The MADS-box transcription factor (TF) superfamily, one of the largest gene groups in plants, is essential for regulating stress responses. However, its function in rice under pesticide stress remains unknown. To address this gap, we investigated the traits and roles of the rice MADS-box gene family under pesticide exposure. Transcriptome analysis of rice (Oryza sativa) treated with fluroxypyr-meptyl (FLUME) and oxyfluorfen (OFF) revealed 30 OsMADS-box genes and 3 MADS-box differentially expressed genes (DEGs). Phylogenetic analysis classified these genes into 12 subfamilies: Mα, Mβ, Mγ, SOC1, E, A, AGL12, SVP, ANR1, Bs, B, and MIKC*. Chromosomal mapping revealed uneven distribution of OsMADS-box genes across all 12 chromosomes, with segmental duplication contributing to gene family expansion. Collinearity analysis identified 14 orthologous gene pairs within rice and additional orthologous gene pairs shared with other plant species: 4 with Arabidopsis (Arabidopsis thaliana), 17 with soybean (Glycine max), 45 with maize (Zea mays), and 36 with wild sugarcane (Saccharum spontaneum). Structural analysis showed that OsMADS-box genes possess diverse gene architectures, cis-acting elements, motif compositions, and conserved domains, enabling responses to biotic and abiotic stress. Docking studies of OFF, FLUME, and the three MADS-box DEGs identified key amino acid residues implicated in pesticide binding. qRT-PCR confirmed preferential expression of several MADS-box DEGs under OFF- and FLUME-induced stress. Protein-protein interaction network analysis further supported the involvement of OsMADS-box proteins in FLUME and OFF metabolism. These findings provide insights into the OsMADS-box superfamily and offer valuable resources for functional studies on their roles in pesticide metabolism.

The c-kit-ligand (KITLG) is a pigmentation gene that has a strong selection signal in the majority of domestic animals. Recent studies in human and rodent populations have indicated a role for KITLG in the response to social stress. Regression analysis revealed three significant predictors of KITLG minor allele frequency (MAF) in domestic goat populations: urbanization level (β = +0.0037, p < 0.001), latitude (β = +0.0019, p = 0.010), and solar radiation (β = -0.00029, p < 0.001). Together, these factors explained 53.6% of the variation in the KITLG gene MAF (adjusted R² = 0.527). The results obtained indicate a complex influence of anthropogenic and natural factors on the genetic structure of domestic goat populations. We used local urbanization level as an indirect indicator of human-animal relationship, suggesting that the KITLG pleiotropy links human-recognizable pigmentation patterns to certain behavioural phenotypes. This association can be considered as a possible mechanism for facilitating and maintaining domestication.

Population genetics plays a critical role in creating policies for managing fisheries, conservation, and development of aquaculture. The golden snapper, Lutjanus johnii (Bloch, 1792), is a highly commercial and aquaculture important snapper species. This study used mitochondrial markers D-loop (151 specimens) and Cytochrome b (Cyt-b, 120 specimens) from 10 populations, including populations from the east South China Sea, the west South China Sea and the Strait of Malacca to investigate the genetic diversity, population connectivity, and historical demography of L. johnii. High levels of haplotype diversity (D-loop: 0.974-1.000; Cyt-b: 0.711-0.952) were observed along with low nucleotide diversity (D-loop: 0.009-0.052; Cyt-b: 0.001-0.007), which suggests a population bottleneck was followed by an abrupt rise in population size. Genetic structuring was identified between populations in the South China Sea and its adjacent waters, compared to those in the Kuala Kedah population. Genetic structuring was consistently inferred from Bayesian inference trees, median joining networks (MJN), population pairwise ФST comparisons, FST indices of genetic differentiation and a hierarchical AMOVA (Analysis of Molecular Variance). Demographic neutrality statistics and DNA mismatch distributions revealed species went through a sudden demographic expansion. Throughout the Pleistocene. Result from this study suggest that fisheries management for this species should take into consideration the genetic and demographic independence of the Kuala Kedah population. Policymaking should adhere to the precautionary principle to safeguard potential adaptive genetic diversity and ensure the sustainability of regional and local fisheries.

