RNA-seq-based identification of potential resistance genes against the soybean cyst nematode (Heterodera glycines) HG Type 1.2.3.5.7 in ‘Dongnong L-10’

Jiang, Haipeng; Tian, Lizheng; Bu, Fanshan; Sun, Qiuxia; Zhao, Xue; Han, Yingpeng

doi:10.1016/j.pmpp.2021.101627

Cited by 11 publications

(12 citation statements)

References 28 publications

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“…First, RNA-seq analysis identified DEGs potentially involved in resistance, including several transcription factors [ 68 ]. Then, the same cultivar was challenged with a virulent SCN population (HG type 1.2.3.5.7) which confirmed the implication of several genes including GmRSCN4-1 and GmRSCN4-2 [ 69 ]. The two genes, which were overexpressed using a hairy root transformation in the susceptible cultivar Heinong 37, led to a substantial reduction in the number of developing SCN females.…”

Section: Identifying Novel Sources Of Resistancementioning

confidence: 88%

A Broad Review of Soybean Research on the Ongoing Race to Overcome Soybean Cyst Nematode

Nissan

Mimee

Cober

et al. 2022

Biology

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Plant pathogens greatly impact food security of the ever-growing human population. Breeding resistant crops is one of the most sustainable strategies to overcome the negative effects of these biotic stressors. In order to efficiently breed for resistant plants, the specific plant–pathogen interactions should be understood. Soybean is a short-day legume that is a staple in human food and animal feed due to its high nutritional content. Soybean cyst nematode (SCN) is a major soybean stressor infecting soybean worldwide including in China, Brazil, Argentina, USA and Canada. There are many Quantitative Trait Loci (QTLs) conferring resistance to SCN that have been identified; however, only two are widely used: rhg1 and Rhg4. Overuse of cultivars containing these QTLs/genes can lead to SCN resistance breakdown, necessitating the use of additional strategies. In this manuscript, a literature review is conducted on research related to soybean resistance to SCN. The main goal is to provide a current understanding of the mechanisms of SCN resistance and list the areas of research that could be further explored.

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Section: Identifying Novel Sources Of Resistancementioning

confidence: 88%

A Broad Review of Soybean Research on the Ongoing Race to Overcome Soybean Cyst Nematode

Nissan

Mimee

Cober

et al. 2022

Biology

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“…In the case of Lr34 , resistant and susceptible NILs do not exhibit gene expression differences, and no sequence variation exists within 2 kb of the putative promoter region (Krattinger et al, 2009 ). Despite this restriction, differential gene expression analysis has been successfully used to identify the candidate genes for iron efficiency (Peiffer et al, 2012 ; Atwood et al, 2014 ), bacterial leaf pustule resistance (Kim et al, 2011 ), resistance to soybean aphid (Lee et al, 2017 ), and resistance against cyst nematodes in soybean (Jiang et al, 2021 ). Thus, combined transcriptomic and linkage analyses represent a viable tool for identifying potential gene(s) underpinning QDRL-18 .…”

Section: Discussionmentioning

confidence: 99%

“…Recent studies in cowpea ( Vigna unguiculata (L.)) (Santos et al, 2018 ), cotton ( Gossypium spp.) (Li et al, 2017 ), wild rice ( Oryza rufipogon) (Wang et al, 2017 ), soybean (McCabe et al, 2018 ; Jiang et al, 2021 ), wheat ( Triticum aestivum) (Wang Y. et al, 2021 ), and common bean ( Phaseolus vulgaris L) (Yang et al, 2022 ) have successfully identified the candidate genes for root-knot nematode resistance, fiber length, salt tolerance, brown stem rot resistance, cyst nematode, stripe rust, and bacterial blight, respectively, by coupling linkage mapping with RNA-seq expression analyses. Thus, the integration of mapping and gene expression information may be a promising method for characterizing complex loci such as QDRL-18 .…”

Section: Introductionmentioning

confidence: 99%

Identification of Candidate Genes for a Major Quantitative Disease Resistance Locus From Soybean PI 427105B for Resistance to Phytophthora sojae

Karhoff

Vargas-Garcia²,

Lee³

et al. 2022

Front. Plant Sci.

