This volume focuses on modern computational and statistical tools for translational gene expression and regulation research to improve prognosis, diagnostics, prediction of severity, and therapies for human diseases. It introduces some of state of the art technologies as well as computational and statistical tools for translational bioinformatics in the areas of gene transcription and regulation, including the tools for next generation sequencing analyses, alternative spicing, the modeling of signaling pathways, network analyses in predicting disease genes, as well as protein and gene expression data integration in complex human diseases etc. The book is particularly useful for researchers and students in the field of molecular biology, clinical biology and bioinformatics, as well as physicians etc. Dr. Jiaqian Wu is assistant professor in the Vivian L. Smith Department of Neurosurgery and Center for Stem Cell and Regenerative Medicine, University of Texas Health Science Centre, Houston, TX, USA.​

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

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.

This volume provides experimental and bioinformatics approaches related to different aspects of gene expression analysis. Divided in three sections chapters detail wet-lab protocols, bioinformatics approaches, single-cell gene expression, highly multiplexed amplicon sequencing, multi-omics techniques, and targeted sequencing. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Gene Expression Analysis: Methods and Protocols aims provide useful information to researchers worldwide.

Gene regulation is tightly regulated to produce individual phenotypes appropriate to a animal's placement in time and space. How specific genetic and environmental factors shape gene regulation has been extensively studied in laboratory model species. However, far less is known about sources of variance in gene regulation in the wild, in populations where natural selection operates. My dissertation research aimed to identify factors that influence individual variation in gene regulation by evaluating transcriptome-wide gene expression levels within and across populations. In my first chapter, I evaluated gene expression changes in captive Swainson's thrushes (Catharus ustulatus) originating from two populations as they transitioned from the non-migratory to migratory condition. Birds exhibited significant seasonal differences in the expression of genes involved in cellular development in the brain, providing support for seasonal neural plasticity in migratory birds. In my second chapter, I focused on a single population, the North American gray wolves (Canis lupus) of Yellowstone National Park, to evaluate the relative impacts of intrinsic (age and sex) and environmental variables (social status and presence of sarcoptic mange) on gene expression variation in blood. I found that, unexpectedly, animal age, but not sex, social status, or sarcoptic mange infestation, impacted gene expression, suggesting that age may have pervasive, evolutionarily conserved effects on gene expression variation in natural populations of mammals. Finally, in my third chapter, I adopted an in vitro experimental approach to study how gene regulation is impacted by genotype at the CBD103 gene, which encodes a protein with antimicrobial properties, exists in two forms (alleles) in North American gray wolves, and is associated with lifetime reproductive success. I established keratinocyte lines from 24 gray wolves and utilized CRISPR/Cas9 to generate one heterozygous and homozygous line. To test whether the fitness effects of CBD103 genotype are explained by their roles in immune defense, I challenged the cells with synthetic antigens and live canine distemper virus. No effect of CBD103 genotype was detected, but immune challenge altered expression of thousands of genes. This work demonstrated the ability to establish a population panel of cell lines from a wild mammal, a potentially powerful method for studying gene regulation in natural populations.

This book is the first comprehensive volume on conifers detailing their genomes, variations, and evolution. The book begins with general information about conifers such as taxonomy, geography, reproduction, life history, and social and economic importance. Then topics discussed include the full genome sequence, complex traits, phenotypic and genetic variations, landscape genomics, and forest health and conservation. This book also synthesizes the research included to provide a bigger picture and suggest an evolutionary trajectory. As a large plant family, conifers are an important part of economic botany. The group includes the pines, spruces, firs, larches, yews, junipers, cedars, cypresses, and sequoias. Of the phylum Coniferophyta, conifers typically bear cones and evergreen leaves. Recently, there has been much data available in conifer genomics with the publication of several crop and non-crop genome sequences. In addition to their economic importance, conifers are an important habitat for humans and animals, especially in developing parts of the world. The application of genomics for improving the productivity of conifer crops holds great promise to help provide resources for the most needy in the world.