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Zhang S, Wu Y, Skaro M, Cheong JH, Bouffier-Landrum A, Torrres I, Guo Y, Stupp L, Lincoln B, Prestel A, Felt C, Spann S, Mandal A, Johnson N, Arnold J. Computer vision models enable mixed linear modeling to predict arbuscular mycorrhizal fungal colonization using fungal morphology. Sci Rep 2024; 14:10866. [PMID: 38740920 DOI: 10.1038/s41598-024-61181-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 05/02/2024] [Indexed: 05/16/2024] Open
Abstract
The presence of Arbuscular Mycorrhizal Fungi (AMF) in vascular land plant roots is one of the most ancient of symbioses supporting nitrogen and phosphorus exchange for photosynthetically derived carbon. Here we provide a multi-scale modeling approach to predict AMF colonization of a worldwide crop from a Recombinant Inbred Line (RIL) population derived from Sorghum bicolor and S. propinquum. The high-throughput phenotyping methods of fungal structures here rely on a Mask Region-based Convolutional Neural Network (Mask R-CNN) in computer vision for pixel-wise fungal structure segmentations and mixed linear models to explore the relations of AMF colonization, root niche, and fungal structure allocation. Models proposed capture over 95% of the variation in AMF colonization as a function of root niche and relative abundance of fungal structures in each plant. Arbuscule allocation is a significant predictor of AMF colonization among sibling plants. Arbuscules and extraradical hyphae implicated in nutrient exchange predict highest AMF colonization in the top root section. Our work demonstrates that deep learning can be used by the community for the high-throughput phenotyping of AMF in plant roots. Mixed linear modeling provides a framework for testing hypotheses about AMF colonization phenotypes as a function of root niche and fungal structure allocations.
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Affiliation(s)
- Shufan Zhang
- Institute of Bioinformatics, University of Georgia, Athens, GA, USA
| | - Yue Wu
- Institute of Bioinformatics, University of Georgia, Athens, GA, USA
| | - Michael Skaro
- Institute of Bioinformatics, University of Georgia, Athens, GA, USA
| | | | | | - Isaac Torrres
- Institute of Bioinformatics, University of Georgia, Athens, GA, USA
| | - Yinping Guo
- Genetics Department, University of Georgia, Athens, GA, USA
| | - Lauren Stupp
- Genetics Department, University of Georgia, Athens, GA, USA
| | - Brooke Lincoln
- Genetics Department, University of Georgia, Athens, GA, USA
| | - Anna Prestel
- Genetics Department, University of Georgia, Athens, GA, USA
| | - Camryn Felt
- Genetics Department, University of Georgia, Athens, GA, USA
| | - Sedona Spann
- School of Earth and Sustainability and Department of Biological Sciences, North Arizona University, Flagstaff, AZ, USA
| | - Abhyuday Mandal
- Statistics Department, University of Georgia, Athens, GA, USA
| | - Nancy Johnson
- School of Earth and Sustainability and Department of Biological Sciences, North Arizona University, Flagstaff, AZ, USA
| | - Jonathan Arnold
- Genetics Department, University of Georgia, Athens, GA, USA.
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Krach EK, Skaro M, Wu Y, Arnold J. Characterizing the gene-environment interaction underlying natural morphological variation in Neurospora crassa conidiophores using high-throughput phenomics and transcriptomics. G3 (BETHESDA, MD.) 2022; 12:jkac050. [PMID: 35293585 PMCID: PMC8982394 DOI: 10.1093/g3journal/jkac050] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 02/21/2022] [Indexed: 11/12/2022]
Abstract
Neurospora crassa propagates through dissemination of conidia, which develop through specialized structures called conidiophores. Recent work has identified striking variation in conidiophore morphology, using a wild population collection from Louisiana, United States of America to classify 3 distinct phenotypes: Wild-Type, Wrap, and Bulky. Little is known about the impact of these phenotypes on sporulation or germination later in the N. crassa life cycle, or about the genetic variation that underlies them. In this study, we show that conidiophore morphology likely affects colonization capacity of wild N. crassa isolates through both sporulation distance and germination on different carbon sources. We generated and crossed homokaryotic strains belonging to each phenotypic group to more robustly fit a model for and estimate heritability of the complex trait, conidiophore architecture. Our fitted model suggests at least 3 genes and 2 epistatic interactions contribute to conidiophore phenotype, which has an estimated heritability of 0.47. To uncover genes contributing to these phenotypes, we performed RNA-sequencing on mycelia and conidiophores of strains representing each of the 3 phenotypes. Our results show that the Bulky strain had a distinct transcriptional profile from that of Wild-Type and Wrap, exhibiting differential expression patterns in clock-controlled genes (ccgs), the conidiation-specific gene con-6, and genes implicated in metabolism and communication. Combined, these results present novel ecological impacts of and differential gene expression underlying natural conidiophore morphological variation, a complex trait that has not yet been thoroughly explored.
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Affiliation(s)
- Emily K Krach
- Genetics Department, University of Georgia, Athens, GA 30602, USA
| | - Michael Skaro
- Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
| | - Yue Wu
- Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
| | - Jonathan Arnold
- Genetics Department, University of Georgia, Athens, GA 30602, USA
- Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
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Phenotype to genotype in Neurospora crassa: Association of the scumbo phenotype with mutations in the gene encoding ceramide C9-methyltransferase. CURRENT RESEARCH IN MICROBIAL SCIENCES 2022; 3:100117. [PMID: 35909622 PMCID: PMC9325734 DOI: 10.1016/j.crmicr.2022.100117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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