Climate change poses an increasing threat to agricultural productivity in the Texas High Plains (THP), a semi-arid region facing both warming trends and declining groundwater resources. This study integrates process-based crop modeling with geospatial analysis to identify spatial zones of climate vulnerability and adaptive potential for four major crops; winter wheat, cotton, maize, and grain sorghum under future climate scenarios. Using the Decision Support System for Agrotechnology Transfer (DSSAT) model, historical (1991–2020) and future yields (2031–2060 and 2070–2099) were simulated across 48 counties under Representative Concentration Pathway 4.5 and 8.5 (RCP 4.5 and RCP 8.5). Spatial clustering techniques, including Global Moran’s I and Getis-Ord Gi* statistics, were applied to classify counties into vulnerable, adaptive, stable, and more stable zones based on projected yield changes. Results revealed that wheat vulnerability was concentrated in southern counties, with projected yield decreases of 10–30% under RCP 8.5 relative to the 1991–2020 baseline. In contrast, northern counties showed yield increases of 30–50% under RCP 4.5 by mid-century and under RCP 8.5 by end-century. Cotton yields are projected to increase by 20–40% across most counties under both RCP 4.5 end-century and RCP 8.5 mid- and end-century relative to the historical baseline, although localized vulnerability may emerge in southwestern THP under RCP 8.5 by end-century. For grain sorghum yields are projected to increase by 10–20% in eastern and northern counties under RCP 4.5, but under RCP 8.5 widespread yield declines exceeding 40% are expected by end-century. These reductions are largely attributed to reduced rainfall and increased temperature stress during the growing season. In this study, sorghum was planted in June, which may have exposed the crop to greater late-season heat stress; earlier planting dates could potentially mitigate some of these adverse effects. Maize, which was planted in April in this study, showed spatially variable yield changes, with several southern counties exhibiting positive trends. These localized yield increases are primarily associated with projected precipitation increases during the maize growing season compared to the historical baseline, rather than an inherent crop-specific resilience to climate change. These spatially explicit findings underscore the need for targeted adaptation strategies, including the deployment of climate-resilient crop varieties, optimized irrigation management, crop diversification, and adaptive land use planning. The study offers actionable insights to support climate-resilient agricultural planning and inform precision adaptation policies for sustaining crop productivity in the THP under future climate scenarios.

Quantifying the natural inter-individual variation in DNA methylation patterns is important for identifying its contribution to phenotypic variation, but also for understanding how the environment affects variability, and for incorporation into statistical analyses. The inter-individual variation in DNA methylation patterns in female cattle and the effect that a prenatal stressor has on such variability have yet to be quantified. Thus, the objective of this study was to utilize methylation data from mature Brahman females to quantify the inter-individual variation in DNA methylation. Pregnant Brahman cows were transported for 2 h durations at days 60 ± 5; 80 ± 5; 100 ± 5; 120 ± 5; and 140 ± 5 of gestation. A non-transport group was maintained as a control. Leukocytes, amygdala, and anterior pituitary glands were harvested from eight cows born from the non-transport group (Control) and six from the transport group (PNS) at 5 years of age. The DNA harvested from the anterior pituitary contained the greatest variability in DNA methylation of cytosine-phosphate-guanine (mCpG) sites from both the PNS and Control groups, and the amygdala had the least. Numerous variable mCpG sites were associated with retrotransposable elements and highly repetitive regions of the genome. Some of the genomic features that had high variation in DNA methylation are involved in immune responses, signaling, responses to stimuli, and metabolic processes. The small overlap of highly variable CpG sites and features between tissues and leukocytes supports the role of variable DNA methylation in regulating tissue-specific gene expression. Many of the CpG sites that exhibited high variability in DNA methylation were common between the PNS and Control groups within a tissue, but there was little overlap in genomic features with high variability. The interaction between the prenatal environment and the genome could be responsible for the differences in location of the variable DNA methylation.

Knowledge of circadian rhythm clock gene expression outside the suprachiasmatic nucleus is increasing. The purpose of this study was to determine whether expression of circadian clock genes differed within or among the bovine stress axis tissues (e.g., amygdala, hypothalamus, pituitary, adrenal cortex, and adrenal medulla). Tissues were obtained at an abattoir from eight mature nonpregnant Brahman cows that had been maintained in the same pasture and nutritional conditions. Sample tissues were stored in RNase-free sterile cryovials at −80 °C until the total RNA was extracted, quantified, assessed, and sequenced (NovaSeq 6000 system; paired-end 150 bp cycles). The trimmed reads were then mapped to a Bos taurus (B. taurus) reference genome (Umd3.1). Further analysis used the edgeR package. Raw gene count tables were read into RStudio, and low-expression genes were filtered out using the criteria of three minimum reads per gene in at least five samples. Normalization factors were then calculated using the trimmed mean of M values method to produce normalized gene counts within each sample tissue. The normalized gene counts important for a circadian rhythm were analyzed within and between each tissue of the stress axis using the GLM and CORR procedures of the Statistical Analysis System (SAS). The relative expression profiles of circadian clock genes differed (p < 0.01) within each tissue, with neuronal PAS domain protein 2 (NPAS2) having greater expression in the amygdala (p < 0.01) and period circadian regulator (PER1) having greater expression in all other tissues (p < 0.01). The expression among tissues also differed (p < 0.01) for individual circadian clock genes, with circadian locomotor output cycles protein kaput (CLOCK) expression being greater within the adrenal tissues and nuclear receptor subfamily 1 group D member 1 (NR1D1) expression being greater within the other tissues (p < 0.01). Overall, the results indicate that within each tissue, the various circadian clock genes were differentially expressed, in addition to being differentially expressed among the stress tissues of mature Brahman cows. Future use of these findings may assist in improving livestock husbandry and welfare by understanding interactions of the environment, stress responsiveness, and peripheral circadian rhythms.

