Mapping QTLs Related to Salt Tolerance in Rice at the Young Seedling Stage using 384-plex Single Nucleotide Polymorphism SNP, Marker Sets  

Isaac Kofi Bimpong , Baboucarr Manneh , Raafat El-Namaky , Faty Diaw , Nana Kofi Abaka Amoah , Bakary Sanneh , Kanfany Ghislain , Abdulai Sow , R.K. Singh , Glenn Gregorio , Jean Berchmans Bizimana , M. Wopereis
1. Africa Rice Centre, Sahel Regional Station, B.P 96, Saint Louis, Senegal
2. International Rice Research Institute ?IRRI), DAPO Box 7777, Metro Manila, Philippines
3. Tanzania National Agricultural Research Institute
4. Africa Rice Centre, 01 BP 2031, Cotonou, Benin
Author    Correspondence author
Molecular Plant Breeding, 2014, Vol. 5, No. 9   doi: 10.5376/mpb.2014.05.009
Received: 19 May, 2014    Accepted: 28 May, 2014    Published: 13 Jun., 2014
© 2014 BioPublisher Publishing Platform
This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:

Bimpong et al., Mapping QTLs Related to Salt Tolerance in Rice at the Young Seedling Stage using 384-plex Single Nucleotide Polymorphism SNP, Marker Sets, Molecular Plant Breeding, 2014, Vol.5, No. 9 47-63 (doi: 10.5376/mpb.2014.05.0009)

Abstract

Salinity is one of the most serious factors limiting the productivity of rice crops, with adverse effects on germination, plant vigor and crop yield. A population of 300 F5:6 recombinant inbred lines (RILs), which was derived from a cross between IR29 (indica sensitive to salinity) and Hasawi (Saudi cultivar showing salt tolerance), was evaluated at a young seedling stage under hydroponic conditions at an EC of 12 dsm-1. Such RIL population when fixed can be repeatedly used for investigating QTLs of various phenotypes under different environments. Transgressive segregation was noted for all traits in the RILs; In all 31 RILs (10% of the 300 RILs) had tolerance level similar or better than Hasawi as determined by their standard evaluation system (SES) score of 4 or less, performance under both saline and non-saline conditions for plant height, root length, shoot dry weight and shoot fresh weight; suggesting these RILs can be rated as tolerant to salinity and are been advanced in our breeding program

Quantitative trait loci (QTL) related to salt tolerance were detected using 142 F5 RILs and single nucleotide polymorphisms (SNPs) chip composed of 384 SNP markers for indica x indica background. There were seven significant QTL related to 4 different traits associated to salt tolerance at young seedling stage. They were mapped on chromosomes 1, 2 and 6. The QTL qDW1.1, qDW2.1, qDW2.2 and qDW6.1 co-segregated with shoot dry weight and accounted between 10.6 and 42.3% of its phenotypic variation, while qPH1.1 and qPH1.2 were associated with plant height (explaining between 12.7 and 13.8% of its phenotypic variation), and qF2.1 co-segregated with shoot fresh weight (10.6% of trait variation) was accounted by SNP marker (id2007526). These QTLs had positive additive effects confirming that Hasawi alleles contributed to enhance traits related to salt tolerance at young seedling stage. The SNP markers associated with the QTLs identified in this study could be useful for further marker-aided breeding aiming at developing new rice cultivars for saline-prone agro-ecosystems

Keywords
Africa; Hasawi; Oryza sativa; RILs; SNPs; Salt tolerance; Transgressive segregation; QTLs

Grain yield of rice is increasing at a faster rate in sub-Saharan Africa than the world’s average; between 2007 to 2012, average grain rice yields in sub-Saharan Africa increased about 30% or 108 kg.ha-1.year-1 (AfricaRice, 2011), Despite this grain yield increase, rice productivity continues to be affected by a series of pests blast, bacterial blight, rice yellow mottle virus and stem borers, and abiotic factors drought, flood, salinity, cold and iron toxicity, in this continent. Soil salinity in reclaimed paddy fields is one of the important constraints limiting rice growth and yield. Salt-tolerant cultivars have been seldom selected in Africa. Furthermore, there are not many advanced salt-tolerant breeding lines with useful agronomic characteristics due to the difficulty of transferring tolerant traits into popular rice cultivars. Likewise, Munns and Tester 2008, indicated that the effect of salinity is caused by multigenic traits with complex genetics and mechanisms.

