Mapping quantitative trait loci (QTLs) for fatty acid composition in an interspecific cross of oil palm

• Main Authors: Singh, Rajinder, Tan, Soon Guan, Panandam, Jothi Malar, Abdul Rahman, Rahimah, Ooi, Leslie Cheng Li, Low, Leslie Eng Ti, Sharma, Mukesh, Jansen, Johannes, Cheah, Suan Choo
• Format: Article
• Language: English
• Published: BioMed Central 2009
• Online Access: http://psasir.upm.edu.my/id/eprint/5590/1/Mapping_quantitative_trait_loci.pdf; http://psasir.upm.edu.my/id/eprint/5590/; https://bmcplantbiol.biomedcentral.com/articles/10.1186/1471-2229-9-114

Background: Marker Assisted Selection (MAS) is well suited to a perennial crop like oil palm, in which the economic products are not produced until several years after planting. The use of DNA markers for selection in such crops can greatly reduce the number of breeding cycles needed. With the use of DNA markers, informed decisions can be made at the nursery stage, regarding which individuals should be retained as breeding stock, which are satisfactory for agricultural production, and which should be culled. The trait associated with oil quality, measured in terms of its fatty acid composition, is an important agronomic trait that can eventually be tracked using molecular markers. This will speed up the production of new and improved oil palm planting materials. Results: A map was constructed using AFLP, RFLP and SSR markers for an interspecific cross involving a Colombian Elaeis oleifera (UP1026) and a Nigerian E. guinneensis (T128). A framework map was generated for the male parent, T128, using Joinmap ver. 4.0. In the paternal (E. guineensis) map, 252 markers (199 AFLP, 38 RFLP and 15 SSR) could be ordered in 21 linkage groups (1815 cM). Interval mapping and multiple-QTL model (MQM) mapping (also known as composite interval mapping, CIM) were used to detect quantitative trait loci (QTLs) controlling oil quality (measured in terms of iodine value and fatty acid composition). At a 5% genome-wide significance threshold level, QTLs associated with iodine value (IV), myristic acid (C14:0), palmitic acid (C16:0), palmitoleic acid (C16:1), stearic acid (C18:0), oleic acid (C18:1) and linoleic acid (C18:2) content were detected. One genomic region on Group 1 appears to be influencing IV, C14:0, C16:0, C18:0 and C18:1 content. Significant QTL for C14:0, C16:1, C18:0 and C18:1 content was detected around the same locus on Group 15, thus revealing another major locus influencing fatty acid composition in oil palm. Additional QTL for C18:0 was detected on Group 3. A minor QTL for C18:2 was detected on Group 2. Conclusion: This study describes the first successful detection of QTLs for fatty acid composition in oil palm. These QTLs constitute useful tools for application in breeding programmes.