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New generation sequencing machines: Illumina and Solexa can generate millions of short reads from a given genome sequence on a single run. Alignment of these reads to a reference genome is a core step in Next-generation sequencing data analysis such as genetic variation and genome re-sequencing etc. Therefore there is a need of a new approach, efficient with respect to memory as well as time to align these enormous reads with the reference genome. Existing techniques such as MAQ, Bowtie, BWA, BWBBLE, Subread, Kart, and Minimap2 require huge memory for whole reference genome indexing and reads alignment. Gapped alignment versions of these techniques are also 20–40% slower than their respective normal versions. In this paper, an efficient approach: WIT for reference genome indexing and reads alignment using Burrows–Wheeler Transform (BWT) and Wavelet Tree (WT) is proposed. Both exact and approximate alignments are possible by it. Experimental work shows that the proposed approach WIT performs the best in case of protein sequence indexing. For indexing, the reference genome space required by WIT is 0.6N (N is the size of reference genome) whereas existing techniques BWA, Subread, Kart, and Minimap2 require space in between 1.25N to 5N. Experimentally, it is also observed that even using such small index size alignment time of proposed approach is comparable in comparison to BWA, Subread, Kart, and Minimap2. Other alignment parameters accuracy and confidentiality are also experimentally shown to be better than Minimap2. The source code of the proposed approach WIT is available at http://www.algorithm-skg.com/wit/home.html.

On the surface, wheat and barley have little to offer the rice genomics research community. They have very large genomes without a physical map, making positional cloning complex, and they are difficult to transform, which hinders the functional analysis of genes and delivery of transgenic technologies. However, shifts in plant genomics research into understanding the basis of diversity and mechanisms involved in creating and maintaining genome complexity have shifted research from a model organism toward more complex species. Wheat and barley are becoming increasingly attractive organisms for many of the new genomics studies. Several key tools have been important for this change, including detailed and well-phenotyped populations, mapping of a large collection of ESTs, and studies of synteny with rice and maize.

Importantly, wheat and barley are widely adapted and there has been extensive monitoring and archiving of genotypes and associated phenotypic data. We also have populations adapted to specific environments and end-uses that have resulted from a long history of selective breeding. These advantages are becoming increasingly significant as analytic tools improve. Early genomics efforts in wheat and barley have delivered useful markers for application in breeding programs and identified key regions of the genome that carry disease-resistance loci, tolerance of abiotic stresses, and components of quality. The expanding resource base for wheat and barley genomics and the new insights being gained into genome organization and behavior of these species offer improvements in our ability to identify new sources of variation and to implement this information in breeding programs.