Transcriptomics and gene expression profiling enables the elucidation of the genetic response of an organism to various environmental cues. Transcriptomics enables the deciphering of differences between two closely related organisms to the same environment and in contrast, enables the elucidation of genetic responses of the same organism to different environmental cues. Two major methods are utilized for the study of transcriptomes, high-throughput sequencing and microarray analysis. High-throughput sequencing technologies such as the Illumina platform are relatively new and protocols must be developed for the analyses of transcriptomes (RNA-sequencing). A RNA-seq protocol was developed and refined for the Illumina sequencing platform. This protocol was then utilized for the de novo sequencing of the steelhead salmon transcriptome. Hatchery steelhead exhibit a reduced fitness compared to wild steelhead that has been shown to be genetically based. Consequently, the steelhead transcriptome was assembled, annotated, and used to identify gene expression differences between hatchery and wild fish. We uncovered many differentially expressed genes involved in metabolic processes and growth and development. This work has created a better understanding of the genetic differences between hatchery and wild steelhead salmon. Brachypodium distachyon is a monocot grass important as a model for cereal crops and potential biofuels feedstocks. To better understand the genetic response of this plant to different environmental cues, a comprehensive assessment of the transcriptomic response was conducted under a variety of conditions including diurnal/circadian light/dark/temperature environments and different abiotic stress conditions. Using a whole-genome tiling DNA microarray, we identified that the majority of transcripts in Brachypodium exhibit a daily rhythm in their abundance that is conserved between rice and Brachypodium. We also identified numerous cis-regulatory elements dictating these rhythmic expression patterns. We also identified the genetic response to abiotic stresses such as salinity, drought, cold, heat, and high light. We uncovered a core set of genes which responds to all stresses, indicating a core stress response. A large number of transcription factors were uncovered as potential nodes for regulating the abiotic stress response in Brachypodium. Moreover, promoter elements that drive specific responses to discrete abiotic stresses were uncovered. Altogether, the transcriptome analyses in this work furthers our understandings of how particular organisms respond to environmental cues and better elucidates the relationship between genes and the environment.

Next generation sequencing is revolutionizing molecular biology. Owing to this new technology it is now possible to carry out a panoply of experiments at an unprecedented low cost and high speed. These go from sequencing whole genomes, transcriptomes and small non-coding RNAs to description of methylated regions, identification protein – DNA interaction sites and detection of structural variation. The generation of gigabases of sequence information for each of this huge bandwidth of applications in just a few days makes the development of bioinformatics applications for next generation sequencing data analysis as urgent as challenging.

Transcriptome analysis is the study of the transcriptome, of the complete set of RNA transcripts that are produced under specific circumstances, using high-throughput methods. Transcription profiling, which follows total changes in the behavior of a cell, is used throughout diverse areas of biomedical research, including diagnosis of disease, biomarker discovery, risk assessment of new drugs or environmental chemicals, etc. Transcriptome analysis is most commonly used to compare specific pairs of samples, for example, tumor tissue versus its healthy counterpart. In this volume, Dr. Pyo Hong discusses the role of long RNA sequences in transcriptome analysis, Dr. Shinichi describes the next-generation single-cell sequencing technology developed by his team, Dr. Prasanta presents transcriptome analysis applied to rice under various environmental factors, Dr. Xiangyuan addresses the reproductive systems of flowering plants and Dr. Sadovsky compares codon usage in conifers.

The study of transcriptomics is key to understanding complex diseases. This new edition will build on the foundation of the first edition while incorporating the progress that has been made in the field of transcriptomics in the past six years, including bioinformatics for data analysis. Written by leading experts, chapters address new subjects such as methodological advances in large-scale sequencing, the sequencing of single-cells, and spatial transcriptomics. The new edition will address how transcriptomics may be used in combination with genetic strategies to identify causative genes in monogenic and complex genetic diseases. Coverage will also explore transcriptomics in challenging groups of diseases, such as cancer, inflammation, bacterial infection, and autoimmune diseases. The updated volume will be useful for geneticists, genome biologists, biomedical researchers, molecular biologists, bioinformaticians, and students, among others.

