Abstract
Highlights: • Sucrose, inorganic phosphorus and yield allow identifying quick-starter clones. • QTL analysis revealed a complex genetic basis of latex production. • First application of latex diagnosis-based clonal typology in breeding. • First identification of a QTL associated with sucrose loading. • First identification of chromosomal regions underlying QTLs linked to physiological parameters.Abstract: Hevea brasiliensis, a natural rubber producing species, is widely cultivated due to its high rubber yield potential. Natural rubber is synthesised in the rubber particles of laticifers. Latex diagnosis (LD) was established to characterise the physiological state of the laticiferous system by measuring its physiological parameters, i.e., sucrose, inorganic phosphorous (Pi), thiols and total solid content (TSC). Rubber clones are often classified in three groups i.e., quick starters, medium starters and slow starters. To better understand the genetic bases of latex yield, a biparental population was generated from a cross between the quick-starter clone PB 260 and the medium-starter clone SP 217. LD was performed during the peak latex production season and used to calculate sucrose loading. The agronomic and physiological parameters associated with latex yield led to the classification of genotypes according to the rubber clonal typology and to the identification of quantitative trait loci (QTL) using a high-density map. Inorganic phosphorous content was positively associated with yield during the first year of production thus enabling identification of quick-starter clones. In addition, the LD-based clonal typology led to determine the long-term yield potential and the use of appropriate ethephon stimulation. QTL analysis successfully identified several QTLs related to yield, sucrose, Pi and TSC. One QTL related to sucrose loading was identified in the same position as the QTL for sucrose on linkage group 1. To our knowledge, this is the first study to report QTL analysis for this trait. The use of a high-density map enables the identification of genes underlying QTLs. Several putative genes underlying QTLs related to yield, sucrose and TSC were identified.