Research Report
Precisely Positioning QTLs for Premature Senescence Resistance in Asparagus Bean Using a High-density SNP Chip 
,
Xirui Yuan1,2 ,
Xinyi Wu1 ,
Ying Wang1 ,
Xiaohua Wu1 ,
Baogen Wang1 ,
Zhongfu Lu1 ,
Guojing Li1 ,
Pei Xu1 
2 College of Horticulture, Northwest Agricultural and Forestry University, Yangling, 712100, China
Author Correspondence author
Molecular Plant Breeding, 2019, Vol. 10, No. 2 doi: 10.5376/mpb.2019.10.0002
Received: 21 Dec., 2018 Accepted: 10 Jan., 2019 Published: 31 Jan., 2019
Huang L.J., Yuan X.R., Wu X.Y., Wang Y., Wu X.H., Wang B.G., Lu Z.F., Li G.J., and Xu P., 2019, Precisely positioning QTLs for premature senescence resistance in asparagus bean using a high-density SNP chip, Molecular Plant Breeding, 10(2): 11-15 (doi: 10.5376/mpb.2019.10.0002)
Premature senescence (PS) is an important adverse agronomic trait of asparagus bean. Since immature pods are the major economic organ for asparagus bean, PS will influence the pod number in late stage which leads to the decline of pod yield and brings economic losses to growers. Using an enlarged recombinant inbred line population (RIL, F6:8) comprising 119 lines from the cross of ZN016 and ZJ282 as materials, the study carried out the quantitative trait loci (QTL) precise positioning of PS resistance traits of asparagus bean based on the high density molecular genetic map with 8,032 SNP loci which was constructed by the 60K high-density SNP chip of cowpea. We positioned the major QTLs for PS resistance of asparagus bean to an about 0.424 cM interval on LG11. Compared with previous results of QTL positioning of the same trait, the coarse positioning results in the early stage of this laboratory were confirmed, and the accuracy of QTL positioning was greatly improved which greatly reduced the distance between the wing markers. This study might provide the basis for molecular marker-assisted breeding and gene cloning against the agronomic trait of PS resistance.
Background
Cowpea (Vigna unguiculata L. Walp.), native to Africa, is an important annual plant of the Leguminosae family. Grown primarily in Asia and Africa respectively, the asparagus bean (V. unguiculata L. Walp. ssp. sesquipedalis) and common cowpea (V. unguiculata L. Walp. ssp. unguiculata) constitute the two main groups of cultivated cowpeas (Timko et al., 2007) in the world. In China and many other East/South-East Asian countries, asparagus bean was grown mainly for vegetable use.
Premature senescence (PS) is an adverse agronomic trait of asparagus bean, which is characterized by leaf yellowing, stem wilting and premature plant death in reproductive growth stage of the plants. Because fresh pods are the major economic organ of asparagus bean, PS usually remarkably affects the final pod yield by reducing pod number per plant. Therefore, overcoming PS is an important objective in cowpea breeding programs to allow for production of more tender pods to increase pod yield. To data, little is known about the genetic architecture of premature senescence in cowpea. Muchero et al. (2011) reported two maturity-related QTLs, Mat-2 and Mat-1, in cowpea. Cui et al. (2007) detected three QTLs for leaf senescence in soybean by using three RIL populations, explaining 5.8% to 13.7% of the phenotypic variation, respectively. In our previous work, a recombinant inbred line (RIL) population was constructed using a PS commercial cultivar ‘ZJ282’ and a non-PS variety ‘ZN016’. Through low-density SSR and SNP marker-based QTL scanning, a major QTL for PS was mapped to the LG11 spanning the interval of 26.8-36.9 cM (Hu, 2011; Xu et al., 2013).
In collaboration with several international partners such as UC Riverside and the International Institute of Tropical Agriculture, we developed the high-density 60 K SNP chip of cowpea with 51,128 SNPs (Muñoz-Amatriaín et al., 2017). Using this chip and an enlarged ‘ZN016 x ZJ282’ RIL, a second generation high-density molecular genetic map of asparagus bean having 8,032 SNP markers was constructed. In this study, the major QTL for PS on LG11 was more precisely mapped by using the above-mentioned mapping population and genetic map, which provides a basis for molecular marker-assisted breeding against PS and gene cloning.
1 Results
1.1 Analysis of PS phenotype in the enlarged RIL population
ZJ282, the male parent of the RIL population, shows serious PS phenotype (score 5), whereas the female parent ZN016 is a landrace showing no PS (score 0). In the four experiments, the PS score varied between 0~5 in the RIL population with a mean value of 3 (Table 1). Except for the 2010 SX experiment, the distributions of the PS score were near normal (Figure 1). In 2009, the trait distributions were slightly biased toward the male parent (PS), whereas in 2010 SX the distribution deviated from a normal distribution due to the environment variation in late growth stage caused by the different sowing time between the two replicates.