It has also been documented that multi-genes control various salt-tolerant associated traits such as shoot fresh weight, shoot dry weight, shoot length, root length, and shoot Na+/K+ ratio in rice (Akbar et al., 1986; Jones, 1986; Yeo and Flowers, 1986; Flowers et al., 2000; Ashraf, 2004; Masood et al., 2004; Munns and Tester, 2008). In spite of this difficulty, efforts have been made by International Rice Research Institute IRRI, in the Philippines in collaboration with many national institutes to develop and improve rice varieties tolerant to salinity. This has led to the release of varieties such as FL478, IR4630-22-2-5-1-3 (SAL 002), PSBRc 88, IR77644-B-9-3-3-21-15-2-AJY4 and IR83415-B-SDO3-3-AJY3. However most of these varieties were developed with limited number of resistant such as Nona Bokra or Pokkali or varieties derived from these parents such as CSR27 (Negrao et al., 2011), There is the need to broaden the genepool of rice for salinity tolerance. Hasawi is a landrace from eastern Saudi Arabia and characterized by its strong adaptability to soil salinity and drought making it a plausible donor to be used in salinity research.

Research on quantitative trait loci QTL, mapping for salt tolerance in rice has advanced significantly in the last 2 decades (Zhang et al., 1995; Lin et al., 1998; Gong et al., 1999; Flowers et al., 2000; Prasad et al., 2000; Tuan et al., 2000; Koyama et al., 2001; Lang et al., 2001; Masood et al., 2004; Yao et al., 2005; Sabouri and Sabouri, 2009; Ahmadi and Fotokian, 2011; Islam et al., 2011); but only few studies of heterogeneous quality have been conducted (Negrao et al., 2011), Several QTLs have been identified for salinity tolerance in rice using different mapping populations such as RIL, DH or F2:3, ranging from indicaxjaponica originally developed for other purposes, such as IR64×Azucena or Co39×Moroberekan. Most of these QTLs compute indices for plant developments under normal and stress conditions www.Gramene, Some QTLs have been detected repeatedly on chromosomes 1, 4, 6, and 7, whilst none have been found on chromosomes 8 and 11 and very few on chromosomes 2, 3, 5, 9, 10 and 12 (Negrao et al., 2011), QTL studies have led to the conclusion that different loci are involved in the different plant responses under salt stress (Haq et al., 2010).

A large number of QTLs have been detected to concentrate on the segment of short arm on chromosome 1 (Bonilla et al., 2002, Gregorio et al., 2002, Lin et al., 2004; Ren et al., 2005).

More recently, the use of single nucleotide polymorphisms (SNPs), due to their high level of informative content, has led to identifying various QTL in rice.

The advantages of using recombinant inbred lines RILs, for a QTL analysis are well documented. First, multiple selfing processes can increase the number of recombination events (Soller and Beckmann, 1990), which results in a finer mapping of QTLs. More importantly, once RILs are established, in which the genotypes of all lines are fixed as homozygotes, these lines can be repeatedly used for investigating QTLs of various phenotypes under different environments. Thus, the establishment of a comprehensive set of RILs will be a substantial contribution to QTL mapping for salinity tolerance in rice.

The RILs population used in the current study consists of 300 lines using single seed descent until the F5 generation developed at IRRI. This RIL population was derived from a cross between IR29 and Hasawi. IR29 is an IRRI-bred indica line and it is used as a susceptible check in salinity experiments. SNP-facilitated allelic diversity analysis have revealed that Hasawi is an Aus cultivar; suggesting that there may be a possibility of high level of polymorphism in offspring derived by crossing Hasawi with indica cultivars (Thomson et al., 2010a; Platten et al., 2013).

The objectives of our research were to identify and map QTL controlling salt tolerance at early seedling stage in IR29×Hasawi F5 RIL population using 384 SNP chip under hydroponic conditions, and also to select best performing RILs for their further use as breeding materials or for cultivar development.

1 Results
1.1 Trait Analysis and Performance of F5–derived RILs
The descriptive statistics of the qualitative and quantitative traits measured in the F5 derived–RILs are given in Table 1. There was a significant variation for all traits in these RILs; besides we also observed transgressive for all traits (Figure 1~Figure 4).


Table 1 Descriptive statistics for salt-tolerant associated traits evaluated in 300 F5–derived recombinant inbred lines and their parents IR29 susceptible, and Hawasi tolerant, under salines stress S, and non-stress N


Figure 1 Distribution of salt tolerance score (SES), in 300 F5–derived recombinant inbred lines from IR29×Hasawi


Figure 2 Distribution of plant height under saline stress in 300 F5–derived recombinant inbred lines from IR29×Hasawi


Figure 3 Distribution of root length under saline stress in 300 F5–derived recombinant inbred lines from IR29×Hasawi


Figure 4 Distribution of fresh weight under saline stress in 300 F5–derived recombinant inbred lines from IR29×Hasawi


Ranking of F5:6 RILs for salinity damage using SES
. Salinity tolerance was rated as any entry having an SES score of equal to that of the tolerant parent, Hasawi or better than it. The tolerant parent Hasawi had a score of 4 and IR29 had 7, confirming its susceptibility to salinity. Salinity damage scores were given to each RIL according to their plant vigor, leaf chlorosis, necrosis and general physical health. The mean SES score for the RILs was 6 but with a wide range of variation SES score of 3~9 (Table 1; Figure 1), Thirty-o

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