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Phytophthora root and stem rot is a yield-limiting soybean disease caused by the soil-borne oomycete Phytophthora sojae. Although multiple quantitative disease resistance loci (QDRL) have been identified, most explain <10% of the phenotypic variation (PV). The major QDRL explaining up to 45% of the PV were previously identified on chromosome 18 and represent a valuable source of resistance for soybean breeding programs. Resistance alleles from plant introductions 427105B and 427106 significantly increase yield in disease-prone fields and result in no significant yield difference in fields with less to no disease pressure. In this study, high-resolution mapping reduced the QDRL interval to 3.1 cm, and RNA-seq analysis of near-isogenic lines (NILs) varying at QDRL-18 pinpointed a single gene of interest which was downregulated in inoculated NILs carrying the resistant allele compared to inoculated NILs with the susceptible allele. This gene of interest putatively encodes a serine–threonine kinase (STK) related to the AtCR4 family and may be acting as a susceptibility factor, based on the specific increase of jasmonic acid concentration in inoculated NILs. This work facilitates further functional analyses and marker-assisted breeding efforts by prioritizing candidate genes and narrowing the targeted region for introgression.

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“…RNA-Seq is a powerful tool for transcriptome studies and is especially valuable for the sequence analysis of crops without a reference genome sequence. The large quantity of assembled transcriptomes can be used for gene prediction, gene annotation, gene ontology, gene expression level analysis, and identifying the regulation system of metabolic pathways in plant organisms [30][31][32][33][34]. RNA-Seq has been used for detecting sequence variations (SNPs, SSRs) to develop DNA markers without a reference genome [35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

De Novo Transcriptome Assembly and SNP Discovery for the Development of dCAPS Markers in Oat

et al. 2022

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Cultivated oat (Avena sativa L.) is an important cereal crop that has captured interest worldwide due to its nutritional properties and associated health benefits. Despite this interest, oat has lagged behind other cereal crops in genome studies and the development of DNA markers due to its large and complex genome. RNA-Seq technology has been widely used for transcriptome analysis, functional gene study, and DNA marker development. In this study, we performed the transcriptome sequencing of 10 oat varieties at the seedling stage using the Illumina platform for the development of DNA markers. In total, 31,187,392~41,304,176 trimmed reads (an average of 34,322,925) were generated from 10 oat varieties. All of the trimmed reads of these varieties were assembled and generated, yielding a total of 128,244 assembled unigenes with an average length of 1071.7 bp and N50 of 1752 bp. According to gene ontology (GO) analysis, 30.7% of unigenes were assigned to the “catalytic activity” of the parent term in the molecular function category. Of the 1273 dCAPS markers developed using 491 genotype-specific SNPs, 30 markers exhibiting polymorphism in 28 oat varieties were finally selected. The transcriptome data of oat varieties could be used for functional studies about the seedling stage of oat and information about sequence variations in DNA marker development. These 30 dCAPS markers will be utilized for oat genetic analysis, cultivar identification, and breeders’ rights protection.

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RNA-seq-based identification of potential resistance genes against the soybean cyst nematode (Heterodera glycines) HG Type 1.2.3.5.7 in ‘Dongnong L-10’

Cited by 11 publications

References 28 publications

A Broad Review of Soybean Research on the Ongoing Race to Overcome Soybean Cyst Nematode

A Broad Review of Soybean Research on the Ongoing Race to Overcome Soybean Cyst Nematode

Identification of Candidate Genes for a Major Quantitative Disease Resistance Locus From Soybean PI 427105B for Resistance to Phytophthora sojae

De Novo Transcriptome Assembly and SNP Discovery for the Development of dCAPS Markers in Oat

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