Progress 01/01/24 to 12/31/24
Outputs
Target Audience:Our targeted audience includes researchers and students in plant genetics, plant breeding, and microbiology. Corn growers who are interested in reducing agricultural inputs and are looking for organic solutions to lower nitrogen input in their fields might also find our work relevant. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?In 2024, we trained one postdoctoral researcher, one Ph.D. student, and one M.S. student. The postdoctoral scholar in Dr. Schachtman's lab continues to lead host genetics, microbiome data analysis, and data integration efforts. In Dr. Yang's lab, a new Ph.D. student enrolled in Plant Breeding and Genetics has joined the project. The student is becoming proficient in microbiome data analysis and is currently refining the microbiome-wide association study. Additionally, a master's student in Dr. Schachtman's lab successfully defended her thesis and has graduated. How have the results been disseminated to communities of interest?In 2024, we published two papers from the work supported by the USDA. And one graduate student from Dr. Yang's lab presented the work in a poster during the Maize Genetics Conference at St. Louis in March of 2024. We also present two posters during the Plant Science Retreat in October of 2024 in Nebraska City. In 2024, Dr. Yang disseminated the work to the USDA Ag Microbiome PD meeting in St. Louis and also presented it as an invited speaker during the Baker Plant Breeding Symposium at Iowa State University. What do you plan to do during the next reporting period to accomplish the goals?Goal 1 - We will wrap up the testing and report our discovery to a peer-reviewed journal. Goal 2 - We will refine our microbiome and host trait association analysis. In the meanwhile, we will develop a computational protocol to analyze the root imagery data. Goal 3 - We will further refine the microbiome-wide association study pipeline to connect host traits with ASVs.?
Impacts
What was accomplished under these goals?
Goal 1: Testing NUE-related phenotypic effects of the beneficial microbes. In Goal 1, Dr. Yang provided Dr. Schachtman with ASV sequences from a previous study (Meier et al., 2022). These sequences came from a culture-independent field study that identified ASVs genetically associated with nitrogen use efficiency (NUE) measurements in maize. Dr. Schachtman's lab searched these ASVs against a 16S database of a large culture collection, identifying 60 bacterial isolates related to the ASVs. These isolates were tested multiple times in in an axenic system under low nitrogen conditions. The low nitrogen testing system was calibrated using full-strength Hoagland's solution and a solution with similar ionic content, except for 10% nitrate concentration and 50% ammonium concentration. Maize seeds (Mo17 genotype) were sterilized using a chlorine gas method, imbibed in sterile aerated water for 24 hours, and planted in a sterilized turface placed in sterile germination bags. A sterile membrane was added to the bags to facilitate gas exchange. Seeds were primed with each microbe culture for 12 hours immediate after radical emergence and then planted in sterilized turface and placed in sterile germination bags with a membrane on them that allows for gas exchange. Plants were maintained in the bags for 15 days, after which they were harvested and their root and shoot dry weight and fresh weight were measured. In each experiment, 4-8 replicates of plants were grown with and without microbes under low nitrogen conditions, with a no microbe high nitrogen control included for calibration. From the study, we narrowed down to three promising isolates. In 2024, these three isolates were tested across three maize genotypes under two inoculation regimes: (1) single inoculation and (2) repeated inoculation. The key finding was that repeated inoculation revealed a genotype by isolate interaction effect. We are currently preparing a manuscript to report our discovery. Goal 2: Validating microbiome-associated GWAS signals using an unrelated population. In the 2022 and 2023 field trials, we excavated roots and captured images for each excavated root for phenotyping. We have also harvested mature to measure ear-related traits. In 2024, we have finished phenotyping on ear-related traits, and are currently working on root imagery data analysis. In 2024, we refined our analysis on the 16S amplicon sequencing data. Our results suggested that N treatment significantly increased both rhizosphere microbial network modularity and the ratio of negative to positive interactions compared to untreated soils in inbred lines. This aligns with the Stress Gradient Hypothesis suggesting a shift toward positive interactions between microbial species as environmental stress increases. We have published this discovery in a peer-reviewed journal (Mukhtar et al., 2025). Additionally, from analyzing the phenotypic data, our results revealed that hybrids consistently outperform inbreds for conventional phenotypic traits under both N conditions. Interestingly, microbial traits generally display lower abundance and diversity in