Rice is a staple food for more than half of the world's population, and is therefore one of the most important crops directly involved in global food security. Rice accumulates high concentrations of silicon (Si), up to 10% of its dry mass. Silicon has been shown to be involved in plant growth, high yield and mitigating biotic and abiotic stresses. Importantly, inorganic arsenic (As) is taken up by rice through Si transporters. The aims of this project were: 1) To identify natural variation for shoot silicon concentration in rice 2) To determine if germanium is a suitable analogue of silicon for determining natural variation of silicon concentration in rice 3) To identify the underlying putative genes for shoot silicon/germanium concentration in rice. Initially the concentration of silicon in 50 accessions grown in the field was assessed. There was a significant difference of shoot Si concentration observed in these rice accessions. This indicated that there is genetic regulation of natural variation of shoot Si concentration in rice. Germanium (Ge) is an analogue of silicon which produces brown lesion in shoot and leaves. Ge has previously been used to screen a large population of mutant rice plants to identify Si transporters Lsi1 and Lsi2 and the homologue of these two genes Lsi6 and Lsi3 respectively. In this study a Ge screen was developed to identify natural genetic variation for shoot Ge lesions in rice. To identify the Ge tolerant loci in the rice genome, a phenotypic method for Ge screening was developed and performed on two different genetic mapping populations. An experiment with 19 cultivars from RDP1 where Ge uptake was measured found a positive relationship between shoot Ge lesions and shoot Ge concentration in rice. A genetic mapping study of the Bala × Azucena F6 population with 15 µM of GeO2 had a broad sense heritability of 75.8% - 86.1% and identified 15 significant quantitative trait loci (QTLs) and 7 putative QTLs for Ge lesions. A number of QTLs co-localised with previously detected Si and As QTLs. A genome-wide association (GWA) study was also conducted for Ge lesion with 341 rice accessions from the Rice Diversity Panel 1. Statistical analysis indicated genotype v explained 66.10%, 63.70% and 57.60% of the phenotypic variation on days 4, 5 and 6 respectively. Rice subpopulation structure explained 16.50%, 14.70% and 15.90% of the phenotypic variation on days 4 and 5 and 6 respectively. A total of 17 significant SNPs (P < 0.0001; MAF > 0.05) were detected in GWA mapping of Ge tolerant loci for all accessions and a further 54 significant SNPs were detected when performing the analysis with individual rice subpopulations. A number of associations co-localised with previously detected Ge, Si and As QTLs. From the QTL mapping of Bala × Azucena F6 population a QTL was identified on top of chromosome 1 on multiple days where LOC_Os01g02190 is located. LOC_Os01g02190 is 86.71% and 83.57% homologous with Lsi6 and Lsi1 respectively. The GWA mapping of Ge tolerant loci in RDP1 identified a significant SNP near to LOC_Os10g31040 which is 53.60% and 55.46% homologous with Lsi2 and Lsi3 respectively. This high-throughput, cost effective and time saving method can be used for the identification of Si transporters in any other crop as well as to screen a bigger population in rice that may help for the identification of Si/As transporters.