Withdraw
Loading…
Improvement of soybean breeding via high throughput phenotyping and disease resistance
Yu, Chong
Loading…
Permalink
https://hdl.handle.net/2142/93020
Description
- Title
- Improvement of soybean breeding via high throughput phenotyping and disease resistance
- Author(s)
- Yu, Chong
- Issue Date
- 2016-07-07
- Director of Research (if dissertation) or Advisor (if thesis)
- Diers, Brian
- Doctoral Committee Chair(s)
- Diers, Brian
- Committee Member(s)
- Nelson, Randall
- Hudson, Matthew
- Schroeder, Nathan
- Department of Study
- Crop Sciences
- Discipline
- Crop Sciences
- Degree Granting Institution
- University of Illinois at Urbana-Champaign
- Degree Name
- Ph.D.
- Degree Level
- Dissertation
- Keyword(s)
- Soybean
- Unmanned aerial Vehicle
- Remote sensing
- Multi-spectral image
- Yield estimation
- Maturity
- Soybean cyst nematode
- Fine mapping
- Glycine soja
- Asian soybean rust
- Disease resistance
- Abstract
- Development of an Unmanned Aerial Vehicle High Throughput Phenotyping Platform to Improve Soybean Breeding Efficiency Advances in phenotyping technology are critical to ensure the genetic improvement of crops meet future global demands for food and fuel. Field-based phenotyping platforms are being evaluated for their ability to deliver the necessary throughput for large scale experiments and to provide an accurate depiction of trait performance in real-world environments. We developed a dual-camera high throughput phenotyping (HTP) platform on an unmanned aerial vehicle (UAV) and collected time course multispectral images for large scale soybean [Glycine max (L.) Merr.] breeding trials. We used a supervised machine learning model (Random Forest) to measure crop geometric features and obtained high correlations with final yield in breeding populations (r = 0.82). The traditional yield estimation model was significantly improved by incorporating plot row length as covariate (p<0.01). We developed a binary prediction model from time-course multispectral HTP image data and achieved over 93% accuracy in classifying soybean maturity. This prediction model was validated in an independent breeding trial with a different plot type. These results show that multispectral data collected from the UAV-based HTP platform could improve yield estimation accuracy and maturity recording efficiency in a modern soybean breeding program. Impact of Rhg1 Copy Number and Interaction with Rhg4 on Resistance to Heterodera glycines in Soybean Rhg1 and Rhg4 are important loci conferring resistance to soybean cyst nematode (SCN; Heterodera glycines). Alleles at Rhg1 have been shown to vary for copy number and type and the importance of this variation in conferring resistance is not well defined. The repeat number ranges from one to 10 and there are three variant repeat sequence types [PI 88788-'Fayette' type (F), 'Peking' type (P) and Williams 82 type (W)] across diverse soybean germplasm. We developed populations segregating for Rhg1 copy number and type and Rhg4 allele type to investigate the effect of these factors and their interaction on SCN resistance. F2 plants from each cross were evaluated for the segregation of Rhg1 and Rhg4 alleles and for SCN reproduction after infesting plants with HG type 2.5.7 and HG type 7 populations. Within repeat types, an increase in repeat number was associated with greater resistance. The P type Rhg1 showed an advantage over F+W type for SCN population HG type 2.5.7 but this was not observed for SCN HG type 7. While plants with P type Rhg1 required Rhg4 to achieve full resistance, Rhg4 did not increase resistance in the background of F+W type Rhg1 repeat. This study demonstrates the importance of both Rhg1 copy number and type in determining resistance and can assist soybean breeders in determining what alleles would best fit their breeding goals. Fine Mapping of the SCN Resistance QTL cqSCN-006 and cqSCN-007 from Glycine soja PI 468916 The majority of soybean cyst nematode (Heterodera glycines Ichinohe, SCN) resistant cultivars available to growers in the northern USA have resistance originating from PI 88788, which is being overcome by shifting SCN populations. The novel resistance quantitative trait loci (QTL) cqSCN-006 and cqSCN-007 were mapped from Glycine soja Sieb. and Zucc. plant introduction (PI) 468916. The objective of this study was to further narrow down these QTL intervals to improve the effectiveness of marker-assisted selection (MAS) for resistance and to provide resources for cloning these genes. The fine mapping was initiated by screening recombinant plants using simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers that flank these QTL. Selected recombinant plants were tested with additional genetic markers saturating the QTL intervals and progeny from the recombinant plants were then tested for resistance in a SCN bioassay. These efforts resulted in the fine mapping of cqSCN-006 into a 212.1 kb interval and cqSCN-007 to a 103.2 kb interval on the Williams 82 reference genome (Glyma.Wm82.a2), which reduced the interval size compared to previous fine mapping by 62% and 30%. One gene located in the cqSCN-006 region was predicted to encode a γ-soluble N-ethylmaleimide–sensitive factor attachment protein (γ-SNAP), which is involved in the same process as α-SNAP, one of the required components in Rhg1 SCN resistance. The identified SSR and SNP markers close to these novel SCN resistance QTL and the candidate gene information presented in this study will be significant resources for MAS and gene cloning research. Fine mapping of the Asian soybean rust resistance gene Rpp2 from soybean PI 230970 Asian soybean rust (ASR), caused by the fungus Phakopsora pachyrhizi Syd. & P. Syd, is a serious disease in major soybean [Glycine max (L.) Merr.] production countries worldwide and causes yield losses up to 75%. Defining the exact chromosomal position of ASR resistance genes is critical for improving the effectiveness of marker-assisted selection (MAS) for resistance and for cloning these genes. The objective of this study was to fine map the ASR resistance gene Rpp2 from the plant introduction (PI) 230970. Rpp2 was previously mapped within a 12.9-cM interval on soybean chromosome 16. The fine mapping was initiated by identifying recombination events in F2 and F3 plants using simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers that flank the gene. Seventeen recombinant plants were identified and then tested with additional genetic markers saturating the gene region to localize the positions of each recombination. The progeny of these selected plants were tested for resistance to ASR and with SSR markers resulting in the mapping of Rpp2 to a 188.1 kb interval on the Williams 82 reference genome (Glyma.Wm82.a2). Twelve genes including ten toll/interleukin-1 receptor (TIR) nucleotide-binding site (NBS) leucine-rich repeat (LRR) genes were predicted to exist in this interval on the Glyma.Wm82.a2.v1 gene model map. Eight of these ten genes were homologous to the Arabidopsis TIR-NBS-LRR gene AT5G17680.1. The identified SSR and SNP markers close to Rpp2 and the candidate gene information presented in this study will be significant resources for MAS and gene cloning research.
- Graduation Semester
- 2016-08
- Type of Resource
- text
- Permalink
- http://hdl.handle.net/2142/93020
- Copyright and License Information
- Copyright 2016 Chong Yu
Owning Collections
Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at IllinoisManage Files
Loading…
Edit Collection Membership
Loading…
Edit Metadata
Loading…
Edit Properties
Loading…
Embargoes
Loading…