School of Plant and Environmental Sciences
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SPES was formed in 2017 from three departments: Crop and Soil Environmental Sciences; Horticulture; and Plant Pathology, Physiology, and Weed Science.
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Browsing School of Plant and Environmental Sciences by Subject "06 Biological Sciences"
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- Counterions, smectite, and palygorskite increase microstructural stability of saline-sodic soilsJavaheri, F.; Esfandiarpour-Boroujeni, Isa; Farpoor, Mohammad Hady; Holthusen, D.; Stewart, Ryan D. (Elsevier, 2022-02-01)Saline-sodic soils are susceptible to wind and water erosion when the dispersive effect of sodium overcomes inter-particle bonds. Rheological parameters of viscoelasticity can help to quantify inter-particle attractive forces and account for the effect of salinity in these soils. The main objective of the present study was to investigate the viscoelasticity behavior of saline-sodic soils of the Sirjan playa in south-central Iran. Three representative pedons were excavated and described by horizon. Soil physicochemical properties and rheological properties were determined, namely the micromechanical parameters flow point (γf), loss factor tan δ, and integral z, with samples analyzed at three matric potentials (0, −6, and −15 kPa). Results showed that soil microstructural stiffness was mainly influenced by soil texture, clay minerals, gypsum, calcium carbonate equivalent (CCE), and matric potential. The dispersive effect of sodium, as indicated by low integral z and γf values, decreased with increasing gypsum content in − 6 and − 15 kPa matric potentials (0.6 < r < 0.8) and CCE percentage in the quasi-saturated (0 kPa) condition (r > 0.8). However, greater microstructural stability (i.e., higher integral z and γf) was observed for fine-textured soils with relatively high amounts of smectite and palygorskite and low pH. Furthermore, integral z and γf increased with lower matric potentials due to the stabilizing effect of menisci forces. Therefore, the viscoelastic behavior of the saline-sodic soils was negatively associated with water content and high sodium concentration, while the presence of smectite, palygorskite, gypsum, and CCE improved the soil physical conditions and thus the rigidity of the porous system. These results demonstrate that rheological measurements can identify saline-sodic soils that have strongly degraded microstructural stability and would most benefit from active management and amelioration.
- Genomic features of bacterial adaptation to plantsLevy, Asaf; Gonzalez, Isai Salas; Mittelviefhaus, Maximilian; Clingenpeel, Scott; Paredes, Sur Herrera; Miao, Jiamin; Wang, Kunru; Devescovi, Giulia; Stillman, Kyra; Monteiro, Freddy; Alvarez, Bryan Rangel; Lundberg, Alvarez Derek S.; Lu, Tse-Yuan; Lebeis, Sarah; Jin, Zhao; McDonald, Meredith; Klein, Andrew P.; Feltcher, Meghan E.; Rio, Tijana Glavina; Grant, Sarah R.; Doty, Sharon L.; Ley, Ruth E.; Zhao, Bingyu Y.; Venturi, Vittorio; Pelletier, Dale A.; Vorholt, Julia A.; Tringe, Susannah G.; Woyke, Tanja; Dangl, Jeffery L. (Nature Publishing Group, 2018-01-01)Plants intimately associate with diverse bacteria. Plant-associated bacteria have ostensibly evolved genes that enable them to adapt to plant environments. However, the identities of such genes are mostly unknown, and their functions are poorly characterized. We sequenced 484 genomes of bacterial isolates from roots of Brassicaceae, poplar, and maize. We then compared 3,837 bacterial genomes to identify thousands of plant-associated gene clusters. Genomes of plant-associated bacteria encode more carbohydrate metabolism functions and fewer mobile elements than related non-plant-associated genomes do. We experimentally validated candidates from two sets of plant-associated genes: one involved in plant colonization, and the other serving in microbe-microbe competition between plant-associated bacteria. We also identified 64 plant-associated protein domains that potentially mimic plant domains; some are shared with plant-associated fungi and oomycetes. This work expands the genome-based understanding of plant-microbe interactions and provides potential leads for efficient and sustainable agriculture through microbiome engineering.
- Herbicide injury induces DNA methylome alterations in ArabidopsisKim, Gunjune; Clarke, Christopher R.; Larose, Hailey; Tran, Hong T.; Haak, David C.; Zhang, Liqing; Askew, Shawn D.; Barney, Jacob; Westwood, James H. (2017-07)The emergence of herbicide-resistant weeds is a major threat facing modern agriculture. Over 470 weedy-plant populations have developed resistance to herbicides. Traditional evolutionary mechanisms are not always sufficient to explain the rapidity with which certain weed populations adapt in response to herbicide exposure. Stress-induced epigenetic changes, such as alterations in DNA methylation, are potential additional adaptive mechanisms for herbicide resistance. We performed methylC sequencing of Arabidopsis thaliana leaves that developed after either mock treatment or two different sub-lethal doses of the herbicide glyphosate, the most-used herbicide in the history of agriculture. The herbicide injury resulted in 9,205 differentially methylated regions (DMRs) across the genome. In total, 5,914 of these DMRs were induced in a dose-dependent manner, wherein the methylation levels were positively correlated to the severity of the herbicide injury, suggesting that plants can modulate the magnitude of methylation changes based on the severity of the stress. Of the 3,680 genes associated with glyphosateinduced DMRs, only 7% were also implicated in methylation changes following biotic or salinity stress. These results demonstrate that plants respond to herbicide stress through changes in methylation patterns that are, in general, dose-sensitive and, at least partially, stress-specific.
