Chickpea is an annual, self-pollinating, diploid (2n=2x=16) and the second most important food legume crop with major production areas in the Indian sub-continent, West Asia and North Africa. Australia is the largest exporter of chickpea and yield for 2015 has been forecasted at 990,000 tonnes (http://www.agriculture.gov.au/abares/media-releases/2015). The main constraint for increasing yield is the susceptibility of the plant to foliar disease, ascochyta blight, fusarium wilt. Chickpea breeding aims at high yielding cultivars that combine longlasting resistance against both biotic and abiotic stress. Emerging sequencing technologies have enhanced the availability of crop genomic resources. Analysis of huge amounts of genomic data comes with major computational challenges.This thesis describes a new method for assessing the quality of reference genome assembly by flow sorting and isolating chromosomes based on size. This chromosomal DNA was sequenced and mapped to the reference genome assembly.This approach will reduce the genome DNA complexity to a chromosome level and is expect to correspond to only one chromosome assembly. Appling this approach on both released desi and kabuli reference genomes has shown miss-assembly. The desi genome was of poor quality compared to the kabuli genome. To fix these misassemblies, we developed a novel method called skimGBS for rearranging the fragmented sequences. In this approach, genotypes were called from population individuals to construct haplotype blocks. Based on the haplotype block signature, contigs/fragmented sequences were reordered as new assemblies. Using this approach, both desi and kabuli genomes were improved by placing unplaced contig sequences into chromosomes. Furthermore, these improved reference assemblieswere assessed and annotated.This thesis also reports identification of more than 800,000 high quality SNPs by sequencing 69 diverse Australian chickpea accessions. Gene loss, genetic relatedness, population structure and diversity analysis was also performed. The public accessibility of the data and above results provides a valuable resource to support chickpea research.iiThe developed methodology can also apply to other genomics studies, and will therefore be a valuable approach to assist crop improvement and further breeding approaches.iii