@article{3040, author = "MRITYUNJAY CHOUBEY and URVASHI LAMA and P. CHETRI and B. BERA", abstract = "Tea (Camellia sinensis L. (O) Kuntze) is the most widely consumed health drink. Due to self incompatibility and highly heterozygous nature along with large genome size of about 4.0Gigabase, the genomic research on tea is not been explored as much as conducted in other annual crops. Nowadays, advances in genome sequencing technologies are revolutionizing the routine research work of plant genetics. This will pave the way for identification of genes responsible for various agronomically important traits, development of improved tea cultivars, tolerant to biotic and a biotic stress. However, Next generation sequencing (NSG) data analysis in tea is an emerging field of tea research. Hence, the use of bio-informatics tools to evaluate and interpret NGS data is a challenge for the researcher. Analysis of this large amount of heterogeneous genomic data requires effective use and application of bioinformatics tools that must include unified functional annotation, structural search and comprehensive analysis and identification of new genes with fully sequenced genomes. This review discusses momentarily about the applications of phenomics, genomics resources and bioinformatics in next generation sequencing data analysis, with an emphasis on those relevant to tea research. Some fundamental issues related to biological sequence analysis, data basis and software tools are also focussed that facilitate an understanding of the biological processes with the goal to serve as an important information platform for genomic studies which will effectively improve the efficiency of breeding programmes in tea. ", issn = "23191473", journal = "IJAIR", keywords = "Bioinformatics;Camellia;Marker Assisted Selection;Molecular Markers;Next-Generation Sequencing;Phenomics;Tea Genome", month = "May", number = "6", pages = "622-627", title = "{A}pplication of {P}henomics, {G}enomic {R}esources and {B}ioinformatics {T}ools for {T}ea {P}lant {I}mprovement", volume = "7", year = "2019", }