The multiple facets of homology and their use in comparative genomics to study the evolution of genes, genomes, and species

The incredible development of comparative genomics during the last decade has required a correct use of the concept of homology that was previously utilized only by evolutionary biologists. Unhappily, this concept has been often misunderstood and thus misused when exploited outside its evolutionary context. This review brings back to the correct definition of homology and explains how this definition has been progressively refined in order to adapt it to the various new kinds of analysis of gene properties and of their products that appear with the progress of comparative genomics. Then, we illustrate the power and the proficiency of such a concept when using the available genomics data in order to study the evolution of individual genes, of entire genomes and of species, respectively. After explaining how we detect homologues by an exhaustive comparison of a hundred of complete proteomes, we describe three main lines of research we have developed in the recent years. The first one exploits synteny and gene context data to better understand the mechanisms of genome evolution in prokaryotes. The second one is based on phylogenomics approaches to reconstruct the tree of life. The last one is devoted to reminding that protein homology is often limited to structural segments (SOH=segment of homology or module). Detecting and numbering modules allows tracing back protein history by identifying the events of gene duplication and gene fusion. We insist that one of the main present difficulties in such studies is a lack of a reliable method to identify genuine orthologues. Finally, we show how these homology studies are helpful to annotate genes and genomes and to study the complexity of the relationships between sequence and function of a gene.     

Recent insights into cotton functional genomics: progress and future perspectives

Functional genomics has transformed from futuristic concept to well‐established scientific discipline during the last decade. Cotton functional genomics promise to enhance the understanding of fundamental plant biology to systematically exploit genetic resources for the improvement of cotton fibre quality and yield, as well as utilization of genetic information for germplasm improvement. However, determining the cotton gene functions is a much more challenging task, which has not progressed at a rapid pace. This article presents a comprehensive overview of the recent tools and resources available with the major advances in cotton functional genomics to develop elite cotton genotypes. This effort ultimately helps to filter a subset of genes that can be used to assemble a final list of candidate genes that could be employed in future novel cotton breeding programme. We argue that next stage of cotton functional genomics requires the draft genomes refinement, re‐sequencing broad diversity panels with the development of high‐throughput functional genomics tools and integrating multidisciplinary approaches in upcoming cotton improvement programmes.     

How genomics has affected the concept of microbiology

Genomics influences multiple areas of microbiology, and thus affects key microbiological concepts. Recent reports that describe the large genome and unusual coding capacity of mimivirus, the minimized fungal genomes that contain elements of bacterial metabolism, and the 'signature' eukaryotic proteins in bacteria are introducing grey shades into the black-and-white distinctions between microbial domains. The concept of the 'universal' minimal genome is being challenged, and the ability of minimal genomes to support cellular complexity is under investigation. There have been intriguing insights into microbe-microbe relationships, for example conflict mediation in competing bacteriophages that rapidly evolve survival mechanisms when cooperation is experimentally enforced. Genomics has given birth to metagenomics, but has also stimulated the development of improved cultivation techniques. Lastly, the taxonomic potential of genomics is emerging, as studies of multiple strains allow us to revise and refine the bacterial species concept as well as the idea of a static genome.     

Cell death goes LIVE: Technological advances in real-time tracking of cell death

Cell population can be viewed as a quantum system, which like Schrödinger’s cat exists as a combination of survival- and death-allowing states. Tracking and understanding cell-to-cell variability in processes of high spatio-temporal complexity such as cell death is at the core of current systems biology approaches. As probabilistic modeling tools attempt to impute information inaccessible by current experimental approaches, advances in technologies for single-cell imaging and omics (proteomics, genomics, metabolomics) should go hand in hand with the computational efforts. Over the last few years we have made exciting technological advances that allow studies of cell death dynamically in real-time and with the unprecedented accuracy. These approaches are based on innovative fluorescent assays and recombinant proteins, bioelectrical properties of cells, and more recently also on state-of-the-art optical spectroscopy. Here, we review current status of the most innovative analytical technologies for dynamic tracking of cell death, and address the interdisciplinary promises and future challenges of these methods.     

How genomics can help biodiversity conservation

The availability of public genomic resources can greatly assist biodiversity assessment, conservation, and restoration efforts by providing evidence for scientifically informed management decisions. Here we survey the main approaches and applications in biodiversity and conservation genomics, considering practical factors, such as cost, time, prerequisite skills, and current shortcomings of applications. Most approaches perform best in combination with reference genomes from the target species or closely related species. We review case studies to illustrate how reference genomes can facilitate biodiversity research and conservation across the tree of life. We conclude that the time is ripe to view reference genomes as fundamental resources and to integrate their use as a best practice in conservation genomics.     

