Mei Yuan

Dr. Mei Yuan

orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 January 2012 in BMC Plant Biology
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Journal Article
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HWHui Wang
Hui Wang
VPVarma Penmetsa
Varma Penmetsa
MYMei Yuan
Mei Yuan
LGLimin Gong
Limin Gong
YZYongli Zhao
Yongli Zhao
GHGuohao He
Guohao He
Background: Cultivated peanut (Arachis hypogaeaL.) is an important crop worldwide, valued for its edible oil and digestible protein. It has a very narrow genetic base that may well derive from a relatively recent single polyploidization event. Accordingly molecular markers have low levels of polymorphism and the number of polymorphic molecular markers available for cultivated peanut is still limiting.Results: Here, we report a large set of BAC-end sequences (BES), use them for developing SSR (BES-SSR) markers, and apply them in genetic linkage mapping. The majority of BESs had no detectable homology to known genes (49.5%) followed by sequences with similarity to known genes (44.3%), and miscellaneous sequences (6.2%) such as transposable element, retroelement, and organelle sequences. A total of 1,424 SSRs were identified from 36,435 BESs. Among these identified SSRs, dinucleotide (47.4%) and trinucleotide (37.1%) SSRs were predominant. The new set of 1,152 SSRs as well as about 4,000 published or unpublished SSRs were screened against two parents of a mapping population, generating 385 polymorphic loci. A genetic linkage map was constructed, consisting of 318 loci onto 21 linkage groups and covering a total of 1,674.4 cM, with an average distance of 5.3 cM between adjacent loci. Two markers related to resistance gene homologs (RGH) were mapped to two different groups, thus anchoring 1 RGH-BAC contig and 1 singleton.Conclusions: The SSRs mined from BESs will be of use in further molecular analysis of the peanut genome, providing a novel set of markers, genetically anchoring BAC clones, and incorporating gene sequences into a linkage map. This will aid in the identification of markers linked to genes of interest and map-based cloning.

26 May 2019 in Plant Biotechnology Journal
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Journal Article
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YZYuhan Zhao
Yuhan Zhao
JMJunjie Ma
Junjie Ma
MLMing Li
Ming Li
LDLi Deng
Li Deng
GLGuanghui Li
Guanghui Li
XWXingjun Wang
Xingjun Wang
Summary: Peanut (Arachis hypogaea. L) is an important oil crop worldwide. The common testa colours of peanut varieties are pink or red. But the peanut varieties with dark purple testa have been focused in recent years due to the potential high levels of anthocyanin, an added nutritional value of antioxidant. However, the genetic mechanism regulating testa colour of peanut is unknown. In this study, we found that the purple testa was decided by the female parent and controlled by a single major gene named AhTc1. To identify the candidate gene controlling peanut purple testa, whole‐genome resequencing‐based approach (QTL‐seq) was applied, and a total of 260.9 Gb of data were generated from the parental and bulked lines. SNP index analysis indicated that AhTc1 located in a 4.7 Mb region in chromosome A10, which was confirmed by bulked segregant RNA sequencing (BSR) analysis in three segregation populations derived from the crosses between pink and purple testa varieties. Allele‐specific markers were developed and demonstrated that the marker pTesta1089 was closely linked with purple testa. Further, AhTc1 encoding a R2R3‐MYB gene was positional cloned. The expression of AhTc1 was significantly up‐regulated in the purple testa parent YH29. Overexpression of AhTc1 in transgenic tobacco plants led to purple colour of leaves, flowers, pods and seeds. In conclusion, AhTc1, encoding a R2R3‐MYB transcription factor and conferring peanut purple testa, was identified, which will be useful for peanut molecular breeding selection for cultivars with purple testa colour for potential increased nutritional value to consumers.

30 December 2020 in Genes
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Journal Article
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Manish K. PandeyManish K. Pandey
Manish K. Pandey
SGSunil S. Gangurde
Sunil S. Gangurde
Vinay SharmaVinay Sharma
Vinay Sharma
Santosh PattanashettiSantosh Pattanashetti
Santosh Pattanashetti
GNGopalakrishna K. Naidu
Gopalakrishna K. Naidu
Rajeev VarshneyRajeev Varshney
Rajeev Varshney
A deep understanding of the genetic control of drought tolerance and iron deficiency tolerance is essential to hasten the process of developing improved varieties with higher tolerance through genomics-assisted breeding. In this context, an improved genetic map with 1205 loci was developed spanning 2598.3 cM with an average 2.2 cM distance between loci in the recombinant inbred line (TAG 24 × ICGV 86031) population using high-density 58K single nucleotide polymorphism (SNP) “Axiom_Arachis” array. Quantitative trait locus (QTL) analysis was performed using extensive phenotyping data generated for 20 drought tolerance- and two iron deficiency tolerance-related traits from eight seasons (2004–2015) at two locations in India, one in Niger, and one in Senegal. The genome-wide QTL discovery analysis identified 19 major main-effect QTLs with 10.0–33.9% phenotypic variation explained (PVE) for drought tolerance- and iron deficiency tolerance- related traits. Major main-effect QTLs were detected for haulm weight (20.1% PVE), SCMR (soil plant analytical development (SPAD) chlorophyll meter reading, 22.4% PVE), and visual chlorosis rate (33.9% PVE). Several important candidate genes encoding glycosyl hydrolases; malate dehydrogenases; microtubule-associated proteins; and transcription factors such as MADS-box, basic helix-loop-helix (bHLH), NAM, ATAF, and CUC (NAC), and myeloblastosis (MYB) were identified underlying these QTL regions. The putative function of these genes indicated their possible involvement in plant growth, development of seed and pod, and photosynthesis under drought or iron deficiency conditions in groundnut. These genomic regions and candidate genes, after validation, may be useful to develop molecular markers for deploying genomics-assisted breeding for enhancing groundnut yield under drought stress and iron-deficient soil conditions.

