Scholarworks

ScholarWorks is an open access repository for the capture of the intellectual work of Montana State University (MSU) in support of its teaching, research and service missions. MSU ScholarWorks is a central point of discovery for accessing, collecting, sharing, preserving, and distributing knowledge to the Montana State University community and the world.

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Scholarship & Research

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A roadmap for equitable reuse of public microbiome data
(Springer Science and Business Media LLC, 2025-09) Hug, Laura A.; Hatzenpichler, Roland; Moraru, Cristina; Soares, André R.; Meyer, Folker; Heyder, Anke; The Data Reuse Consortium; Probst, Alexander J.
Science benefits from rapid open data sharing, but current guidelines for data reuse were established two decades ago, when databases were several million times smaller than they are today. These guidelines are largely unfamiliar to the scientific community, and, owing to the rapid increase in biological data generated in the past decade, they are also outdated. As a result, there is a lack of community standards suited to the current landscape and inconsistent implementation of data sharing policies across institutions. Here we discuss current sequence data sharing policies and their benefits and drawbacks, and present a roadmap to establish guidelines for equitable sequence data reuse, developed in consultation with a data consortium of 167 microbiome scientists. We propose the use of a Data Reuse Information (DRI) tag for public sequence data, which will be associated with at least one Open Researcher and Contributor ID (ORCID) account. The machine-readable DRI tag indicates that the data creators prefer to be contacted before data reuse, and simultaneously provides data consumers with a mechanism to get in touch with the data creators. The DRI aims to facilitate and foster collaborations, and serve as a guideline that can be expanded to other data types.
Improving genomic prediction for plant disease using environmental covariates
(Springer Science and Business Media LLC, 2025-08) Brault, Charlotte; Conley, Emily; Read, Andrew C.; Glover, Karl D.; Cook, Jason P.; Gill, Harsimardeep S.; Fiedler, Jason D.; Anderson, James A.
Background. Fusarium Head Blight (FHB) is a destructive fungal disease affecting wheat and barley, leading to significant yield losses and reduced grain quality. Susceptibility to FHB is influenced by genetic factors, environmental conditions, and genotype-by-environment interactions (GxE), making it challenging to predict disease resistance across diverse environments. This study investigates GxE in a long-term spring wheat multi-environment uniform nursery trial focusing on the evaluation of resistant lines in northern US breeding programs. Results. Traditionally, GxE has been analyzed as a reaction norm over an environment index. Here, we computed the environment index as a linear combination of environmental covariables specific to each environment, and we derived an environment relationship matrix. Three methods were compared, all aimed at predicting untested genotypes in untested environments: the widely used Finlay-Wilkinson regression (FW), the joint-genomic regression analysis (JGRA) method, and mixed models incorporating an environmental covariates matrix. These were benchmarked against a baseline genomic selection model (GS) without environmental covariates. Predictive abilities were assessed within and across environments. The results revealed that the JGRA marker effect method was more accurate than GS in within- and across-environment predictions, although the differences were small. The predictive ability slightly decreased when the target environment was less related to the training environments. Mixed models performed similarly to JGRA within-environment, but JGRA outperformed the other methods for across-environment predictions. Additionally, JGRA identified significant genetic markers associated with baseline FHB resistance and environmental sensitivity. Furthermore, location-specific genomic estimated breeding values were predicted, providing insights into genotype stability across varying locations. Conclusion. These findings highlight the value of incorporating environmental covariates to increase predictive ability and improve the selection of resistant genotypes for diverse, untested environments. By leveraging this approach, breeders can effectively exploit GxE interactions to improve disease management at no additional cost.
K-8 Pre-Service Teachers’ Technology Integration in Mathematics: Perspectives and Anticipated Practices
(Ax Publications, 2025-06) Mayerink, Monte; Luo, Fenqjen
