Location: Corn Insects and Crop Genetics Research
2022 Annual Report
Objectives
Objective 1: Identify and characterize genes, markers, and molecular networks contributing to yield, resistance to pathogens, and nutrient stress tolerance in soybean and other legumes, and work with researchers to use the information in crop improvement by conventional breeding and gene editing technology.
Sub-objective 1.A. Identify and characterize legume gene expression and epigenetic networks that control nutrient homeostasis, generating information for improving resistance or tolerance to abiotic stress.
Sub-objective 1.B. Identify and characterize soybean disease resistance loci and defense gene expression and epigenetic networks, generating information for improving resistance or tolerance to pathogens that cause economic loss in soybeans.
Approach
The United States leads world soybean production, contributing over 40 billion dollars to the economy in 2014. However, nutrient, disease and pest stresses limit agricultural production. The overarching goal of this project is to provide data and resources that will increase soybean (Glycine max (L.) Merrill) production by mitigating losses due to abiotic and biotic stresses. To study nutrient deficiency we will use iron deficiency chlorosis as a model. To study disease resistance responses we will use a variety of pathogens including Phakopsora pachyrhizi (Asian soybean rust), Phialophora gregata (brown stem rot), Phytophthora sojae (Phytophthora rot), and the insect pest Aphisglycines (soybean aphid). Regulation of abiotic and biotic stress responses requires constant signaling, likely controlled by gene expression and epigenetic changes. Further, a single stress exposure likely primes subsequent plant stress responses. To characterize the genes and networks involved in these responses we will couple RNA-seq, Methyl-seq and Virus Induced Gene Silencing. Finally, we will use RNA-seq data to characterize resistance loci and downstream defense responses. Successful completion of this project will result in genes, gene networks and validated markers that can be used to breed soybean germplasm with durable resistance to abiotic and biotic stress. This project will provide valuable resources to public and private soybean breeders, scientists and growers.
Progress Report
Subobjective 1.A: Identifying gene expression networks contributing nutrient stress tolerance.
Characterizing novel root to shoot iron stress signaling mechanisms in soybean. Iron deficiency chlorosis significantly impacts soybean yield and quality. Previous gene expression experiments by ARS scientists in Ames, Iowa suggested the soybean line Clark signals iron deficiency stress from root to shoot. To further study this novel finding, we took advantage of two nearly identical soybean lines, with contrasting iron stress tolerance. Shoots from an iron stress susceptible line were grafted to roots from an iron stress tolerant line (and vice versa). Following grafting, plants were maintained in iron sufficient media to allow grafts to heal. Two weeks later, plants were transferred to either fresh iron sufficient media or iron deficient media. After 2 weeks, the plants were evaluated for their iron stress tolerance. Only grafted plants with iron stress tolerant roots were iron stress tolerant, supporting the root to shoot signaling hypothesis. We then repeated the experiment, harvesting leaf and root tissue from grafted plants 30 minutes, 2 hours, and 2 weeks after transfer to either iron sufficient or iron deficient media for use in whole genome expression analyses. Gene activity in response to iron stress conditions was first detected in the roots, not the shoots. Analyses of these data suggest that only iron stress tolerant roots can signal iron stress conditions to the leaves. This signal initiates sometime between 30 and 120 minutes after transfer to iron stress conditions. This data highlights knowledge gaps between crop and model species and identifies key genes involved in iron stress tolerance signaling networks from roots to shoots. This research will identify genes and markers for improving crop responses to abiotic stress conditions.
Characterizing candidate genes in the historic iron stress tolerance quantitative trait locus in soybean. Previous research by ARS and Iowa State University scientists demonstrated that a region on soybean chromosome 3 associated with iron stress tolerance was composed of four distinct regions, each containing candidate iron stress response genes. We used virus-induced gene silencing (VIGS) to turn-down the activity of candidate genes within these four regions. Silenced plants were grown in soil and in iron stress conditions to identify changes in iron stress tolerance due to gene silencing. After multiple rounds of testing, three candidate genes were selected for further evaluation. Each gene was silenced individually and in combination with one of the other three remaining candidate genes. Silenced plants were grown in iron sufficient conditions, allowing us to determine if silencing blocked iron uptake and homeostasis, resulting in iron stress even under iron replete conditions. These analyses confirmed that multiple genes in this region are required for iron stress tolerance. Analyses of these data sets will identity novel iron stress response genes in soybean and the molecular networks they control. This research will provide new genes for improving crop responses to abiotic stress conditions, leading to new and improved varieties.