Alternative splicing: a paradoxical qudo in eukaryotic genomes

One of the most remarkable observations stemming from the sequencing of genomes of diverse species is that the number of protein-coding genes in an organism does not correlate with its overall cellular complexity. Alternative splicing, a key mechanism for generating protein complexity, has been suggested as one of the major explanation for this discrepancy between the number of genes and genome complexity. Determining the extent and importance of alternative splicing required the confluence of critical advances in data acquisition, improved understanding of biological processes and the development of fast and accurate computational analysis tools. Although many model organisms have now been completely sequenced, we are still very far from understanding the exact frequency of alternative splicing from these sequenced genomes.This paper will highlight some recent progress and future challenges for functional genomics and bioinformatics in this rapidly developing area.     

Putting the landscape into the genomics of trees: approaches for understanding local adaptation and population responses to changing climate

The Forest ecosystem genomics Research: supporTing Transatlantic Cooperation project (FoResTTraC, http://www.foresttrac.eu/) sponsored a workshop in August 2010 to evaluate the potential for using a landscape genomics approach for studying plant adaptation to the environment and the potential of local populations for coping with changing climate. This paper summarizes our discussions and articulates a vision of how we believe forest trees offer an unparalleled opportunity to address fundamental biological questions, as well as how the application of landscape genomic methods complement to traditional forest genetic approaches that provide critical information needed for natural resource management. In this paper, we will cover four topics. First, we begin by defining landscape genomics and briefly reviewing the unique situation for tree species in the application of this approach toward understanding plant adaptation to the environment. Second, we review traditional approaches in forest genetics for studying local adaptation and identifying loci underlying locally adapted phenotypes. Third, we present existing and emerging methods available for landscape genomic analyses. Finally, we briefly touch on how these approaches can aid in understanding practical topics such as management of tree populations facing climate change.     

Understanding the industrial application potential of lactic acid bacteria through genomics

Lactic acid bacteria (LAB) are a heterogeneous group of bacteria contributing to various industrial applications, ranging from food and beverage fermentation, bulk and fine chemicals production to pharmaceuticals manufacturing. Genome sequencing is booming; hitherto, 25 genomes of LAB have been published and many more are in progress. Based on genomic content of LAB, this review highlights some findings related to applications revealed by genomics and functional genomics analyses. Finally, this review summarizes mathematical modeling strategies of LAB in the context of genomics, to further our understanding of industrial related features.     

Mining the genomes of plant pathogenic bacteria: how not to drown in gigabases of sequence

Hundreds of bacterial genomes including the genomes of dozens of plant pathogenic bacteria have been sequenced. These genomes represent an invaluable resource for molecular plant pathologists. In this review, we describe different approaches that can be used for mining bacterial genome sequences and examples of how some of these approaches have been used to analyse plant pathogen genomes so far. We review how genomes can be mined one by one and how comparative genomics of closely related genomes releases the true power of genomics. Databases and tools useful for genome mining that are publicly accessible on the Internet are also described. Finally, the need for new databases and tools to efficiently mine today's plant pathogen genomes and hundreds more in the near future is discussed.     

Comparative genomics and the evolution of prokaryotes

Although biologists have long recognized the importance of studying evolution to understand the organization of living organisms, only with the development of genomics have evolutionary studies become part of their routine toolkit. Placing genomes into an evolutionary framework has proved useful for understanding the functioning of organisms. It has also substantially increased understanding of the processes by which genomes evolve and led to a re-evaluation of our representation of the diversity and the history of life. In this review, we present some of the most important recent advances and promising leads in the field of microbial evolutionary genomics.     

Searching for synthetic lethality in cancer

The incentive to develop personalised therapy for cancer treatment is driven by the premise that it will increase therapeutic efficacy and reduce toxicity. Understanding the underlying cellular and molecular basis of the disease has been extremely important in the design of these novel therapies; however, identifying new drug targets for personalised therapies remains problematic. This review describes how the biological concept of synthetic lethality has been successfully implemented to identify new therapeutic approaches and targets in models from yeast through to human cells. We also discuss how recent technical advances combined with an increased understanding of the complexity of cellular networks may facilitate therapeutic advances in the future.     

Plant Metabolic Modeling: Achieving New Insight into Metabolism and Metabolic Engineering

Models are used to represent aspects of the real world for specific purposes, and mathematical models have opened up new approaches in studying the behavior and complexity of biological systems. However, modeling is often time-consuming and requires significant computational resources for data development, data analysis, and simulation. Computational modeling has been successfully applied as an aid for metabolic engineering in microorganisms. But such model-based approaches have only recently been extended to plant metabolic engineering, mainly due to greater pathway complexity in plants and their highly compartmentalized cellular structure. Recent progress in plant systems biology and bioinformatics has begun to disentangle this complexity and facilitate the creation of efficient plant metabolic models. This review highlights several aspects of plant metabolic modeling in the context of understanding, predicting and modifying complex plant metabolism. We discuss opportunities for engineering photosynthetic carbon metabolism, sucrose synthesis, and the tricarboxylic acid cycle in leaves and oil synthesis in seeds and the application of metabolic modeling to the study of plant acclimation to the environment. The aim of the review is to offer a current perspective for plant biologists without requiring specialized knowledge of bioinformatics or systems biology.     

