Identification and multiple comparisons of QTL and epistatic interaction conferring high yield under boron and phosphorus deprivation in Brassica napus

Ding, Guangda; Zhao, Zunkang; Wang, Lin; Zhang, Didi; Shi, Lei; Xu, Fangsen

doi:10.1007/s10681-014-1110-8

Cited by 9 publications

(6 citation statements)

References 42 publications

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“…ICIM also facilitated the detection of E-QTLs. Although both methods detected comparable number of M-QTLs across traits in the studied populations, CIM detected slightly more M-QTLs than ICIM, which agrees with results of an earlier study 36 . Three or more M-QTLs were detected by both programs while ICIM detected two or more E-QTLs for each trait in each of the studied populations.…”

Section: Discussionsupporting

confidence: 90%

Seed protein content and its relationships with agronomic traits in pigeonpea is controlled by both main and epistatic effects QTLs

Obala

Saxena

Singh

et al. 2020

Sci Rep

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The genetic architecture of seed protein content (SPC) and its relationships to agronomic traits in pigeonpea is poorly understood. Accordingly, five F 2 populations segregating for SPC and four agronomic traits (seed weight (SW), seed yield (SY), growth habit (GH) and days to first flowering (DFF)) were phenotyped and genotyped using genotyping-by-sequencing approach. Five high-density population-specific genetic maps were constructed with an average inter-marker distance of 1.6 to 3.5 cM, and subsequently, integrated into a consensus map with average marker spacing of 1.6 cM. Based on analysis of phenotyping data and genotyping data, 192 main effect QTLs (M-QTLs) with phenotypic variation explained (PVE) of 0.7 to 91.3% were detected for the five traits across the five populations. Major effect (PVE ≥ 10%) M-QTLs included 14 M-QTLs for SPC, 16 M-QTLs for SW, 17 M-QTLs for SY, 19 M-QTLs for GH and 24 M-QTLs for DFF. Also, 573 epistatic QTLs (E-QTLs) were detected with PVE ranging from 6.3 to 99.4% across traits and populations. Colocalization of M-QTLs and E-QTLs explained the genetic basis of the significant (P < 0.05) correlations of SPC with SW, SY, DFF and GH. The nature of genetic architecture of SPC and its relationship with agronomic traits suggest that genomics-assisted breeding targeting genome-wide variations would be effective for the simultaneous improvement of SPC and other important traits.

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Section: Discussionsupporting

confidence: 90%

Seed protein content and its relationships with agronomic traits in pigeonpea is controlled by both main and epistatic effects QTLs

Obala

Saxena

Singh

et al. 2020

Sci Rep

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“…The epistatic effect of QTL was analyzed by ICIM-EPI in BIP model of QTL IciMapping v3.3 (P value \0.0005; LOD[5.0). This method has been described in detail by Li et al (2008), and applied to epistatic QTL mapping for amounts of essential traits (Ding et al 2014;Wang et al 2012a, b). The genes within QTLs were annotated and analyzed via the database of Phytozome v9.1 (www.phytozome.net) and NCBI (www.ncbi.nlm.nih.gov).…”

Section: Construction Of the Genetic Map And Data Analysismentioning

confidence: 99%

Analysis of additive and epistatic quantitative trait loci underlying fatty acid concentrations in soybean seeds across multiple environments

Fan

et al. 2015

Euphytica

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Soybean is one of the most important oilseed crops in the world. The soybean oil contains various fatty acids. Their concentrations determine the quality and nutritional value of soybean oil. On the other hand, quantitative trait loci (QTL) mapping for the concentrations of soybean predominant fatty acids could provide the genetic basis for soybean fatty acid composition. In this study, a soybean genetic linkage map was constructed based on 161 polymorphic SSR markers in recombinant inbred lines (RILs) derived from a cross of cv. Luheidou2 9 Nanhuizao. By using this map, 35 additive QTLs underlying individual fatty acid concentrations were identified in single environment, while 17 additive QTLs were identified underlying specific fatty acids across multiple environments or underlying multiple fatty acids. Fifteen of the 52 loci were found to be novel loci, explaining 5-24 % of phenotypic variation. Moreover, 25 epistatic QTLs were identified and explained a high phenotypic variation for the fatty acid concentrations, suggesting an essential role of epistatic effect for fatty acid concentrations. The identification of additive and epistatic QTLs suggested a complex network for soybean fatty acid concentrations, and will facilitate the understanding for fatty acid accumulation. Keywords Soybean Á Fatty acid Á Quantitative trait locus (QTL) Á QTL interaction Shengxu Fan, Bin Li and Fukuan Yu have contributed equally to this work.

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“…Understanding the genetic architecture of SNPP is the first step towards its improvement. During the past decade, nearly ten linkage mapping studies 2 12 13 14 15 16 17 18 19 20 and one association analysis study 21 involving the SNPP of rapeseed have been reported. However, the genetic architecture of SNPP has remained fragmented and the underlying candidate gene(s) have remained unknown because these detected QTLs had not been integrated and the physical map was unavailable.…”

mentioning

confidence: 99%

Genetic architecture and mechanism of seed number per pod in rapeseed: elucidated through linkage and near-isogenic line analysis

Yang

Shi

Wang

et al. 2016

Sci Rep

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Seed number per pod (SNPP) is one of the major yield components and breeding targets in rapeseed that shows great variation and is invaluable for genetic improvement. To elucidate the genetic architecture and uncover the mechanism of SNPP, we identified five quantitative trait loci (QTLs) using the BnaZNRIL population, which were integrated with those of previous studies by physical map to demonstrate a complex and relatively complete genetic architecture of SNPP. A major QTL, qSN.A6, was successfully fine-mapped from 1910 to 267 kb using near-isogenic line (NIL). In addition, qSN.A6 exhibited an antagonistic pleiotropy on seed weight (SW), which is caused by a physiological interaction in which SNPP acts “upstream” of SW. Because the negative effect of qSN.A6 on SW cannot fully counteract its positive effect on SNPP, it also enhanced the final yield (17.4%), indicating its great potential for utilization in breeding. The following genetic and cytological experiments further confirmed that the different rate of ovule abortion was responsible for the ~5 seed difference between Zhongshuang11 and NIL-qSN.A6. This systematic approach to dissecting the comprehensive genetic architecture of SNPP and characterizing the underlying mechanism has advanced the understanding of SNPP and will facilitate the development of high-yield cultivars.

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Identification and multiple comparisons of QTL and epistatic interaction conferring high yield under boron and phosphorus deprivation in Brassica napus

Cited by 9 publications

References 42 publications

Seed protein content and its relationships with agronomic traits in pigeonpea is controlled by both main and epistatic effects QTLs

Seed protein content and its relationships with agronomic traits in pigeonpea is controlled by both main and epistatic effects QTLs

Analysis of additive and epistatic quantitative trait loci underlying fatty acid concentrations in soybean seeds across multiple environments

Genetic architecture and mechanism of seed number per pod in rapeseed: elucidated through linkage and near-isogenic line analysis

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