Ramesh Buyyarapu

By Siva P. Kumpatla, Ramesh Buyyarapu, Ibrokhim Y. Abdurakhmonov and Jafar A. Mammadov

Part of the book: Plant Breeding

By Venkateswara R. Sripathi, Ramesh Buyyarapu, Siva P. Kumpatla, Abreeotta J. Williams, Seloame T. Nyaku, Yonathan Tilahun, Venu Kalavacharla and Govind C. Sharma

Cotton is economically and evolutionarily important crop for its fiber. In order to improve fiber quality and yield, and to exploit the natural genetic potential inherent in genotypes, understanding genome structure and function of cultivated cotton is important. In order to achieve this, a functional understanding of bioinformatics resources such as databases, software solutions, and analysis tools is required. But currently, there are very few unified reports on bioinformatics tools and even fewer repositories to access cotton genomic information. Also, resourceful developers and bioinformatics scientists actively addressing complex genomic challenges in cotton genomes are much in need. The primary goal of this chapter is to provide a review of such tools and resources for analyzing the structure and function of the cotton genome with preferential emphasis on this complex and economically important plant species. This discourse begins with a description of concurrent advances in high‐throughput genome sequencing and bioinformatics analyses and focuses on four major sections covering bioinformatics tools and resources for analysis of: (1) genomes; (2) transcriptomes; (3) small RNAs; and (4) epigenomes. In each section, recent advances in cotton have been discussed. Cotton genome sequencing and annotation efforts are outlined within these sections. This review discusses the availability of genome information of both diploid and tetraploid species that have impelled cotton genome research into the post‐genomics era, opening new avenues for exploring regulatory mechanisms associated with fine‐tuning of gene expression of fiber‐related genes. Finally, the potential impacts of these rapid advances, especially the challenges in handling and analyzing the large datasets are discussed.

Part of the book: Bioinformatics