Advances in Genetics最新文献

The ABC protein superfamily-also called traffic ATPases-are energy-dependent ubiquitous proteins, representing one of the crucial and the largest family in the fungal genomes. The ATP-binding cassette endows a characteristic 200-250 amino acids and is omnipresent in all organisms ranging from prokaryotes to eukaryotes. Unlike in bacteria with nutrient import functions, ABC transporters in fungal entomopathogens serve as effective efflux pumps that are largely involved in the shuttle of metabolites across the biological membranes. Thus, the search for ABC proteins may prove of immense importance in elucidating the functional and molecular mechanism at the host-pathogen (insect-fungus) interface. Their sequence homology, domain topology, and functional traits led to the actual identification of nine different families in fungal entomopathogens. Evolutionary relationships within the ABC superfamily are discussed, concentrating on computational approaches for comparative identification of ABC transporters in insect-pathogenic fungi (entomopathogens) with those of animals, plants, and their bacterial orthologs. Ancestors of some fungal candidates have duplicated extensively in some phyla, while others were lost in one lineage or the other, and predictions for the cause of their duplications and/or loss in some phyla are made. ABC transporters of fungal insect-pathogens serve both defensive and offensive functions effective against land-dwelling and ground foraging voracious insects. This study may help to unravel the molecular cascades of ABC proteins to illuminate the means through which insects cope with fungal infection and fungal-related diseases.

In the past decade, advances in next-generation sequencing technologies and bioinformatic pipelines for phylogenomic analysis have led to remarkable progress in fungal systematics and taxonomy. A number of long-standing questions have been addressed using comparative analysis of genome sequence data, resulting in robust multigene phylogenies. These have added to, and often surpassed traditional morphology or single-gene phylogenetic methods. In this chapter, we provide a brief history of fungal systematics and highlight some examples to demonstrate the impact of phylogenomics on this field. We conclude by discussing some of the challenges and promises in fungal biology posed by the ongoing genomics revolution.

Since its original inception over 150 years ago by Darwin, we have made tremendous progress toward the reconstruction of the Tree of Life. In particular, the transition from analyzing datasets comprised of small numbers of loci to those comprised of hundreds of loci, if not entire genomes, has aided in resolving some of the most vexing of evolutionary problems while giving us a new perspective on biodiversity. Correspondingly, phylogenetic trees have taken a central role in fields that span ecology, conservation, and medicine. However, the rise of big data has also presented phylogenomicists with a new set of challenges to experimental design, quantitative analyses, and computation. The sequencing of a number of very first genomes presented significant challenges to phylogenetic inference, leading fungal phylogenomicists to begin addressing pitfalls and postulating solutions to the issues that arise from genome-scale analyses relevant to any lineage across the Tree of Life. Here we highlight insights from fungal phylogenomics for topics including systematics and species delimitation, ecological and phenotypic diversification, and biogeography while providing an overview of progress made on the reconstruction of the fungal Tree of Life. Finally, we provide a review of considerations to phylogenomic experimental design for robust tree inference. We hope that this special issue of Advances in Genetics not only excites the continued progress of fungal evolutionary biology but also motivates the interdisciplinary development of new theory and methods designed to maximize the power of genomic scale data in phylogenetic analyses.

Rust fungi (Pucciniales) are the most speciose and the most complex group of plant pathogens. Historically, rust taxonomy was largely influenced by host and phenotypic characters, which are potentially plastic. Molecular systematic studies suggest that the extant diversity of this group was largely shaped by host jumps and subsequent shifts. However, it has been challenging to reconstruct the evolutionary history for the order, especially at deeper (family-level) nodes. Phylogenomics offer a potentially powerful tool to reconstruct the Pucciniales tree of life, although researchers working at this vanguard still face unprecedented challenges working with nonculturable organisms that possess some of the largest and most repetitive genomes now known in kingdom fungi. In this chapter, we provide an overview of the current status and special challenges of rust genomics, and we highlight how phylogenomics may provide new perspectives and answer long-standing questions regarding the biology of rust fungi.

The genomic era has been transformative for many fields, including our understanding of the phylogenetic relationships between organisms. The wide availability of whole-genome sequences practically eliminated data availability as a limiting factor for inferring phylogenetic trees, providing hundreds to thousands of loci for analyses, leading to molecular phylogenetics gradually being replaced by phylogenomics. The new era has also brought new challenges: systematic errors (resulting from, e.g., model violation) can be more pronounced in phylogenomic datasets and can lead to strongly supported incorrect relationships, creating significant incongruence among studies. Here, we review common practices, technical and biological challenges of phylogenomic analyses, with examples illustrated from fungi. We compare major approaches of phylogenetic inference, and illustrate the advantages conferred and challenges presented in phylogenomic case studies across the fungal tree of life, including cases where genome-scale data could conclusively resolve contentious relationships, and others that remain challenging despite the flood of genomic data.