Understanding the genetic structure of wild ungulate populations is essential for informed conservation planning, particularly in ecologically sensitive and topographically complex landscapes such as the Himalayas. We investigated the genetic variation in Bharal (Pseudois nayaur) populations from the western (WH) and eastern Himalayas (EH) using eight microsatellite loci. Our analysis revealed significant genetic divergence between WH and EH populations, with a Nei's genetic distance of 0.91 and a pairwise FST value of 0.14, indicating their delineation as distinct lineages. WH populations showed greater genetic affinity with the Himalayan Bharal (P. n. nayaur). In contrast, EH populations were closely related to the Chinese Bharal (P. n. szechuanensis) of the Tibetan Plateau. Hence, WH and EH Bharal represent distinct Evolutionarily Significant Units (ESUs) and should be managed as separate Management Units (MUs). It further highlighted the need for region-specific conservation strategies to safeguard the genetic integrity and ecological resilience of Bharal populations across the Indian Himalayan Region.

Bacteria are constantly exposed to diverse environmental stresses, necessitating complex adaptive mechanisms for survival. Thermus thermophilus, a thermophilic extremophile, serves as an excellent model for investigating these responses due to its remarkable resilience to harsh conditions. Recent advances in artificial intelligence, particularly in machine learning, have transformed the identification of novel stress-responsive biomarkers. In this study, we analyzed transcriptomic data from 65 T. thermophilus HB8 samples subjected to various abiotic stresses to identify key genes involved in stress adaptation. We applied a suite of supervised machine learning algorithms to classify samples and prioritize informative features. Among the tested models, Extreme Gradient Boosting (XGBoost) and Random Forest (RF) achieved the highest classification performance, with XGBoost attaining perfect discrimination between stressed and control samples (AUC = 1.00) and RF closely following (AUC = 0.99). Feature importance analysis consistently identified three candidate genes: TTHA0029, TTHA1720, and TTHA1359. Functional validation using RT-qPCR confirmed the significant upregulation of TTHA0029 and TTHA1720 under salt and hydrogen peroxide stress, suggesting roles in redox regulation and ionic homeostasis. Phylogenetic analysis further revealed the specificity of these genes to the Thermus genus. Overall, our findings highlight central molecular players in stress tolerance in T. thermophilus and demonstrate the utility of machine learning in biomarker discovery. The identified genes, TTHA0029 and TTHA1720, may serve as promising targets for genetic engineering to improve stress resilience in both crops and industrially relevant microorganisms.

Thaumatin-Like Proteins (TLPs) play a crucial role against biotic and abiotic stresses, acting as signaling molecules in transduction pathways and exhibiting antimicrobial activity. The present study aimed to characterize TLPs of Cenostigma pyramidale (Fabaceae) and analyze their expression (RNA-Seq) in root tissues under salt stress. A total of 36 CpTLPs were identified, which showed the characteristic TLP domain and a signal peptide in the N-terminal region. Multiple sequence alignment revealed the conservation of 16 cysteine residues, a signature motif, and a "REDDD" motif, all characteristic of TLPs. Three typical TLPs domains were identified in the three-dimensional modeling of the six analyzed sequences. The molecular dynamics simulation revealed stability along most of these sequences. RNA-seq under salt stress showed that six C. pyramidale TLPs (CpTLP2, CpTLP3, CpTLP5, CpTLP17, CpTLP20, and CpTLP31) were differentially expressed. The RT-qPCR expression validation was performed in leaf and root tissues (30min, 2h, and 11 days after salt stress). In leaf tissue, most CpTLPs were induced in at least one time point analyzed. In root tissue, we observed validation of the RNA-Seq expression data of CpTLP3, CpTLP5, CpTLP20, and CpTLP31, as well as distinct expression patterns between leaf and root tissues. Our results showed significant variations in the transcriptional response of the TLP family across different plant tissues and associated specific genes of this family with salt tolerance in C. pyramidale. These findings enhance the understanding of the role of TLPs in salt stress and may be useful in genetic improvement strategies to increase salt tolerance.

