel, Mukeshbhai S. Patel, Manubhai P. Patel
Chickpea (Cicer arietinum L.) is an important cool season food legume but an array of environmental conditions limits its production; therefore, introducing compatible cultivars to a range of environments is an important goal in breeding programs. The present research focused on investigating the impact of genotype-environment interaction on the yield stability and performance of chickpea genotypes across four different locations by deploying the AMMI and GGE biplot method. Over multiple harvests, yield component parameters such as the total number of pods per plant (PP) and Seed index (SI) were assessed as these factors directly contribute to yield enhancement. The AMMI analysis of variance for grain yield revealed significant genotype, environment and G × E interaction indicating the presence of variability among the genotypes and environments. AMMI model exposed the genotypes G5 and G6, as best performer and environment E1 and E2 as most favourable ones for seed yield. GGE biplots revealed that the most desirable genotypes exhibiting high levels of stability along with high yield potential were G6 and G4, both of which are adaptable to a variety of environments. This study also identified the genotypes that adapted well and uniquely to each environment. With its high representativeness and discriminative capacity, environment E1 (Sardarkrushinagar) was determined to be the optimum test environment for choosing genotypes that are typically acclimated. According to our findings, genotypes that are stable and high performing across conditions may be advocated for commercial cultivation or use in crop breeding programmes for enhanced performance.
{"title":"Stability assessment for selection of elite chickpea genotypes across multi-environment based on AMMI and GGE biplots","authors":"Manish Sharma, Prakashkumar R. Patel, Mukeshbhai S. Patel, Manubhai P. Patel","doi":"10.1016/j.egg.2025.100342","DOIUrl":"10.1016/j.egg.2025.100342","url":null,"abstract":"<div><div>Chickpea (<em>Cicer arietinum</em> L.) is an important cool season food legume but an array of environmental conditions limits its production; therefore, introducing compatible cultivars to a range of environments is an important goal in breeding programs. The present research focused on investigating the impact of genotype-environment interaction on the yield stability and performance of chickpea genotypes across four different locations by deploying the AMMI and GGE biplot method. Over multiple harvests, yield component parameters such as the total number of pods per plant (PP) and Seed index (SI) were assessed as these factors directly contribute to yield enhancement. The AMMI analysis of variance for grain yield revealed significant genotype, environment and G × E interaction indicating the presence of variability among the genotypes and environments. AMMI model exposed the genotypes G5 and G6, as best performer and environment E1 and E2 as most favourable ones for seed yield. GGE biplots revealed that the most desirable genotypes exhibiting high levels of stability along with high yield potential were G6 and G4, both of which are adaptable to a variety of environments. This study also identified the genotypes that adapted well and uniquely to each environment. With its high representativeness and discriminative capacity, environment E1 (Sardarkrushinagar) was determined to be the optimum test environment for choosing genotypes that are typically acclimated. According to our findings, genotypes that are stable and high performing across conditions may be advocated for commercial cultivation or use in crop breeding programmes for enhanced performance.</div></div>","PeriodicalId":37938,"journal":{"name":"Ecological Genetics and Genomics","volume":"35 ","pages":"Article 100342"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hydrocarbon contamination is a significant environmental concern, impacting soil health and microbial communities. Understanding the microbial diversity in such environments is crucial for developing bioremediation strategies. This study compares the microbial composition of two distinct soil types: a chronically crude oil sludge-contaminated soil and an agricultural field soil. The study uses metagenomic analysis to explore differences in dominant phyla, metabolic pathways, enzyme classes, and specific hydrocarbon-degrading enzymes. The agricultural field soil had relatively higher alpha diversity indices than the oil-contaminated soil, highlighting the impact of crude oil contamination on microbial diversity. The most abundant phyla in the crude oil-contaminated soil included Proteobacteria, Actinobacteria, Chloroflexi, Acidobacteria, Bacteroidetes, and Firmicutes. Species such as Immundisolibacter cernigliae and Bradyrhizobium sp. STM 3843, and hydrocarbon-degrading genera like Rhodococcus, Sphingomonas, Geobacillus, and Pseudomonas were prominent. The analysis identified 21 distinct bacterial strains with demonstrated potential for degrading petroleum hydrocarbons. This study provides valuable insights into the microbial ecology of hydrocarbon-polluted sites and highlights microbial taxa that could be harnessed for effective bioremediation. The findings highlight the importance of further exploring these predominant strains to address hydrocarbon contamination.
{"title":"Unravelling microbial dynamics in hydrocarbon contaminated sites: a comparative metagenomic perspective","authors":"Mukesh Aakula , Mayur Mahindra Kedare , Satyam , Sanjukta Patra , Siddhartha Singha","doi":"10.1016/j.egg.2025.100363","DOIUrl":"10.1016/j.egg.2025.100363","url":null,"abstract":"<div><div>Hydrocarbon contamination is a significant environmental concern, impacting soil health and microbial communities. Understanding the microbial diversity in such environments is crucial for developing bioremediation strategies. This study compares the microbial composition of two distinct soil types: a chronically crude oil sludge-contaminated soil and an agricultural field soil. The study uses metagenomic analysis to explore differences in dominant phyla, metabolic pathways, enzyme classes, and specific hydrocarbon-degrading enzymes. The agricultural field soil had relatively higher alpha diversity indices than the oil-contaminated soil, highlighting the impact of crude oil contamination on microbial diversity. The most abundant phyla in the crude oil-contaminated soil included <em>Proteobacteria</em>, <em>Actinobacteria</em>, <em>Chloroflexi</em>, <em>Acidobacteria</em>, <em>Bacteroidetes</em>, and <em>Firmicutes</em>. Species such as <em>Immundisolibacter cernigliae</em> and <em>Bradyrhizobium</em> sp. <em>STM 3843,</em> and hydrocarbon-degrading genera like <em>Rhodococcus, Sphingomonas, Geobacillus,</em> and <em>Pseudomonas</em> were prominent<em>.</em> The analysis identified 21 distinct bacterial strains with demonstrated potential for degrading petroleum hydrocarbons. This study provides valuable insights into the microbial ecology of hydrocarbon-polluted sites and highlights microbial taxa that could be harnessed for effective bioremediation. The findings highlight the importance of further exploring these predominant strains to address hydrocarbon contamination.</div></div>","PeriodicalId":37938,"journal":{"name":"Ecological Genetics and Genomics","volume":"35 ","pages":"Article 100363"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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