hybrids than inbreds under high N conditions. However, under low N conditions, about 10-20% of the microbial traits exhibit heterosis. To uncover the genetic basis of traits (including rhizosphere microbial traits) per se, heterosis, and N-responsive traits, we conducted Genome-wide Association Studies (GWAS) and identified a number of favorable tropical alleles, some of which contributed to the heterosis of conventional or microbial traits and were associated with N-responsive traits. We will continue to finish the phenotypic data collection and refine our analysis. Goal 3: Developing genomic selection models to enhance NUE-related traits. In 2024, we refined our mediation model and developed a new model to dissect the colocalized GWAS and eQTL with mediation analysis. It was published on a peer-review journal (Zhang et al., 2024). In the meanwhile, using the rhizosphere microbiome and host genetics data, we are currently developing a microbiome-wide association study (MWAS) model to detect the host trait associated ASVs by considering the host population structure and genetic relatedness. Our results identified 38 core ASVs that are significantly associated with host phenotypic traits. We will continue to refine the association analysis.
Publications
- Type:
Peer Reviewed Journal Articles
Status:
Published
Year Published:
2024
Citation:
Qi Zhang, Zhikai Yang, Jinliang Yang, Dissecting the colocalized GWAS and eQTLs with mediation analysis for high-dimensional exposures and confounders, Biometrics, Volume 80, Issue 2, June 2024, ujae050, https://doi.org/10.1093/biomtc/ujae050
- Type:
Peer Reviewed Journal Articles
Status:
Published
Year Published:
2025
Citation:
Mukhtar, H., Hao, J., Xu, G. et al. Nitrogen input differentially shapes the rhizosphere microbiome diversity and composition across diverse maize lines. Biol Fertil Soils 61, 112 (2025). https://doi.org/10.1007/s00374-024-01863-4
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Progress 01/01/23 to 12/31/23
Outputs
Target Audience:Our targeted audience includes researchers and students in the areas of plant genetics, plant breeding, and microbiology. Corn growers who are interested in reducing agricultural input and are looking for organic solutions to lower nitrogen input in their fields might also find our work relevant. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?In 2023, we trained 2 postdocs, 2 PhD students, 1 MS student, and 5 undergraduates (including one UCARE in Yang lab). The two postdoctoral research scholars, one in Dr. Yang's lab and one in Dr. Schachtman's lab, are in charge of host genetics and microbiome data analysis and data integration. In Yang's lab, one Ph.D. student graduated, and another Ph.D. student enrolled in plant breeding and genetics started working on the project. With the guidance of Dr. Yang, a UCARE (The Undergraduate Creative Activities and Research Experience) undergraduate student at UNL has been successfully accepted for the 2023-2024 program cycle to conduct plant microbiome-related research. Additionally, a master's student in Dr. Schachtman's lab is being trained in microbial ecology and has successfully completed her second year and has become proficient at low nitrogen and microbe testing experiments as well as rigorous statistical analyses. How have the results been disseminated to communities of interest?We published the microbiome-enabled genomic selection manuscript to G3 (doi.org/10.1101/2023.03.03.530932). One graduate student from Dr. Yang's lab was selected to give a talk about the work during the Maize Genetics Conference in St. Louis in March 2023. One graduate student from Dr. Schachtman's lab presented a poster at the Nitrogen Use Efficiency Workshop at Oklahoma State University in August 2023. In 2023, Dr. Yang disseminated the work to local (UNL Plant Pathology Seminar, Mar. 2023; Nebraska Plant Science Symposium, Apr. 2023; Complex Biology Seminar CBIO-841 class, Nov. 2023), national (Corn Breeding Research Meeting, Mar. 2023), and international communities (Plant and Animal Genomics Conference, Jan. 2023; the University of Bonn, Germany, Jul. 2023), including both academia and industry audiences (Invited talk for Google-X). What do you plan to do during the next reporting period to accomplish the goals?Goal 1 - Further testing of bacterial isolates. Some promising isolates will be followed up with further testing. In the next year, we will focus on showing their efficacy in improving growth under low N conditions using N-responsive GEM genotypes. Goal 2 - 16S data will be analyzed to cross-validate the GWAS results. We will focus on understanding the genetic control of 16S data showing heterosis. Additionally, we will test whether microbiome heterosis contributes to phenotypic heterosis. Goal 3 - We will apply the microbiome-enabled prediction model from a diversity population (previously published maize association panel) to a breeding population (the GEM population from this project). Additionally, we will conduct a mediation analysis using the 16S, genotypic, and phenomics data by considering the microbiome as the intermediate molecular process.
