High levels of arsenic in rice grains threaten the health of millions of people particularly in the Ganges delta of India and Bangladesh where arsenic-contaminated irrigation water is used for rice cultivation. It is of global importance that this problem is tackled and that Indian scientists are able to contribute to the solution. In this application it is proposed that an advanced backcross breeding approach be used to both map quantitative loci (QTLs) for low grain arsenic and to incorporate these QTLs into farmer preferred verities by marker- assisted selection (MAS). Hybrids between locally adapted arsenic tolerant variety and Azucena have already been made in Calcutta University. These hybrids will be utilized for raising backcross populations. Two approaches will be employed to identify QTLs for low arsenic. For one population, QTL for low grain arsenic will be identified by conventional QTL analysis. For the other population, a new method of bulk segregant analysis linked to feature polymorphism of an Affymetrix microarray will be used. Feature polymorphisms between the parents and which also segregate in the segregant pools will be linked to the rice sequence by bioinformatics and the genomic regions responsible for the trait identified. All results obtained will be compared to those obtained in the UK-funded project to allow meta-QTL analysis.. Identify the markers will be used to breed low arsenic varieties suited to West Bengal and the MAS breeding will be forwarded in the second year of the project exploiting ability to get 3 generations per year in West Bengal. The final steps of the breeding will be completed in the return phase where workshops will be deployed to transfer knowledge gained on the advanced genetic and bioinformatic techniques.