Since the independent invention of DNA sequencing by Sanger and by Gilbert 30 years ago, it has grown from a small scale technique capable of reading several kilobase-pair of sequence per day into today's multibillion dollar industry. This growth has spurred the development of new sequencing technologies that do not involve either electrophoresis or Sanger sequencing chemistries. Sequencing by Synthesis (SBS) involves multiple parallel micro-sequencing addition events occurring on a surface, where data from each round is detected by imaging. New High Throughput Technologies for DNA Sequencing and Genomics is the second volume in the Perspectives in Bioanalysis series, which looks at the electroanalytical chemistry of nucleic acids and proteins, development of electrochemical sensors and their application in biomedicine and in the new fields of genomics and proteomics. The authors have expertly formatted the information for a wide variety of readers, including new developments that will inspire students and young scientists to create new tools for science and medicine in the 21st century. Reviews of complementary developments in Sanger and SBS sequencing chemistries, capillary electrophoresis and microdevice integration, MS sequencing and applications set the framework for the book. * 'Hot Topic' with DNA sequencing continuing as a major research activity in many areas of life science and medicine. * Bringing together new developments in DNA sequencing technology * Reviewing issues relevant to the new applications used

DNA microarrays and high throughput sequencing (HTS) have allowed investigators to characterize nucleic acids (DNA and RNA) across tissues, treatments, samples, and species, providing a wealth of information in efficient and cost-effective ways. This dissertation presents an application of DNA microarrays and two novel methods for analysis of HTS data. Bacterial and fungal species that live in and on the human body are believed to play important roles in the maintenance of health and prevention of disease. To study these communities in the human vagina, we developed the VChip, a DNA microarray with probes representing 313 strains of bacteria as well as 716 human immunity genes. This array was validated using mock bacterial communities and tested using DNA and cDNA from vaginal swabs. The VChip produced results that accurately reflected the composition of the mock bacterial communities, and produced results similar to those obtained from 16S rRNA amplicon pyrosequencing. Assembly by Reduced Complexity (ARC), is a software package that facilitates iterative, reference seeded assembly of HTS datasets. This strategy is useful for datasets that can be divided into several discreet subsets that can each be assembled independently. A set of reference or "target" sequences is used to recruit initial subsets of reads, each subset is assembled independently into contigs, these contigs are then used to recruit a new set of reads. This process is iterated, to grow assemblies until stopping conditions are met. I showed that ARC works well even with moderately divergent references, and is not plagued by reference bias, a serious limitation of mapping based strategies. StopGap is a strategy for improving genome assemblies. Gap spanning Pacific Biosciences continuous long reads are identified and used to guide assembly of high quality Illumina or 454 reads with the ARC pipeline. Two assembly merging programs were tested for their ability to take advantage of these gap-bridging contigs. I show that this approach was able to produce more contiguous assemblies and better represent repeated sequences within the assembly. Although StopGap was used here to improve the assembly of a bacterial genome, this approach could be used in the assembly of more complex eukaryotic genomes as well.

Transcriptome Profiling: Progress and Prospects assists readers in assessing and interpreting a large number of genes, up to and including an entire genome. It provides key insights into the latest tools and techniques used in transcriptomics and its relevant topics which can reveal a global snapshot of the complete RNA component of a cell at a given time. This snapshot, in turn, enables the distinction between different cell types, different disease states, and different time points during development. Transcriptome analysis has been a key area of biological inquiry for decades. The next-generation sequencing technologies have revolutionized transcriptomics by providing opportunities for multidimensional examinations of cellular transcriptomes in which high-throughput expression data are obtained at a single-base resolution. Transcriptome analysis has evolved from the detection of single RNA molecules to large-scale gene expression profiling and genome annotation initiatives. Written by a team of global experts, key topics in Transcriptome Profiling include transcriptome characterization, expression analysis of transcripts, transcriptome and gene regulation, transcriptome profiling and human health, medicinal plants transcriptomics, transcriptomics and genetic engineering, transcriptomics in agriculture, and phylotranscriptomics. Presents recent development in the tools and techniques in transcriptomic characterization Integrates expression analysis of transcripts and gene regulation Includes the application of transcriptomics in human health, genetic engineering and agriculture