Characterizing the role of a candidate gene in the Fiskeby III soybean iron stress response. Iron deficiency is one of the leading causes of yield loss in the upper Midwest. Soybean line Fiskeby III exhibits high tolerance to a multitude of abiotic stresses, including iron deficiency. In previous work in collaboration with the University of Minnesota, we combined fine-mapping, whole genome expression analyses and VIGS to identify a multidrug and toxic compound extrusion (MATE) transporter associated with iron stress tolerance in Fiskeby III. In current work, we silenced the MATE transporter, then exposed plant to either 2 or 7 days of iron stress, controlling for the age of the plant. Whole genome expression analyses were used to examine the impact of gene silencing on iron stress responses in leaves and roots. This analysis has revealed that as Fiskeby III is exposed to extended iron deficient growth conditions, phosphate deficient responses are invoked in leaves and roots. Additionally, the silencing of the candidate gene induces a gene responsible for interacting with transcription factors bound to the DNA; directly regulating transcription. Further, expression of this subunit is required to induce a plant defense gene that modulates iron homeostasis in leaves and subsequent responses in roots. This research will provide new targets for improving soybean’s response to abiotic stress.
Determining if methylation plays a role in the soybean iron stress response. Previous research has determined changes in genes associated with DNA replication/methylation is a classic response to iron deficiency in soybean and other crop species. In soybean, time-course studies have found that genes associated with DNA replication/methylation exhibit altered expression profiles at the earliest timepoints examined. To test the hypothesis that methylation may be involved with regulating iron stress responses, we grew iron stress tolerant soybeans in iron sufficient hydroponic conditions for 7 days. On day 8, half the plants were moved to new iron sufficient conditions, while half the plants were moved to iron deficient conditions. Whole roots and leaves were harvested at 60 minutes, 120 minutes, and 7 days after stress was induced. The collected tissue was used for both RNA and DNA extraction for whole transcriptome sequencing and bisulfite methylome sequencing. The data is currently being analyzed using the USDA SCINet infrastructure and resources to cross reference differentially methylated genes with gene expression levels. Understanding how and when methylation patterns change and alter gene expression will be a valuable tool for plant geneticists to understand crop responses to abiotic stress.
Subobjective 1.B: Identifying gene expression networks contributing to defense against pathogens.
Characterization of the Resistance to Phakospora Pachyrhizi 3 (Rpp3) loci in soybean. Asian soybean (ASR) rust is a threat to soybean production worldwide. Identification of resistance/defense genes is essential for improving commercial cultivars. In collaboration with ARS researchers in Ft. Detrick, Maryland, we attempted to use a map-based cloning approach to identify candidate genes for Rpp3. Unfortunately, multiple failed attempts to clone the Rpp3 locus suggest the region is unstable, inhibiting the cloning process. Therefore, we identified the region corresponding to Rpp3 in the genome sequence of the ASR susceptible line Williams 82. The sequences of the five resistance genes in this region were used to develop a VIGS construct that silenced Rpp3 in the soybean line Ankur (PI 462312) and to generate sequence data from the five resistance genes in Ankur. One of these five genes, which contains a novel DNA insertion not found in Williams 82, is the candidate gene for Rpp3. Expression analyses suggest only this gene is activated following infection by P. pachyrhizi. Breeders and scientists can use the markers and genes developed by this project to incorporate resistance to ASR into improved commercial cultivars.
Characterizing candidate brown stem rot resistance genes in soybean. Brown stem rot, caused by the fungus Phialophora gregata, reduces soybean yield by 38%. Identifying new sources of resistance has been complicated by time-consuming phenotyping methods and conflicting genetic studies. In a previous study funded by the USDA, National Institute of Food and Agriculture, we combined historical mapping data with genotype expression differences to identify clusters of receptor-like proteins (RLPs), similar to known fungal resistance genes, associated with each of the previously identified resistance genes (Rbs1, Rbs2, and Rbs3). In recent work, we developed VIGS constructs to knock down the activity of these clusters individually and in combination. Members of two clusters are required for Rbs1-mediated resistance. In work funded by the United Soybean Board, whole genome expression analyses confirm silencing of two RLP clusters suppresses defense responses leading to disease susceptibility. This novel research combines contrasting genotypes, classical genetic studies, whole genome expression analyses and VIGS to characterize complex disease resistance traits. Breeders and scientists can use markers and genes identified by this project to incorporate disease resistance into commercial cultivars.
