Open Access Maydica 56-1707 Original Paper RECEIVED 25/03/2011 Natural genetic variation for root traits among diversity lines of maize (Zea Mays L.) Lakshmi Praba Manavalan, Theresa Musket, Henry T Nguyen* Division of Plant Sciences, University of Missouri, Columbia, Missouri, 65211, USA *Corresponding author: E-mail: nguyenhenry@missouri.edu Keywords: maize, diversity lines, root length, leaf area, correlation Introduction Maize (Z. mays L.) is the third most important food grain for humankind after rice and wheat. Maize is mostly grown under rain-fed conditions and among the cereals, it is the second most susceptible to drought next to rice. Constitutive variation for root traits is an important adaptation under drought prone conditions. The objective of this study is to screen the twenty five diverse parental lines used in the maize nested association mapping panel along with the common parental line, B73, for constitutive root traits (including rooting depth and root biomass) and shoot traits. All the lines were grown with five replications in 72 cm deep pots containing a turface:sand mix- ture (2:1 v/v) for 30 days under well-watered conditions in a temperature and humidity controlled green house. Significant variation existed among the diverse lines for root length, root biomass, shoot length, and leaf area. The average root length ranged from 17.5 to 106 cm. The genotypes with a deep root system also recorded greater root biomass and leaf area. The natural genetic variation exhibited by these lines could be exploited to identify potential quantitative trait loci controlling root architecture. Using the nested association mapping populations that were developed from these diverse lines, would allow for in-depth analysis and fine-mapping of prospective candidate genes for root architecture in maize. Abstract The natural genetic variation for root traits es- pecially rooting depth and distribution is essential for plants to adapt to adverse soil conditions in- cluding water deficit, flooding tolerance and nu- trient acquisition. Considerable variation for root architecture exists among and between crop spe- cies, allowing for soil exploration in dynamic soil conditions (Fitter, 2002). In any given year, approx- imately 20-25% of global maize area is affected by drought (Banziger and Araus, 2007). The value of root traits in maize for adverse abiotic stress conditions has been well documented (Sharp and Davies, 1985; Schroder et al, 1996; Richner et al, 1997; Zhu et al, 2007; Hochholdinger and Tu- berosa, 2009; Hund, 2010; Zaidi et al, 2010). An inverse relationship between rooting depth and available soil water was reported in maize under field conditions (Dwyer et al, 1988). However, due to the difficulties in extracting intact root system from soil, time and manpower constraints, it is not easy to screen large numbers of germplasm un- der field conditions to capture the natural genetic variation for root traits. In addition, as plants grow older, the complexity of their root system increas- es (Iyer-Pascuzzi et al, 2010). Identification of quantitative trait loci (QTL) is the first step towards understanding genetic com- ponents contributing to root development. In most crop plants, QTL studies used a parent with less breeding value to magnify the phenotypic variation for traits of interest. However, this limited the util- ity of the detected QTLs in the Marker Assisted Breeding program (Tsonev et al, 2009). In addition, identification of the gene(s) underlying a specific QTL after the initial genetic mapping (linkage map- ping) is not possible due to the poor resolution of the analysis itself (Salvi and Tuberosa, 2005). The QTL supporting interval mapped by primary analy- sis normally range from 10-30 cM which on an av- erage correspond to 2.1 Mb genomic region that constitutes around 310 genes in maize (Salvi and Tuberosa, 2005). Alternatively, QTLs can be de- tected through association mapping based on link- age disequilibrium (Yu and Buckler, 2006). Howev- er association mapping is powerful only when the relevant alleles are present in high frequency and it does not detect rare alleles with good confidence, unless their effect is very large (Rafalski, 2010). To overcome the difficulties associated with bi-pa- rental linkage mapping and association mapping, Mcmullen et al (2009) combined the advantages of both approaches by devising a nested association mapping (NAM) approach in maize. This NAM pop- ulation is based on 25 diversity inbred lines which could be useful to identify genetic architecture of complex traits (Yu et al, 2008). With the availability of this highly valuable NAM population resource, rapid identification of QTL underlying root morphology would be achieved in less time, provided the root morphology of the parental lines is understood. The objective of this