Physiological and psychological stressors have been associated with the attrition of telomeres, which are the protective caps of chromosomes. This study compares the telomere length (TL) in 4-year-old Brahman cows grouped by the first parity (n = 8) and the second parity (n = 11). The cows were bled via jugular venipuncture, weighed, and had their body condition scores recorded at Day −28 prior to calving and at Day + 7 and Day + 28 post-calving. The duration of labor (Dlabor) and parturition ease were recorded. The peripheral leukocytes were isolated, the leukocyte blood count with differential was recorded, and the genomic DNA was extracted. The relative quantity of telomere products, which is proportional to the average TL, was determined via multiplex quantitative PCR using the ratio (T/S ratio) of bovine telomere and β-globulin DNA. Standards of the bovine telomere (10¹²–10⁷ dilution series) and β-globulin (10⁹–10⁴ dilution series) genes were utilized to produce relative copy numbers. The samples were assayed in triplicate and were included if the triplicate C_q difference was less than 0.25 cycles. The parity was the fixed effect, and the random effects included the sire and day repeated with the cow as the subject. Statistical significance was not observed in the leukocyte number or type (p > 0.1). A reduction in the TL of approximately 9225 telomeric copies was found between Parity 1 and Parity 2 (p = 0.02). A trend was found between the TL and Dlabor (p = 0.06). The stress of parturition and raising the first calf of a cow’s life may be responsible for TL attenuation. Parity may be considered a stressor of cow longevity.

Background/Objectives: The experience of prenatal stress results in various physiological disorders due to an alteration of an offspring’s methylome and transcriptome. The objective of this study was to determine whether PNS affects DNA methylation (DNAm) and gene expression in the stress axis tissues of mature Brahman cows. Methods: Samples were collected from the paraventricular nucleus (PVN), anterior pituitary (PIT), and adrenal cortex (AC) of 5-year-old Brahman cows that were prenatally exposed to either transportation stress (PNS, n = 6) or were not transported (Control, n = 8). The isolated DNA and RNA samples were, respectively, used for methylation and RNA-Seq analyses. A gene ontology and KEGG pathway enrichment analysis of each data set within each sample tissue was conducted with the DAVID Functional Annotation Tool. Results: The DNAm analysis revealed 3, 64, and 99 hypomethylated and 2, 93, and 90 hypermethylated CpG sites (FDR < 0.15) within the PVN, PIT, and AC, respectively. The RNA-Seq analysis revealed 6, 25, and 5 differentially expressed genes (FDR < 0.15) in the PVN, PIT, and AC, respectively, that were up-regulated in the PNS group relative to the Control group, as well as 24 genes in the PIT that were down-regulated. Based on the enrichment analysis, several developmental and cellular processes, such as maintenance of the actin cytoskeleton, cell motility, signal transduction, neurodevelopment, and synaptic function, were potentially modulated. Conclusions: The methylome and transcriptome were altered in the stress axis tissues of mature cows that had been exposed to prenatal transportation stress. These findings are relevant to understanding how prenatal experiences may affect postnatal neurological functions.

Spatially explicit crop-yield information is needed for regional environmental modeling, sustainability assessment, and agricultural decision support, yet official yield statistics are commonly reported only at aggregated administrative scales. This study introduces the nayd R package, a reproducible geospatial workflow for converting county-level harvested area and yield statistics into spatially explicit production units and zonal clusters while preserving consistency with official records. County-level statistics from the USDA National Agri-cultural Statistics Service were integrated with USDA Cropland Data Layer crop masks, multi-sensor NDVI products, and satellite-derived evapotranspiration from OpenET SSEBop. An NDVI-based eligibility filter refined crop masks toward reported harvested area, while normalized NDVI and evapotranspiration layers were combined into spatial weighting surfaces and aggregated into contiguous production units and graph-based clusters. Case studies for cotton and winter wheat in Texas showed that the eligibility filter removed approximately 20–40% of CDL-classified pixels while maintaining consistency with reported harvested area and preserving plausible spatial gradients associated with ir-rigated and dryland systems. Evaluation against independent Texas A&M AgriLife vari-ety-trial data yielded normalized RMSE values of approximately 11–15% for cotton and 9–12% for winter wheat. The workflow provides an open-source framework for generating statistically consistent production zones for regional crop modeling, environmental as-sessment, and sustainable agricultural planning.