Dataset Information

Identification of genomic regions and diagnostic markers for resistance to aflatoxin contamination in peanut (Arachis hypogaea L.).

ABSTRACT:

Background

Aflatoxin contamination caused by Aspergillus flavus is a major constraint to peanut industry worldwide due to its toxicological effects to human and animals. Developing peanut varieties with resistance to seed infection and/or aflatoxin accumulation is the most effective and economic strategy for reducing aflatoxin risk in food chain. Breeding for resistance to aflatoxin in peanut is a challenging task for breeders because the genetic basis is still poorly understood. To identify the quantitative trait loci (QTLs) for resistance to aflatoxin contamination in peanut, a recombinant inbred line (RIL) population was developed from crossing Zhonghua 10 (susceptible) with ICG 12625 (resistant). The percent seed infection index (PSII), the contents of aflatoxin B₁ (AFB₁) and aflatoxin B₂ (AFB₂) of RILs were evaluated by a laboratory kernel inoculation assay.

Results

Two QTLs were identified for PSII including one major QTL with 11.32-13.00% phenotypic variance explained (PVE). A total of 12 QTLs for aflatoxin accumulation were detected by unconditional analysis, and four of them (qAFB1A07 and qAFB1B06.1 for AFB₁, qAFB2A07 and qAFB2B06 for AFB₂) exhibited major and stable effects across multiple environments with 9.32-21.02% PVE. Furthermore, not only qAFB1A07 and qAFB2A07 were co-localized in the same genetic interval on LG A07, but qAFB1B06.1 was also co-localized with qAFB2B06 on LG B06. Conditional QTL mapping also confirmed that there was a strong interaction between resistance to AFB₁ and AFB₂ accumulation. Genotyping of RILs revealed that qAFB1A07 and qAFB1B06.1 interacted additively to improve the resistance to both AFB₁ and AFB₂ accumulation. Additionally, validation of the two markers was performed in diversified germplasm collection and four accessions with resistance to aflatoxin accumulation were identified.

Conclusions

Single major QTL for resistance to PSII and two important co-localized intervals associated with major QTLs for resistance to AFB₁ and AFB₂. Combination of these intervals could improve the resistance to aflatoxin accumulation in peanut. SSR markers linked to these intervals were identified and validated. The identified QTLs and associated markers exhibit potential to be applied in improvement of resistance to aflatoxin contamination.

SUBMITTER: Yu B

PROVIDER: S-EPMC6417274 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Publications

Identification of genomic regions and diagnostic markers for resistance to aflatoxin contamination in peanut (Arachis hypogaea L.).

Yu Bolun B Huai Dongxin D Huang Li L Kang Yanping Y Ren Xiaoping X Chen Yuning Y Zhou Xiaojing X Luo Huaiyong H Liu Nian N Chen Weigang W Lei Yong Y Pandey Manish K MK Sudini Hari H Varshney Rajeev K RK Liao Boshou B Jiang Huifang H

BMC genetics 20190312 1

<h4>Background</h4>Aflatoxin contamination caused by Aspergillus flavus is a major constraint to peanut industry worldwide due to its toxicological effects to human and animals. Developing peanut varieties with resistance to seed infection and/or aflatoxin accumulation is the most effective and economic strategy for reducing aflatoxin risk in food chain. Breeding for resistance to aflatoxin in peanut is a challenging task for breeders because the genetic basis is still poorly understood. To iden ...[more]