This qualitative, phenomenological study sought to examine kindergarten through eighth-grade pre-service teachers’ (N = 19) perspectives on technology integration within the context of mathematics. Topics of primary interest were pre-service teachers’ knowledge of technology integration, their questions/concerns regarding technology integration, their anticipated technology integration practices, and the impact of technological resources on mathematics instruction for their proposed uses of technology. Both the SAMR and PICRAT models informed the methodology of this study. Data were collected from responses to open-ended prompts as part of a mathematics methods course and analyzed with both a priori (i.e., SAMR and PICRAT) and emergent coding. Findings showed that responses were most aligned with interactive, amplification level of the PICRAT model and the augmentation level of the SAMR model, in which pre-service teachers often described students’ use of mathematical games. Additionally, this study found that pre-service teachers reported limited knowledge of technology integration, have questions/concerns related to when and how to integrate technology, and anticipate that they will integrate technology into their future classrooms relatively frequently. Implications of the findings for both researchers and teacher educators are discussed, as well as recommendations for future research.
Creating ultra‐high linolenic acid camelina by co‐expressing AtFAD2sm with synonymous mutations and BnFAD3 in the fae1 mutant
(Wiley, 2025-07) Li, Na; Liu, Xiangling; Chen, Yangyang; Zhao, Hailan; Zhao, Yingdong; Du, Chang; Lu, Chaofu; Zhang, Meng
Alpha-linolenic acid (α-linolenic acid, ALA, 18:3) is an ω-3 polyunsaturated fatty acid (PUFA), which along with linoleic acid (LA, 18:2, ω6) is essential for human nutrition that must be obtained through dietary sources due to the absence of Δ12/Δ15 fatty acid desaturases in mammals. Vegetable oils rich in 18:3, such as flaxseed oil, are prone to oxidation, leading to issues like a short shelf-life. The modern oilseed industry addressed this issue by developing high-oleic/low-18:3 vegetable oils to improve their oxidative stability. However, this contributed to the severe imbalance of these essential fatty acids and the very high dietary ω6/ω3 ratio that promotes the pathogenesis of many diseases, including cardiovascular disease, cancer, and inflammatory and autoimmune diseases. Therefore, it is desirable to develop high-18:3 oil crops to improve human health. Camelina (Camelina sativa L. Crantz), a flexible and low-input oilseed crop, contains a high content of 18:3 (31%–40%) in seeds, which represents a potential source (Berti et al., 2016).
Methane emission hotspots in a boreal forest-fen mosaic potentially linked to deep taliks
(IOP Publishing, 2025-08) Farina, Mary; Christian, William; Hasson, Nicholas; McDermott, Timothy R.; Powell, Scott; Hatzenpichler, Roland; Webb, Hailey; LaRue, Gage; Okano, Kyoko; Sproles, Eric A.; Watts, Jennifer D.
Permafrost thaw is transforming boreal forests into mosaics of wetlands and drier uplands. Topographic controls on hydrological and ecological conditions impact methane (CH4) fluxes, contributing to uncertainty in local and regional CH4 budgets and underlying drivers. The objective of this study was to explore CH4 fluxes and their drivers in a transitioning boreal forest-fen ecosystem (Goldstream Valley, Alaska, USA). This landscape is characterized by thawing discontinuous permafrost and heterogeneous mosaics of fens, collapse-scar channels, and small mounds of permafrost soils. From a survey in July 2021, observed chamber CH4 fluxes included fen areas with intermediate to very high emissions (29.8–635.3 mg CH4 m−2 d−1), clustered locations with CH4 uptake (−2.11 to −0.7 mg CH4 m−2 d−1), and three anomalous emission hotspots (342.4–772.4 mg CH4 m−2 d−1) that were located near samples with lower emissions. Some surface and near-surface variables partially explained the spatial variation in CH4 flux. Log-transformed CH4 flux had a positive linear relationship with soil moisture at 20 cm depth (R2 = 0.31, p-value < 1e-5) and negative linear relationships with microtopography (R2 = 0.13, p-value < 0.006) and slope (R2 = 0.28, p-value < 2e-5). Methane emissions generally occurred in flat, wet, graminoid-dominated fens, whereas CH4 uptake occurred on permafrost mounds dominated by feather mosses and woody vegetation. However, the CH4 hotspots occurred on drier, slightly sloped locations with low or undetectable near-surface methanogen abundance, suggesting that CH4 was produced in deeper soils. When the hotspot samples were omitted, log-transformed CH4 flux had a positive linear relationship with near-surface methanogen abundance (R2 = 0.29, p-value = 0.0023), and stronger linear relationships with soil moisture, slope, and soil macronutrient concentrations. Our findings suggest that some CH4 emission hotspots could arise from CH4 in deep taliks. The inference that methanogenesis occurs in deep taliks was strengthened by the identification of intrapermafrost taliks across the study area using low-frequency geophysical induction. This study assesses surface spatial heterogeneity in the context of subsurface permafrost conditions and highlights the complexity of CH4 flux patterns in transitioning forest-wetland ecosystems. To better inform regional CH4 budgets, further research is needed to understand the spatial distribution of terrestrial CH4 hotspots and to resolve their surface, near-surface, and subsurface drivers.