Bioinformatics: A Way Forward to Explore “Plant Omics”

Bioinformatics, a computer-assisted science aiming at managing a huge volume of genomic data, is an emerging discipline that combines the power of computers, mathematical algorithms, and statistical concepts to solve multiple genetic/biological puzzles. This science has progressed parallel to the evolution of genome-sequencing tools, for example, the next-generation sequencing technologies, that resulted in arranging and analyzing the genome-sequencing information of large genomes. Synergism of “plant omics” and bioinformatics set a firm foundation for deducing ancestral karyotype of multiple plant families, predicting genes, etc. Second, the huge genomic data can be assembled to acquire maximum information from a voluminous “omics” data. The science of bioinformatics is handicapped due to lack of appropriate computational procedures in assembling sequencing reads of the homologs occurring in complex genomes like cotton (2n = 4x = 52), wheat (2n = 6x = 42), etc., and shortage of multidisciplinary-oriented trained manpower. In addition, the rapid expansion of sequencing data restricts the potential of acquisitioning, storing, distributing, and analyzing the genomic information. In future, inventions of high-tech computational tools and skills together with improved biological expertise would provide better insight into the genomes, and this information would be helpful in sustaining crop productivities on this planet

Genetic Mapping in Cotton

The genus Gossypium provides natural fiber for textile industry worldwide. Genetic improvement in cotton for traits of interest is not up to mark due to scarcity of adequate information about fiber production and quality. Use of DNA markers for overcoming the issues of selection associated with complex traits is the ultimate choice which may lead to initiate breeding by design. Numerous marker-trait associations have been identified for economical traits using linkage analysis in cotton. Currently there is need for developing high-density genetic maps using next-generation sequencing approaches together with genome-wide association studies (GWAS). Efforts have been started in this direction and several QTLs including fiber quality, yield traits, plant architecture, stomatal conductance and verticillium wilt resistance were identified. This chapter narrates genetic diversity, QTL mapping, association mapping and QTLs related to fiber quality traits. The incorporation of various genomic approaches and previously described marker strategies will pave the way for increase in fiber production

Association Mapping for Improving Fiber Quality in Upland Cottons

Improved fiber yield is considered a constant goal of upland cotton (Gossypium hirsutum) breeding worldwide, but the understanding of the genetic basis controlling yield-related traits remains limited. Dissecting the genetic architecture of complex traits is an ongoing challenge for geneticists. Two complementary approaches for genetic mapping, linkage mapping and association mapping have led to successful dissection of complex traits in many crop species. Both of these methods detect quantitative trait loci (QTL) by identifying marker–trait associations, and the only fundamental difference between them is that between mapping populations, which directly determine mapping resolution and power. Nowadays, the availability of genomic tools and resources is leading to a new revolution of plant breeding, as they facilitate the study of the genotype and its relationship with the phenotype, in particular for complex traits. Next Generation Sequencing (NGS) technologies are allowing the mass sequencing of genomes and transcriptomes, which is producing a vast array of genomic information with the development of high-throughput genotyping, phenotyping will be a major challenge for genetic mapping studies. We believe that high-quality phenotyping and appropriate experimental design coupled with new statistical models will accelerate progress in dissecting the genetic architecture of complex traits

Past, Present and Future Trends in Cotton Breeding

Cotton, a source of natural fiber for textile industry, has a long breeding history aiming at increasing cotton fiber yield and its quality. Newly developed cotton varieties poorly respond in low-input environments. Secondly, the impact of changing climate may threaten the cotton production in the future. To address these challenges, efforts toward the development of resilient cotton varieties have been initiated using genetic and modern genomic approaches. In this book, research updates on cotton fiber types and properties, DNA markers for selecting desirable cotton plants, and cotton fiber genomics were compiled. Also, the modern breeding trends including development of transgenic cotton and the biosafety studies and possibilities of improving cotton genome using modern genome editing tools were also compressively discussed