28 March 2022 in BMC Genomics
Verified
Journal Article
Open access
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PXPing Xu
Ping Xu
HLHui Li
Hui Li
XWXiaohua Wang
Xiaohua Wang
GZGe Zhao
Ge Zhao
XLXiaofei Lu
Xiaofei Lu
ZLZhenning Liu
Zhenning Liu
Background: Peanut is the most essential oil and food crop globally due to its high oil and protein content. Root-knot nematode infects peanut roots, causing poor development and severely limiting peanut yields worldwide. The discovery of peanut genome identified a considerable number of genetic loci controlling the peanut root-knot nematode; however, the molecular mechanism of root-knot nematode remains unknown. Results: The heterogeneous response to root-knot nematode stress in peanut roots was identified using whole-transcriptome RNA-seq. A total of 430 mRNAs, 111 miRNAs, 4453 lncRNAs, and 123 circRNAs were found to have differential expression between infected and non-infected peanuts. The expression profiles of the lncRNA/circRNA-miRNA-mRNA network were developed to understand the potential pathways that lead to root-knot nematodes in peanut roots. During root-knot nematodes stress, a total of 10 lncRNAs, 4 circRNAs, 5 miRNAs, and 13 mRNAs can create competing endogenous RNA and participate in the oxidation–reduction process as well as other biological metabolism processes in peanuts. The findings will highlight the role of peanut ceRNAs in response to root-knot nematodes. Conclusion: The GO classification and KEGG pathway enrichment study of core regulatory networks revealed that ceRNAs are involved in oxidation–reduction, peroxidase activity, lignin synthesis in the xylem, and flavonoid synthesis. Overall, these findings may help researchers better understand the role of non-coding RNAs in response to root-knot nematodes.

23 June 2018 in Plant Molecular Biology Reporter
Verified
Journal Article
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XWXiaohua Wang
Xiaohua Wang
PXPing Xu
Ping Xu
LYLiang Yin
Liang Yin
YRYan Ren
Yan Ren
SLShuangling Li
Shuangling Li
MYMei Yuan
Mei Yuan
Peanut (Arachis hypogaea), a major source of vegetable oil in many Asian countries, has become an integral part of human diet globally due to its high nutritional properties and option to consume in different forms. In order to meet the demand of vegetable oil, many peanut breeding programs of China have intensified their efforts in increasing oil content in newly bred varieties for reducing the import of edible oils in China. In this context, transcriptome sequencing data generated on 49 peanut cultivars were analyzed to identify candidate genes and develop molecular markers for seed oil content across multiple environments. Transcriptome analysis identified 5458 differentially expressed genes (DEGs) including 2243 positive DEGs and 3215 negative DEGs involved in oil synthesis process. Genome-wide association study identified 48 significant insertion/deletion (InDel) markers associated with seed oil content across five environments. A comparative genomics and transcriptomics analysis detected a total of 147 common gene clusters located in 17 chromosomes. Interestingly, an InDel cluster associated with seed oil content on A03 chromosome was detected in three different environments. Candidate genes identified on A03 form a haplotype, in which variable alleles were found to be different in oil content in an independent population. This locus is important for understanding the genetic control of peanut oil content and may be useful for marker-assisted selection in peanut breeding programs.

16 May 2025 in BMC Plant Biology
Verified
Journal Article
Open access
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JXJing Xu
Jing Xu
XJXiao Jiang
Xiao Jiang
XYXiangzhen Yin
Xiangzhen Yin
XZXuhong Zhao
Xuhong Zhao
NCNa Chen
Na Chen
XCXiaoyuan Chi
Xiaoyuan Chi
The cultivated peanut, Arachis hypogaea L., is a critical oil and food crop worldwide. Improving seed oil quality in peanut has long been an aim of breeders. However, our knowledge of the genetic basis of selecting for seed nutritional traits is limited. Based on AhFAD2A and AhFAD2B, scientists have now developed higher oleic acid (80–84%) in peanut. Decoding the genetic makeup behind natural variation in kernel oil and fatty acid concentrations is crucial for molecular breeding-based nutrient quantity and quality manipulation. Herein, we recognized 87 quantitative trait loci (QTLs) in 45 genomic regions for the concentrations of oil, oleic acid, and linoleic acid, as well as the oleic acid to linoleic acid (O/L) ratio via a genome-wide association study (GWAS) involving 499 peanut accessions. Eight QTLs explained more than 15% of the phenotypic variation in peanut accessions. Among the 45 potential genes significantly related to the four traits, only three genes displayed annotation to the fatty acid pathway. Furthermore, on the basis of pleiotropism or linkage data belonging to the identified singular QTLs, we generated a trait-locus axis to better elucidate the genetic background behind the observed oil and fatty acid concentration association. Expression analysis indicated that arahy.AV6GAN and arahy.NNA8KD have higher expressions in the seeds. This natural population consisting of 499 peanut accessions combined with high-density SNPs will provide a better choice for identifying peanut QTLs/genes in the future. Together, our results provide strong evidence for the genetic mechanism behind oil biosynthesis in peanut, facilitating future advances in multiple fatty acid component generation via pyramiding of desirable QTLs.