Impacts
What was accomplished under these goals?
Goal 1: Testing NUE-related phenotypic effects of the beneficial microbes. In Goal 1, Dr. Yang provided Dr. Schachtman with ASV sequences from a previous study (Meier et al., 2022). These sequences came from a culture-independent field study that identified ASVs genetically associated with nitrogen use efficiency (NUE) measurements in maize. Dr. Schachtman's lab searched these ASVs against a 16S database of a large culture collection, identifying 60 bacterial isolates related to the ASVs. These isolates were tested multiple times in an axenic system under low nitrogen conditions. The low nitrogen testing system was calibrated using full-strength Hoagland's solution and a solution with similar ionic content, except for 10% nitrate concentration and 50% ammonium concentration. Maize seeds (Mo17 genotype) were sterilized using a chlorine gas method, imbibed in sterile aerated water for 24 hours, and planted in a sterilized turface placed in sterile germination bags. A sterile membrane was added to the bags to facilitate gas exchange. Seeds were primed with each microbe culture for 12 hours immediately after radical emergence and then planted on a sterilized surface and placed in sterile germination bags with a membrane on them that allows for gas exchange. Plants were maintained in the bags for 15 days, after which they were harvested, and their root and shoot dry weight and fresh weight were measured. In each experiment, 4-8 replicates of plants were grown with and without microbes under low nitrogen conditions, with a no microbe high nitrogen control included for calibration. This work has now been completed, and three promising microbes have been found, with one providing significantly higher growth to maize under low N conditions. Currently, this microbe, along with two others, is being tested in a semi-sterile soil system where plants will be allowed to grow for 4 - 5 weeks. Goal 2: Validating microbiome-associated GWAS signals using an unrelated population. In Goal 2, we conducted a replicated field experiment under low and high N field conditions in 2023, following the same experimental design in 2022. The field trial involved planting 300 GEM-DH lines and over 200 GEM hybrids, as well as some checks (total plot number, n = 2,200). In 2023, we processed and sequenced the maize rhizosphere microbiome using a 16S amplicon sequence from samples collected in the summer of 2022. We also completed the phenotypic data collection for six ear-related traits and seven below-ground root traits. Following the same procedure, in the 2023 field trial, we excavated roots and captured images for each excavated root for phenotyping. We also harvested mature ears and are working on ear-related trait phenotyping. In 2023, we analyzed the 16S amplicon sequencing data and found that N treatment had contrasting effects on the rhizosphere microbial communities of inbreds and hybrids. The inbred lines were characterized by higher alpha diversity and a lower abundance of Pseudomonas taxa. Further, our results suggested that N treatment significantly increased both rhizosphere microbial network modularity and the ratio of negative to positive interactions compared to untreated soils in inbred lines. This aligns with the Stress Gradient Hypothesis, suggesting a shift toward positive interactions between microbial species as environmental stress increases. Conversely, the rhizosphere microbial networks of hybrids exhibited minimal sensitivity to N treatments and supported fewer modular networks under high N. The proportion of variance determined by plant host factors was also better explained under low N, demonstrating that N fertilization reduced the influence of the host over the rhizosphere microbial community. We submitted a manuscript of the above-mentioned results for peer review. Additionally, our results from analyzing the phenotypic data revealed that hybrids consistently outperform inbreds for conventional phenotypic traits under both N conditions. Interestingly, microbial traits generally display lower abundance and diversity in hybrids than inbreds under high N conditions. However, under low N conditions, about 10-20% of the microbial traits exhibit heterosis. To uncover the genetic basis of traits (including rhizosphere microbial traits) per se, heterosis, and N-responsive traits, we conducted Genome-wide Association Studies (GWAS) and identified a number of favorable tropical alleles, some of which contributed to the heterosis of conventional or microbial traits and were associated with N-responsive traits. We will