Computational Biology Methods and Their Application to the Comparative Genomics of Endocellular Symbiotic Bacteria of Insects

Comparative genomics has become a real tantalizing challenge in the postgenomic era. This fact has been mostly magnified by the plethora of new genomes becoming available in a daily bases. The overwhelming list of new genomes to compare has pushed the field of bioinformatics and computational biology forward toward the design and development of methods capable of identifying patterns in a sea of swamping data noise. Despite many advances made in such endeavor, the ever-lasting annoying exceptions to the general patterns remain to pose difficulties in generalizing methods for comparative genomics. In this review, we discuss the different tools devised to undertake the challenge of comparative genomics and some of the exceptions that compromise the generality of such methods. We focus on endosymbiotic bacteria of insects because of their genomic dynamics peculiarities when compared to free-living organisms.     

Understanding the yeast proteome: a bioinformatics perspective

Rapid development of genomic and proteomic methodologies has provided a wealth of data for deciphering the biomolecular circuitry of a living cell. The main areas of computational research of proteomes outlined in this review are: understanding the system, its features and parameters to help plan the experiments; data integration, to help produce more reliable data sets; visualization and other forms of data representation to simplify interpretation; modeling of the functional regulation; and systems biology. With false-positive rates reaching 50% even in the more reliable data sets, handling the experimental error remains one of the most challenging tasks. Integrative approaches, incorporating results of various genome- and proteome-wide experiments, allow for minimizing the error and bring with them significant predictive power.     

比较遗传学介绍

随着遗传作图的不断发展,人们开始比较不同物种的基因组,并且揭示了一种从未被发现的基因组水平上基因排列顺序的保守性。随之,发展出比较遗传学概念：研究基因的排列顺序和基因数量的学科。比较遗传学已经被应用于植物基因组的基因定位,并预示出进化研究的一个全新领域。目前,比较遗传学和狭义的比较基因组学相互渗透和融合,形成一门新的学科,它将大大加深人们对基因组的理解。 Abstract：With the advance of genetic mapping and comparin g of different genomes,an undiscovered type of conservation was revealed: the co nservation of gene content and gene orders on the genome level. And it lodged th e concept of comparative genetics:the science that studies gene content and gene orders. Now comparative genetics has been used to facilitate the isolation of g ene, and it indicates a new field of evolution. This review discuses the develop ment of comparative genetics.In the future, comparative genetics and comparative genomics would be probably syncretize to be a new science, and it will deepen t he understanding of genomes.?     

Ecological and evolutionary genomics of Saccharomyces cerevisiae

Saccharomyces cerevisiae, the budding yeast, is the most thoroughly studied eukaryote at the cellular, molecular, and genetic levels. Yet, until recently, we knew very little about its ecology or population and evolutionary genetics. In recent years, it has been recognized that S. cerevisiae occupies numerous habitats and that populations harbour important genetic variation. There is therefore an increasing interest in understanding the evolutionary forces acting on the yeast genome. Several researchers have used the tools of functional genomics to study natural isolates of this unicellular fungus. Here, we review some of these studies, and show not only that budding yeast is a prime model system to address fundamental molecular and cellular biology questions, but also that it is becoming a powerful model species for ecological and evolutionary genomics studies as well.     

Understanding the yeast proteome: a bioinformatics perspective

Rapid development of genomic and proteomic methodologies has provided a wealth of data for deciphering the biomolecular circuitry of a living cell. The main areas of computational research of proteomes outlined in this review are: understanding the system, its features and parameters to help plan the experiments; data integration, to help produce more reliable data sets; visualization and other forms of data representation to simplify interpretation; modeling of the functional regulation; and systems biology. With false-positive rates reaching 50% even in the more reliable data sets, handling the experimental error remains one of the most challenging tasks. Integrative approaches, incorporating results of various genome- and proteome-wide experiments, allow for minimizing the error and bring with them significant predictive power.     

Understanding Spatial Genome Organization:Methods and Insights

The manner by which eukaryotic genomes are packaged into nuclei while maintaining crucial nuclear functions remains one of the fundamental mysteries in biology. Over the last ten years, we have witnessed rapid advances in both microscopic and nucleic acid-based approaches to map genome architecture, and the application of these approaches to the dissection of higher-order chromosomal structures has yielded much new information. It is becoming increasingly clear, for example, that interphase chromosomes form stable, multilevel hierarchical structures. Among them, self-associating domains like so-called topologically associating domains (TADs) appear to be building blocks for large-scale genomic organization. This review describes features of these broadly-defined hierarchical structures, insights into the mechanisms underlying their formation, our current understanding of how interactions in the nuclear space are linked to gene regulation, and important future directions for the field.