Characterizing Resistance to Phytopthora sojae 2 (Rps2) mediated signaling in soybean. Phytophthora is the second most damaging disease of soybean. In research funded by the United Soybean Board and in collaboration with The Ohio State University researchers, we combined their whole genome expression analyses of three Rps genes (Rps2, Rps3 and Rps8) with publicly available data targeting another four Rps genes (Rps1, Rps3, Rps5 and Rps6). We mined the data to identify signaling genes and transcription factors unique to resistance responses to P. sojae. Twenty genes were selected for analysis using VIGS to silence their expression. VIGS constructs were applied to plants containing the Rpp2 gene, which were then infected or mock-infected with the appropriate P. sojae strain to trigger Rpp2-mediated resistance. So far, no VIGS constructs have inhibited Rpp2-mediated resistance. This response had also been observed by collaborators using other VIGS constructs, suggesting they may be triggering basal defense responses. We are evaluating new inoculation methods. Characterizing novel signaling genes will enable crop improvement.
Accomplishments
1. Characterizing responses to iron deficiency chlorosis in the soybean germplasm collection. In plants, iron deficiency causes interveinal leaf yellowing, and a reduction in photosynthesis and yield. However, much or our knowledge of iron deficiency response mechanisms is from model species. Studies suggest important differences in iron stress responses between soybean and model species. Since crops have been adapted to multiple climates around the world, there are likely multiple mechanisms for responding to iron stress. In collaboration with researchers from Iowa State University, ARS scientists in Ames, Iowa, selected 18 unique soybean lines from the USDA soybean germplasm collection, with a range of iron stress tolerance. The lines were grown in both iron sufficient and deficient conditions and responses were compared. These analyses confirmed that multiple lines responded to iron stress within 60 minutes, much faster than observed in model species. Across all lines, iron stress responses were first detected in the roots, suggesting soybean uses novel root to shoot signaling mechanisms. Also, results suggested there are multiple novel mechanisms for conferring iron stress tolerance in the soybean germplasm collection. These findings highlight the need for conducting research in diverse, agronomically important crop species. Such studies will aid plant breeders in developing soybean lines with improved stress tolerance and greater yield, benefitting both farmers and growers.
2. Using genomics to determine the molecular effects of combining multiple resistance genes to combat Aphids in soybean. Throughout history, plant breeders have incorporated multiple resistance genes targeting specific pathogens or pests within a single line. Lines with multiple resistance genes offer a more robust and durable resistance response compared to lines with individual resistance genes. In soybean, aphid resistance is conferred by Rag genes. Plants containing the Rag1 and Rag2 genes are significantly more resistant to aphid attack than plants containing either Rag1 or Rag2 alone. To understand how combining resistance genes enhances resistance, researchers from Iowa State University and ARS scientists in Ames, Iowa, conducted whole genome expression analyses of four soybean lines (aphid-susceptible, Rag1, Rag2 and a line containing Rag1 and Rag2), collecting samples after infestation with soybean aphids. Approximately 1,000 genes were specifically expressed in response to aphids in the line containing Rag1 and Rag2, but not in either of the single resistance lines. Many of the genes unique to the Rag1 and Rag2 line had functions related to defense including modification of cell walls, detection of pests and pathogens and defense signaling. Understanding how combining multiple resistance genes results in enhanced resistance is essential for future crop improvement, helping preserve yield for farmers and growers.