continue to finish the phenotypic data collection and refine our analysis. Goal 3: Developing genomic selection models to enhance NUE-related traits. For Goal 3, we revised and improved our microbiome-enabled genomic selection model that integrated host genetics (SNPs) and host-associated microbiome (ASVs). Using our previously published data on the maize diversity panel (Meier et al., 2022), the results suggested that the microbiome-enabled prediction model substantially outperformed the conventional model for nearly all time-series traits associated with plant growth and N responses, achieving an average relative improvement of 4%. The improvement was more pronounced under low N conditions (8.4-40.2% relative improvement), consistent with the view that some beneficial microbes can enhance N nutrient uptake, particularly in low N fields. We published our results in G3.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Zhikai Yang, Tianjing Zhao, Hao Cheng, Jinliang Yang, Microbiome-enabled genomic selection improves prediction accuracy for nitrogen-related traits in maize, G3 Genes|Genomes|Genetics, Volume 14, Issue 3, March 2024, jkad286, https://doi.org/10.1093/g3journal/jkad286
- Type:
Journal Articles
Status:
Submitted
Year Published:
2024
Citation:
Hussnain Mukhtar, Jingjie Hao, Gen Xu, Emma Bergmeyer, Musa Ulutas, Jinliang Yang, Daniel P. Schachtman. Nitrogen Input Differentially Shapes the Rhizosphere Microbiome Complexity, Stability and Community Structure Across Diverse Maize Lines. Submitted to Biology and Fertility of Soils
- Type:
Journal Articles
Status:
Accepted
Year Published:
2024
Citation:
E. Rodene, G. D. Fernando, V. Piyush, Y. Ge, J. C. Schnable, S. Ghosh, J. Yang, Image filtering to improve maize tassel detection accuracy using machine learning algorithms, Sensors, 2024.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
S. Palali Delen, J. Lee, J. Yang, Improving the metal composition of plants for reduced Cd and increased Zn content: molecular mechanisms and genetic regulations, Cereal Research Communications, 2023.
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Progress 01/01/22 to 12/31/22
Outputs
Target Audience:Scientific researchers in the area of plant genetics and genomics, and microbiology Local corn growers Master and Ph.D. students in plant breeding and genetics, as well as Complex Biosystems Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?One Postdoc research scholar in Dr. Yang's lab is being trained. Two Ph.D. students in Dr. Yang's lab are currently in their fourth year of training in plant breeding and genetics, as well as Complex Biosystems programs. One undergraduate student is being trained in Dr. Yang's lab. With the guidance of Dr. Yang, the undergrad applied for a UCARE (The Undergraduate Creative Activities and Research Experience) at UNL and has been successfully accepted for the 2023-2024 program cycle for conducting plant microbiome-related research. Additionally, a master's student in Dr. Schachtman's lab is being trained in microbial ecology as it applies to agroecosystems. She is just finishing her first year. How have the results been disseminated to communities of interest?We have uploaded the microbiome-enabled genomic selection manuscript to bioRxiv (doi.org/10.1101/2023.03.03.530932), and it is currently under review by a peer-reviewed journal. In July 2022, Dr. Yang led an online workshop hosted by AG2PI (Agricultural Genome to Phenome Initiative) titled "Genome-wide mediation analysis: bringing genotype to phenotype via intermediate omics data". ?In December 2022, Dr. Yang disseminated the research to a graduate seminar course CBIO-841 (Biosystems Research I: Big Questions) titled "Improving nitrogen-use-efficiency for crop production". What do you plan to do during the next reporting period to accomplish the goals?Goal 1 - 16S data will be fully analyzed in the next year. Further testing of bacterial isolates will be conducted to confirm preliminary results and to test key microbes that show efficacy in improving growth under low nitrogen on additional maize genotypes. Goal 2 - 16S data will be analyzed to test the difference between high N and low N conditions. Additionally, we will compare 16S data between hybrids and their inbred parents to test if the microbiome data is showing heterosis. If so, we will then test if the microbiome heterosis will contribute to phenotypic heterosis. ?Goal 3 - We will continue to improve the microbiome-enabled prediction model. Additionally, we will conduct a mediation analysis by considering the microbiome as the intermediate molecular process.
