Identification of quantitative trait loci with main and epistatic effects for plant architecture traits in Upland cotton (Gossypium hirsutum L.)

Abstract

Plant architecture is important for cotton cultivation and breeding. In this study, two mapping generations/populations F 2 and F 2:3 in Upland cotton (Gossypium hirsutum L.), derived from 'Baimian1' and TM-1, were used to identify quantitative trait loci (QTLs) for 10 plant architecture traits. A total of 55 main-effect QTLs (M-QTLs) were detected. Four common M-QTLs, qTFB-10(F 2 /F 2:3 ) for total fruit branches, qFBL-26b(F 2 )/qFBL-26(F 2:3 ) for fruit branch length, qFBA-5(F 2 /F 2:3 ) for fruit branch angle and qFBN-26b(F 2 )/qFBN-26(F 2:3 ) for fruit branch nodes, were found. The synergistic alleles and the negative alleles can be utilized in cotton plant architecture breeding programmes according to specific breeding objectives. Altogether 54 pairs of epistatic QTLs (E-QTLs) exhibiting the interactions of additive-by-additive (AA), additive-by-dominant (AD), dominant-by-additive (DA) and dominant-by-dominant (DD) were detected. The epistasis appeared to be an important contributor to genetic variation in cotton plant architecture traits. Therefore, the identified markers associated with E-QTLs as well as M-QTLs will be of importance in future breeding programmes to develop cotton cultivars exhibiting desirable plant architecture. Key words: cottonplant architecture traitsquantitative trait locusmain-effect QTLepistatic QTL PH, two for FBL and three for ratio of PH to FBL in a recombinant inbred lines (RILs) population in Upland cotton (Gossypium hirsutum). Wang et al. (2006) identified three QTLs for FBL and one for ratio of PH to FBL in another RIL population in G. hirsutum. Song and Zhang (2009) detected 26 QTLs dispersed over 15 chromosomes in an interspecific population between G. hirsutum and Gossypium barbadense for six plant architecture traits: first fruiting branch position, stem leaf size, PH, SIL, FBA and FBIL. Li et al. (2013) identified five QTLs for PH, 10 for SNL, six for SIL, nine for TFB, three for EFB, eight for FBL, eight for FBN, eight for FBIL, 10 for TFN and six for FBA in two F 2:3 Upland cotton populations. Although there are a few reports applying molecular marker techniques to detect QTLs for cotton plant architecture traits, reliable QTLs *Cheng-Qi Li and Li Song contributed equally to this work.

Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications

“…Different strategies have been implemented through quantitative genetics models, quantitative trait loci (QTL) or mutation-QTL experiments (Mackay, 2014), but there is still no consensus on its importance. For plants, depending on the population and trait considered, some studies have shown that epistasis can significantly contribute to total genetic variance, for example, in maize (Dudley and Johnson, 2009), rice (Luo et al, 2009) or cotton (Li et al, 2014), while also improving the prediction accuracy (Dudley and Johnson, 2009;Hu et al, 2011). Meanwhile, other studies have shown that epistasis has a little impact regarding the genetic architecture of some traits in maize (Buckler et al, 2009) or in the prediction accuracy (Lorenzana and Bernardo, 2009).…”

Dynamic QTL mapping for plant height in Upland cotton (Gossypium hirsutum)

“…Five significant main‐effect QTL for plant height were detected in Chr.2/Chr.1, Chr.14 and Chr.26, respectively, using RIL population (Li et al. ). The main‐effect QTL qPH‐D2‐1, qPH‐D6‐1, qPH‐D8‐2 and qPH‐A9‐1 were repeatedly detected across multiple environments using two immortalized populations of ‘CRI12’ × ‘J8891’ in G. hirsutum (Liu et al.…”

Quantitative trait locus analysis of boll-related traits in an intraspecific population of Gossypium hirsutum

“…Subsequently, several intraspecific genetic linkage maps were constructed for G. hirsutum (Lin et al 2009;Ulloa and Meredith 2000;Ulloa et al 2002Ulloa et al , 2005Zhang et al 2005Zhang et al , 2009, which contain 73-604 loci. Using these maps, the precise locations of many QTLs have been determined Guo et al 2006;Li et al 2014;Liu et al 2012;Ning et al 2014;Paterson et al 2003;Qin et al 2008Qin et al , 2009Shao et al 2014;Shen et al 2005Shen et al , 2007Sun et al 2012;Ulloa and Meredith 2000;Ulloa et al 2005;Wang et al 2006Wang et al , 2007Wu et al 2009;Zhang et al 2005Zhang et al , 2009Zhang et al , 2010Zhang et al , 2012a. For fiber quality, for example, Qin et al (2009) discovered eight QTLs for fiber strength (FS), micronaire (MIC) and fiber elongation (FE) simultaneously in two populations.…”

“…QTL mapping is increasingly used to explore the role of epistasis in the genetic basis of complex quantitative traits Mohan et al 2009). In cotton, QTL mapping analysis of epistatic effects has only been performed to examine a few plant architectural traits in intraspecific populations (Wang et al 2006;Li et al 2014). Wang et al (2006) identified three epistatic QTLs for plant height (PH), three for fruit branch length (FBL) and three for fruit branch number (FBN).…”

“…Wang et al (2006) identified three epistatic QTLs for plant height (PH), three for fruit branch length (FBL) and three for fruit branch number (FBN). Li et al (2014) detected a total of 54 pairs of epistatic QTLs (E-QTLs) for ten plant architecture traits, which exhibit additive-byadditive (AA), additive-by-dominant (AD), dominantby-additive (DA) and dominant-by-dominant (DD) interactions, including five for PH, seven for FBL, eight for FBN and so on.…”