Universal Stress Proteins (USPs) are widely distributed across various organisms and play a crucial role in survival under stress conditions. As environmental stresses become more severe, understanding the role of USPs in developing stress-resistant plants has gained increasing importance. In this study, we identified 231 USP-coding genes in the genomes of Brassica napus (BnUSP1-BnUSP115), B. rapa (BrUSP1-BrUSP54), and B. oleracea (BoUSP1-BoUSP62) using bioinformatics approaches. Phylogenetic analysis grouped these genes into six distinct clusters based on bootstrap values. Structural analysis of USP genes in these Brassica species revealed variability in intron numbers, with phase 0 introns being more prevalent than phases 1 and 2. Gene duplication analysis showed that segmental/WGD duplication events significantly contributed to the expansion of the USP gene family, with duplicated genes undergoing purifying selection. Promoter analysis identified several cis-regulatory elements related to stress and hormone responses-such as MYB, MYC, ARE, ERF, ABRE, TGA-element, and TCA-element-in the upstream regions of BnUSP, BoUSP, and BrUSP genes, suggesting their involvement in complex stress response pathways. Finally, RNA-seq data were used to examine the expression patterns of BnUSP genes across different tissues (root, stem, seed, flower, pod, and leaf) and under various abiotic stresses (cold, salinity, dehydration, and ABA). Their responses to salt stress were further validated using qRT-PCR. These analyses identified BnUSP60 and BnUSP2 as potential targets for breeding programs aimed at enhancing stress resistance in B. napus.

An association between genetic variation in Agouti Related Peptide (AGRP) gene and adaptability was investigated in Ganjam, Narayanpatana, Maraguda and Keonjhar goat populations of Odisha. The comparative quantitative expression of AGRP gene revealed higher expression in Maraguda and Keonjhar goats as compared to Ganjam and Narayanpatana goats. The bioinformatics analysis revealed the intricate mechanism of action for AGRP protein in the cellular pathway for thermal stress. The three-dimensional structure of AGRP protein was predicted and its stability was ascertained by constructing Ramchandran plot, aromatic receptor surface, hydrogen bond interaction and hydrophobicity plot. Momentous intracellular interaction of AGRP protein with leptin and ghrelin receptors was established through in silico analysis. The relationship between genetic variation with physiological, biochemical and haematological parameters was estimated by calculating the adaptability index (AI) through multivariate analysis. The relative importance of each variable in the adaptive responses of the four goat populations was assessed by path analysis. The difference in AI between the goat populations was slightly over 8%. This preliminary AI provides a potential decision-maker method to scale the resilience level of goats. The path analysis avowed that THI significantly modified the skin temperature and respiration rate which in turn will decrease the rectal temperature showing better adaptability. A comprehensive genetic and phenotypic analysis for thermal resilience in goats was established in this study.

C2H2-type zinc finger proteins (ZFPs) are crucial transcription factors in eukaryotes, playing significant roles in various biological processe. The Q-type ZFP, a plant-specific subfamily, are particularly important in responding to abiotic stresses. Wheat is a crucial staple crop in world, with drought significantly affecting its yield and quality. Developing drought-resistant varieties is one of the most cost-effective strategies to mitigate drought stress in wheat. Here, we identified 772 non-redundant members of the Q-type ZFP genes family in Triticeae. Among them, 267 genes were found in common wheat, 56 in wild emmer wheat, 157 in spelt wheat, 154 in durum wheat, 56 in Triticum urart, and 82 in Aegilops tauschii. The phylogenetic tree shows that the Q-type ZFP genes family can be divided into five groups. The Q-type ZFPs family are mainly regulated by MYB, MYC, and WRKY transcription factors. Moreover, there are a large number of drought stress and ABA-related cis-acting elements in the promoter region. We studied their gene structures and found that most genes have a single exon. In this study, we identified 76 tandemly duplicated gene pairs across the six species. A total of 3,445 collinear gene pairs were found, with 1,877 pairs in wheat. Furthermore, most collinear gene pairs have Ka/Ks values less than 1. Comparative analysis of multiple physiological indices, including relative coleoptile length and CAT activity, revealed that common wheat cultivars JM6425 and JM4293 exhibited stronger drought tolerance compared to JM4258 and JM5787. TaZFP3D-12 and TaZFP5D-22 exhibited similar expression patterns in drought-tolerant varieties, contrasting with those in drought-sensitive ones.