3. Characterizing novel regions of the soybean genome for tolerance to iron deficiency. Yield loss due to iron deficiency stress is a problem throughout the major soybean growing regions of the U.S. Fiskeby III is a soybean cultivar with a high level of resistance to multiple abiotic stresses, including iron deficiency. Conversely, Mandarin (Ottawa) suffers severe yield loss when exposed to iron stress. In a project funded by the United Soybean Board, and working with collaborators at the University of Minnesota, ARS scientists in Ames, Iowa, used whole genome expression analyses to compare the Fiskeby III and Mandarin (Ottawa) responses to normal and iron deficient conditions. Researchers then combined previous genome mapping with the whole genome expression analyses to identify 15 candidate genes for a genomic region associated with iron stress tolerance on Fiskeby III chromosome 5. Using virus induced gene silencing (VIGS), all 15 candidate genes were assessed for their roles in iron stress tolerance. Silencing of a multidrug and toxic compound extrusion (MATE) transporter gene resulted in iron stress symptoms, even though plants were grown in iron sufficient conditions. To further evaluate this gene, whole genome expression analyses were conducted on MATE silenced plant grown in iron sufficient and deficient conditions. These analyses confirmed the identify of a new iron stress response gene. These findings can be leveraged by plant breeders to improve abiotic stress tolerance in soybean and other crop species.
4. Dissection of canopy layer-specific genetic control of leaf angle in Sorghum bicolor by RNA sequencing. Leaf angle is an important plant architecture trait, affecting plant density, light interception efficiency, photosynthetic rate, and yield. Ideally, more vertical leaves in the top layers and more horizontal leaves in the lower canopy would maximize overall light conversion efficiency and photosynthesis. Leaf arrangement in sorghum is reversed, suggesting room for improvement. The Dwarf3 (Dw3) auxin transporter has a validated role in controlling leaf angle in sorghum. Iowa State University researchers in collaboration with ARS scientists in Ames, Iowa, used whole genome expression analyses to monitor gene activity across the plant canopy in five sorghum genotypes, each having different versions of the Dw3 gene and with significant leaf angle differences. The researchers identified 284 genes whose activity differed across the canopy in all five genotypes, nine genes were associated with previously identified genomic regions associated with leaf angle. The majority of these genes are involved in transmembrane transport, hormone regulation, response to stimuli, lipid metabolism, and photosynthesis. Further characterization of these genes will allow sorghum researchers to alter leaf angle to the ideal state for sorghum and consequently improve yield, benefitting farmers and growers around the world.
5. Identification of candidate genes for a major quantitative disease resistance locus for Phytophthora root rot. Phytophthora root rot is the second most damaging disease of soybean. Historically, breeders have relied on single resistance genes to combat this disease, however, widespread use of these genes has allowed the pathogen to evolve to evade plant resistance responses. Unlike qualitative resistance, which is controlled by single resistance genes, partial resistance, also known as quantitative resistance, is more durable as it is controlled by several genes distributed across the genome. In work funded by the United Soybean Board, researchers from The Ohio State University, Chungnam National University and ARS scientists (Ames, Iowa and Raleigh, North Carolina) have identified a region on soybean chromosome 18 that contributes up to 45% to quantitative resistance to the pathogen. The researchers combined high resolution mapping with whole genome expression analyses to identify a single gene of interest within this region. This research is an important step in identifying genes conferring durable resistance, however further work is needed to understand how this gene contributes to resistance to protect plan yield for farmers and growers.
Review Publications
Natukunda, M.I., Hohenstein, J.D., McCabe, C.E., Graham, M.A., Qi, Y., Singh, A.K., MacIntosh, G.C. 2021. Interaction between Rag genes results in a unique synergistic transcriptional response that enhances soybean resistance to soybean aphids. BMC Genomics. 22. Article 887. https://doi.org/10.1186/s12864-021-08147-3.
Natukunda, M.I., Mantilla-Perez, M.B., Graham, M.A., Liu, P., Salas-Fernandez, M.G. 2022. Dissection of canopy layer-specific genetic control of leaf angle in Sorghum bicolor by RNA sequencing. BMC Genomics. 23. Article 95. https://doi.org/10.1186/s12864-021-08251-4.
O'Rourke, J.A., Morrisey, M.J., Merry, R., Espina, M.J., Lorenz, A.J., Stupar, R.M., Graham, M.A. 2021. Mining Fiskeby III and Mandarin (Ottawa) expression profiles to understand iron stress tolerant responses in soybean. International Journal of Molecular Sciences. 22(20). Article 11032. https://doi.org/10.3390/ijms222011032.
Kohlhase, D.R., Mccabe, C.E., Singh, A.K., O'Rourke, J.A., Graham, M.A. 2021. Comparing early transcriptomic responses of 18 soybean (Glycine max) genotypes to iron stress. International Journal of Molecular Sciences. 22(21). Article 11643. https://doi.org/10.3390/ijms222111643.