PMID: 30866805

Similar Datasets

Project description:BACKGROUND: Pre-harvest infection of peanuts by Aspergillus flavus and subsequent aflatoxin contamination is one of the food safety factors that most severely impair peanut productivity and human and animal health, especially in arid and semi-arid tropical areas. Some peanut cultivars with natural pre-harvest resistance to aflatoxin contamination have been identified through field screening. However, little is known about the resistance mechanism, which has slowed the incorporation of resistance into cultivars with commercially acceptable genetic background. Therefore, it is necessary to identify resistance-associated proteins, and then to recognize candidate resistance genes potentially underlying the resistance mechanism. RESULTS: The objective of this study was to identify resistance-associated proteins in response to A. flavus infection under drought stress using two-dimensional electrophoresis with mass spectrometry. To identify proteins involved in the resistance to pre-harvest aflatoxin contamination, we compared the differential expression profiles of seed proteins between a resistant cultivar (YJ-1) and a susceptible cultivar (Yueyou 7) under well-watered condition, drought stress, and A. flavus infection with drought stress. A total of 29 spots showed differential expression between resistant and susceptible cultivars in response to A. flavus attack under drought stress. Among these spots, 12 protein spots that consistently exhibited an altered expression were screened by Image Master 5.0 software and successfully identified by MALDI-TOF MS. Five protein spots, including Oso7g0179400, PII protein, CDK1, Oxalate oxidase, SAP domain-containing protein, were uniquely expressed in the resistant cultivar. Six protein spots including low molecular weight heat shock protein precursor, RIO kinase, L-ascorbate peroxidase, iso-Ara h3, 50 S ribosomal protein L22 and putative 30 S ribosomal S9 were significantly up-regulated in the resistant cultivar challenged by A. flavus under drought stress. A significant decrease or down regulation of trypsin inhibitor caused by A. flavus in the resistant cultivar was also observed. In addition, variations in protein expression patterns for resistant and susceptible cultivars were further validated by real time RT-PCR analysis. CONCLUSION: In summary, this study provides new insights into understanding of the molecular mechanism of resistance to pre-harvest aflatoxin contamination in peanut, and will help to develop peanut varieties with resistance to pre-harvested aflatoxin contamination.

Project description:BACKGROUND:Microsatellites, or simple sequence repeats (SSRs), represent important DNA variations that are widely distributed across the entire plant genome and can be used to develop SSR markers, which can then be used to conduct genetic analyses and molecular breeding. Cultivated peanut (A. hypogaea L.), an important oil crop worldwide, is an allotetraploid (AABB, 2n = 4× = 40) plant species. Because of its complex genome, genomic marker development has been very challenging. However, sequencing of cultivated peanut genome allowed us to develop genomic markers and construct a high-density physical map. RESULTS:A total of 8,329,496 SSRs were identified, including 3,772,653, 4,414,961, and 141,882 SSRs that were distributed in subgenome A, B, and nine scaffolds, respectively. Based on the flanking sequences of the identified SSRs, a total of 973,984 newly developed SSR markers were developed in subgenome A (462,267), B (489,394), and nine scaffolds (22,323), with an average density of 392.45 markers per Mb. In silico PCR evaluation showed that an average of 88.32% of the SSR markers generated only one in silico-specific product in two tetraploid A. hypogaea varieties, Tifrunner and Shitouqi. A total of 39,599 common SSR markers were identified among the two A. hypogaea varieties and two progenitors, A. duranensis and A. ipaensis. Additionally, an amplification effectiveness of 44.15% was observed by real PCR validation. Moreover, a total of 1276 public SSR loci were integrated with the newly developed SSR markers. Finally, a previously known leaf spot quantitative trait locus (QTL), qLLS_T13_A05_7, was determined to be in a 1.448-Mb region on chromosome A05. In this region, a total of 819 newly developed SSR markers were located and 108 candidate genes were detected. CONCLUSIONS:The availability of these newly developed and public SSR markers both provide a large number of molecular markers that could potentially be used to enhance the process of trait genetic analyses and improve molecular breeding strategies for cultivated peanut.

Dataset Information

Identification of genomic regions and diagnostic markers for resistance to aflatoxin contamination in peanut (Arachis hypogaea L.).

Background

Results

Conclusions

Publications

Identification of genomic regions and diagnostic markers for resistance to aflatoxin contamination in peanut (Arachis hypogaea L.).

Similar Datasets

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