Impacts
What was accomplished under these goals?
Goal 1: Testing NUE-related phenotypic effects of the beneficial microbes. In Goal 1, Dr. Yang provided Dr. Schachtman with ASV sequences from a previous study (Meier et al., 2022). These sequences came from a culture-independent field study that identified ASVs genetically associated with nitrogen use efficiency (NUE) measurements in maize. Dr. Schachtman's lab searched these ASVs against a 16S database of a large culture collection, identifying 60 bacterial isolates related to the ASVs. These isolates were then tested in an axenic system under low nitrogen conditions. The low nitrogen testing system was calibrated using full-strength Hoagland's solution and a solution with similar ionic content, except for 10% nitrate concentration and 50% ammonium concentration. Maize seeds (Mo17 genotype) were sterilized using a chlorine gas method, imbibed in sterile aerated water for 24 hours, and planted in a sterilized turface placed in sterile germination bags. A sterile membrane was added to the bags to facilitate gas exchange. Seeds were primed with each microbe culture for 12 hours during germination and then planted in the turface. Plants were maintained in the bags for 15 days, after which they were harvested and their root and shoot dry weight and fresh weight were measured. In each experiment, 4-8 replicates of plants were grown with and without microbes under low nitrogen conditions, with a high nitrogen control included for calibration. This work is approaching completion, and the findings will contribute valuable insights into the relationship between host genetics, root-colonizing microbes, and plant phenotypes under different nitrogen conditions in maize. Goal 2: Validating microbiome-associated GWAS signals using an unrelated population. In Goal 2, we carried out a replicated field trial in 2022, collecting above-ground and below-ground phenotypes as well as 16S sequencing data. The field trial involved planting 300 GEM-DH lines and over 200 GEM hybrids, along with some checks, following an incomplete block design. Each genotype had two replications under both high N and low N field conditions, resulting in a total of 2,400 single-row plots (600 genotypes x 2 reps x 2 N levels). From these plots, two plants per plot were excavated at the VT stage, and roots were collected. The roots were then placed into a phosphate buffer and vortexed for two minutes to remove rhizosphere soil. The samples were processed in the lab following the method described by McPherson et al. (2017). Once the rhizosphere soil was isolated, PCR was performed to amplify the V4 region of the 16S gene. The amplicons were then quantified and normalized. Approximately 240 samples containing equal amounts of amplicon were multiplexed for each run and sequenced using MiSeq V3 Illumina sequencing. In total, we have processed and sequenced samples from 2,200 plots. The next step will involve analyzing the data to further understand the relationships between plant genotypes, rhizosphere microbial communities, and nitrogen conditions in the field. Goal 3: Developing genomic selection models to enhance NUE-related traits. ?For Goal 3, we designed a microbiome-enabled genomic selection model that integrated host SNPs and ASVs from plant root-associated microbiomes under high and low N field conditions. We utilized our previously published data on the maize diversity panel (Meier et al., 2022) to develop this model. Our results indicated that the microbiome-enabled prediction model substantially outperformed the conventional model for nearly all time-series traits associated with plant growth and N responses, achieving an average relative improvement of 4%. This enhancement was more significant for traits measured closer to the microbiome data collection date and was more pronounced under low N conditions.
Publications
- Type:
Journal Articles
Status:
Under Review
Year Published:
2023
Citation:
Z. Yang, T. Zhao, H. Cheng , and J. Yang, Microbiome-enabled genomic selection improves prediction accuracy for nitrogen-related traits in maize, bioRxiv, 2023. 10.1101/2023.03.03.530932v1
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