- Measuring shrinkage of undisturbed soil pedsShockey, Matthew C.; Stewart, Ryan D.; Keim, Richard F. (Wiley, 2021-10-19)Methods to measure shrinkage curves typically either disturb natural aggregate structure or include difficult or slow volume measurement techniques. Additionally, most shrinkage curves are obtained by serial measurement of a few samples. We obtained shrinkage curves by collecting rapid, one-off measurements of volume and moisture content for each of 200 undisturbed peds extracted from a field soil, taking measurements as peds slowly dried in the laboratory. The large sample size increased robustness of the shrinkage curve parameter estimates to noise generated by this rapid measurement technique, but a much smaller sample would have resulted in similar parameter estimates.
- Prediction of condition-specific regulatory genes using machine learningSong, Qi; Lee, Jiyoung; Akter, Shamima; Rogers, Matthew; Grene, Ruth; Li, Song (Oxford University Press, 2020-06-19)Recent advances in genomic technologies have generated data on large-scale protein–DNA interactions and open chromatin regions for many eukaryotic species. How to identify condition-specific functions of transcription factors using these data has become a major challenge in genomic research. To solve this problem, we have developed a method called ConSReg, which provides a novel approach to integrate regulatory genomic data into predictive machine learning models of key regulatory genes. Using Arabidopsis as a model system, we tested our approach to identify regulatory genes in data sets from single cell gene expression and from abiotic stress treatments. Our results showed that ConSReg accurately predicted transcription factors that regulate differentially expressed genes with an average auROC of 0.84, which is 23.5–25% better than enrichment-based approaches. To further validate the performance of ConSReg, we analyzed an independent data set related to plant nitrogen responses. ConSReg provided better rankings of the correct transcription factors in 61.7% of cases, which is three times better than other plant tools. We applied ConSReg to Arabidopsis single cell RNA-seq data, successfully identifying candidate regulatory genes that control cell wall formation. Our methods provide a new approach to define candidate regulatory genes using integrated genomic data in plants.
- Rheological evaluation of soil aggregate microstructure and stability across a forested catenaJavaheri, Fatemeh; Esfandiarpour-Boroujeni, Isa; Kourki, Hajir; Farpoor, Mohammad Hady; Stewart, Ryan D. (Elsevier, 2021-12-01)Rheological characteristics of soils, including their deformation and flow behaviors when subjected to external stress, can provide important information on microstructural stability. In this study we used rheological measurements to examine the soil aggregate microstructure and stability of four different soil orders – Alfisol, Mollisol, Inceptisol, and Entisol – along a forested catena in Mazandaran Province, northern Iran. Amplitude sweep tests were used to quantify the initial values of the storage and loss moduli, deformation limit (when the material begins to transition from reversible to irreversible deformation), deformation at flow point (when the material becomes viscous), and integral z (which summarizes the overall visco-elasticity of the material). The deformation limit was significantly higher in subsoil layers than topsoil layers, and was also higher in the Mollisol than the other pedons. The flow point and integral z values, which relate to the structural stiffness of soil matrices, were largest in the Btg horizons of the Alfisol and Mollisol, implying that these soils had more rigid microstructures. In contrast, the Entisol Ckg horizon, which had high sand content and little soil development, had the lowest values for all properties, thus indicating a lack of micro-aggregate stability. Regression analyses revealed that integral z was influenced by soil physicochemical properties, and was higher in soils whose clay fraction was dominated by expansive clay minerals and pedogenic iron and aluminum sesquioxides. Altogether, the rheological parameters indicated that older, more developed soils had greater microstructural stability than their less developed counterparts. As a result, rheological measurements may be useful for identifying the major factors that affect soil aggregation, and can indicate the relative amount of soil development along gradients such as the studied forest catena.
- A selective sweep in the Spike gene has driven SARS-CoV-2 human adaptationKang, Lin; He, Guijuan; Sharp, Amanda K.; Wang, Xiaofeng; Brown, Anne M.; Michalak, Pawel; Weger-Lucarelli, James (Cell Press, 2021-08-19)The coronavirus disease 2019 (COVID-19) pandemic underscores the need to better understand animal-to-human transmission of coronaviruses and adaptive evolution within new hosts. We scanned more than 182,000 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes for selective sweep signatures and found a distinct footprint of positive selection located around a non-synonymous change (A1114G; T372A) within the spike protein receptor-binding domain (RBD), predicted to remove glycosylation and increase binding to human ACE2 (hACE2), the cellular receptor. This change is present in all human SARS-CoV-2 sequences but not in closely related viruses from bats and pangolins. As predicted, T372A RBD bound hACE2 with higher affinity in experimental binding assays. We engineered the reversion mutant (A372T) and found that A372 (wild-type [WT]-SARS-CoV-2) enhanced replication in human lung cells relative to its putative ancestral variant (T372), an effect that was 20 times greater than the well-known D614G mutation. Our findings suggest that this mutation likely contributed to SARS-CoV-2 emergence from animal reservoirs or enabled sustained human-to-human transmission.