Meta‐analysis and candidate gene mining of low‐phosphorus tolerance in maize

Abstract

Plants with tolerance to low-phosphorus (P) can grow better under low-P conditions, and understanding of genetic mechanisms of low-P tolerance can not only facilitate identifying relevant genes but also help to develop low-P tolerant cultivars. QTL meta-analysis was conducted after a comprehensive review of the reports on QTL mapping for low-P tolerance-related traits in maize. Meta-analysis produced 23 consensus QTL (cQTL), 17 of which located in similar chromosome regions to those previously reported to influence root traits. Meanwhile, candidate gene mining yielded 215 genes, 22 of which located in the cQTL regions. These 22 genes are homologous to 14 functionally characterized genes that were found to participate in plant low-P tolerance, including genes encoding miR399s, Pi transporters and purple acid phosphatases. Four cQTL loci (cQTL2-1, cQTL5-3, cQTL6-2, and cQTL10-2) may play important roles for low-P tolerance because each contains more original QTL and has better consistency across previous reports.Keywords: Candidate gene; consensus QTL; low-phosphorus tolerance; maize; meta-analysis Citation: Zhang H, Uddin MS, Zou C, Xie C, Xu Y, Li WX (2014) Meta-analysis and candidate gene mining of low-phosphorus tolerance in maize.

Advances and Perspectives to Improve the Phosphorus Availability in Cropping Systems for Agroecological Phosphorus Management

“…Modern breeding for P-efficient varieties has focused on root architectural, morphological, and physiological traits (Rose et al, 2013;Zhang et al, 2014b). In spite of some successes (Chin et al, 2011), there have been few applications, due in particular to a poor understanding of physiological processes involved, difficulties in field phenotyping, and little consideration of genotype x environment interaction (GxE) interactions (Bovill et al, 2013).…”

Quantitative trait loci identification and meta-analysis for rice panicle-related traits

“…BioMercator, a genetic map compilation and QTL meta-analysis software program, offers wizards to run analyses and display input and output maps through an accessible graphical user interface (Arcade et al 2004;Sosnowski et al 2012). Recently, BioMercator has been used for QTL meta-analysis in several crops, especially maize and soybean (Griffiths et al 2009;Jin et al 2013;Li et al 2013;Qi et al 2011;Truntzler et al 2010;Zhang et al 2014). Though a large number of QTLs have been detected, there are a few reports on QTL meta-analysis of rice yield-related traits (Ballini et al 2008;Courtois et al 2009;Swamy and Sarla 2011).…”

Mining for low-nitrogen tolerance genes by integrating meta-analysis and large-scale gene expression data from maize

“…Previous studies about stress-tolerant cQTL have identified QTL under dichotomous conditions but have failed to exclude QTL of the same traits detected under other conditions (Hao et al 2010;Li et al 2010c;Liu et al 2012;Semagn et al 2013;Zhang et al 2014). Because plant stress-response mechanisms involve multiple intricate physiological and biochemical pathways, the ensuing phenotypes lack direct associations with the corresponding tolerant QTL.…”

“…As described by Zhang et al (2014), a reliable cQTL can be deduced according to numbers of previously detected case QTL within or near a given region. Thus, cQTL1_2Y (on bin 1.03) was reportedly located in the region from 216.55 to 225.33 cM, and we further narrowed this region (Coque et al 2008;Liu et al 2012).…”