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Table 1 PS phenotypes of the parents and in the enlarged ZN016×ZJ282 RIL population Note: (P1, female parent): ‘ZN016’; (P2, male parent): ‘ZJ282’; HN: Haining; SX: Shaoxing |
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Figure 1 Distributions of the PS phenotype in the enlarged ZN016×ZJ282 RIL population |
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1.2 QTL mapping for PS resistance
A major QTL for PS resistance was detected on LG11 with the intervals spanning from 0.424 to 1.739 cM in different experiments, which explained 12% to 32% of the phenotypic variation (Table 2). The QTL peak positions were overlapped between 2009 HN and 2010 HN, and they shared the same flanking makers to define a 0.424 cM interval. The QTL interval lengths in 2009 SX and 2010 SX were 0.424 cM and 1.739 cM, respectively. Combined, this QTL was positioned to an interval no larger than 7.793 cM on LG11 (between the SNPs 2_16920 and 2_48914), and according to the results in 2009 HN and 2010 HN, it was narrowed down to a 0.424 cM-interval (Table 2; Figure 2).
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Table 2 Major QTL information detected in the four trials |
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Figure 2 Positions of the major QTL on LG11 mapped in different experiments Note: LOD score=3; HN: Haining; SX: Shaoxing |
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In addition to detecting the major QTL, 9 minor QTLs were also mapped on LG6 (1 QTL), LG7 (1 QTL), LG8 (6 QTLs), and LG9 (1 QTL), which explained 6.0%, 6.4%, 7.6%-16.4% and 9.8% of the phenotypic variation, respectively (Table 3). Among them, four out of the six QILs were detected in at least two experiments.
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Table 3 Minor QTLs detected in the four trials |
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2 Discussion
Single nucleotide polymorphism (SNP), the star of the third-generation molecular marker, has been widely used in vegetable genomics and genetics research (Xu et al., 2015; Bui et al., 2017), especially in construction of a high density molecular genetic linkage map (Li et al., 2017). SNP markers can also be used to estimate the level of genetic diversity, population structure, and phylogenetic relationships (Xiong et al., 2016). SNP chip technology, based on single nucleotide polymorphisms, has the advantages of being convenient, reproducible, efficient, in high and high accurate.
In the previous study, the number of markers (184 SSR and 191 SNP markers) and the population size (96 RILs) limited the resolution of QTL mapping (Xu et al., 2013). The length of the major QTL was 13.1 cM as opposed to the genome size of cowpea that is approximately 630 Mb (Arumuganathan and Earle, 1991). In this paper, we re-mapped the QTL for PS resistance based on the state-of-the-art high density molecular genetic map which harbors 8,032 SNPs in 697 bins. The marker density in this new map is 21.4 times that of the previous map. Additionally, 119 lines were used for re-mapping, which was a 24% increase of population size as compared to the previous study. These led to a higher precision and accuracy of QTL positioning in our study. Using a similar strategy, Xu et al. (2017) positioned the major QTL Qpl.zaas-3 for pod length to a 1.3 cM-interval on LG3.
In this study, a major QTL was identified on LG11 and nine minor QTLs were detected on LG6, 7, 8 and 9. The current largest interval of the major QTL is 7.793,3 cM, spanning from 28.726 to 36.519 cM. Xu et al. (2013) reported that the marker closest to this major QTL was 1_1103，which was not included in the genetic map used in this study. However, the two neighboring markers to 1_1103 in this study defined an interval from 25.137 to 33.006 cM, which was consistent with the previous result of the QTL location. Compared with the results of Hu (2011), more minor QTLs were identified in this study, demonstrating an improved ability of detecting little-effect QTLs by using the high-density genetic map and enlarged mapping population.
3 Materials and Methods
3.1 Plant materials
The population used for genetic mapping included 119 RILs (F6:8), which were developed from the cross of ‘ZN016’ (P1, female parent) and ‘ZJ282’ (P2, male parent). ‘ZN016’ is a landrace showing no PS, whereas ‘ZJ282’ is a cultivar showing PS.
3.2 Field trials
In 2009 and 2010, 119 RILs were planted in Haining County (HN, 30°32’N, 120°41’E) and Shaoxing County (SX, 29°43’N, 120°14’E), respectively. Each experiment included two replicates. Eight to ten seeds were sowed per line, and after the emergence of seedlings, only 2 uniform seedlings were retained for each line. Two rows of buffer plants (cultivar ‘ZJ106’) were planted to avoid marginal effect. The managements in the two places were similar.
3.3 Trait evaluation and statistic analysis
The phenotypes of PS were scored based on a 0-5 scale (Table 4). Phenotyping of the RIL population in each experiment was performed when the male parent ‘ZJ282’ began to show whole plant symptom of senescence. The phenotypic data was statistically analyzed and normalized using Excel 2010 and SPSS 20.
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Table 4 Scoring criteria for the PS trait |
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3.4 QTL analysis
The phenotypic and SNP genotypic data of the mapping population were analyzed by using QTL IciMapping V4.0 under the composite interval mapping mode. Critical mapping parameters were as follows: step size = 1 cM, PIN = 0.001, LOD threshold = 3.
Authors’ contributions
XRY analyzed the data and wrote the Chinese manuscript, LJH translated it into English. XYW and BGW conceived and performed the experiments. BGW, XHW and ZFL performed the experiments and participated in the result analysis. YW revised the English manuscript. PX and GJL conceived and supervised the study. All authors read and approved the manuscript.
Acknowledgments
This study was partially supported by the Zhejiang Province New Agricultural Variety Breeding Major Science and Technology Special Project (2016C02051-7-3) and the Public Research Project of Zhejiang Province (LGN18C150009).
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