An unprecedented number of pathogenic fungi are emerging and causing disease in animals and plants, putting the resilience of wild and managed ecosystems in jeopardy. While the past decades have seen an increase in the number of pathogenic fungi, they have also seen the birth of new big data technologies and analytical approaches to tackle these emerging pathogens. We review how the linked fields of genomics and epigenomics are transforming our ability to address the challenge of emerging fungal pathogens. We explore the methodologies and bioinformatic toolkits that currently exist to rapidly analyze the genomes of unknown fungi, then discuss how these data can be used to address key questions that shed light on their epidemiology. We show how genomic approaches are leading a revolution into our understanding of emerging fungal diseases and speculate on future approaches that will transform our ability to tackle this increasingly important class of emerging pathogens.

The genetics toolkit is pretty successful in drilling down into minutiae. The big challenge is to integrate the information from this specialty as well as those of biochemistry, physiology, behavior, and anatomy to explain how fundamental biological processes really work. Sleep, the circadian clock and development all qualify as overarching processes that encompass levels from molecule to behavior as part of their known mechanisms. They overlap each other, such that understanding the mechanisms of one can lead to insights into one of the others. In this essay, we consider how the experimental approaches and findings relating to Caenorhabditis elegans development and lethargus on one hand, and to the circadian clock and sleep in higher organisms on the other, could complement and enhance one another.

Mitochondria are intracellular organelles responsible for adenosine triphosphate production. The strict control of intracellular energy needs require proper mitochondrial functioning. The mitochondria are under dual controls of mitochondrial DNA (mtDNA) and nuclear DNA (nDNA). Mitochondrial dysfunction can arise from changes in either mtDNA or nDNA genes regulating function. There are an estimated ∼1500 proteins in the mitoproteome, whereas the mtDNA genome has 37 proteins. There are, to date, ∼275 genes shown to give rise to disease. The unique physiology of mitochondrial functioning contributes to diverse gene expression. The onset and range of phenotypic expression of disease is diverse, with onset from neonatal to seventh decade of life. The range of dysfunction is heterogeneous, ranging from single organ to multisystem involvement. The complexity of disease expression has severely limited gene discovery. Combining phenotypes with improvements in gene sequencing strategies are improving the diagnosis process. This chapter focuses on the interplay of the unique physiology and gene discovery in the current knowledge of genetically derived mitochondrial disease.

Phenotype is defined as the state of an organism resulting from interactions between genes, environment, disease, molecular mechanisms, and chance. The purpose of the emerging field of phenomics is to systematically determine and measure phenotypes across biology for the sake of understanding. Phenotypes can affect more than one cell type and life stage, so ideal phenotyping would include the state of every cell type within the context of both tissue architecture and the whole organism at each life stage. In medicine, high-resolution anatomic assessment of phenotype is obtained from histology. Histology's interpretative power, codified by Virchow as cellular pathology, is derived from its ability to discern diagnostic and characteristic cellular changes in diseased tissues. Cellular pathology is observed in every major human disease and relies on the ability of histology to detect cellular change in any cell type due to unbiased pan-cellular staining, even in optically opaque tissues. Our laboratory has shown that histology is far more sensitive than stereomicroscopy for detecting phenotypes in zebrafish mutants. Those studies have also shown that more complete sampling, greater consistency in sample orientation, and the inclusion of phenotypes extending over longer length scales would provide greater coverage of common phenotypes. We are developing technical approaches to achieve an ideal detection of cellular pathology using an improved form of X-ray microtomography that retains the strengths and addresses the weaknesses of histology as a screening tool. We are using zebrafish as a vertebrate model based on the overlaps between zebrafish and mammalian tissue architecture, and a body size small enough to allow whole-organism, volumetric imaging at cellular resolution. Automation of whole-organism phenotyping would greatly increase the value of phenomics. Potential societal benefits would include reduction in the cost of drug development, a reduction in the incidence of unexpected severe drug and environmental toxicity, and more rapid elucidation of the contributions of genes and the environment to phenotypes, including the validation of candidate disease alleles identified in population and personal genetics.