Population Genomics of Plant Viruses: The Ecology and Evolution of Virus Emergence

2020 ◽  
pp. PHYTO-08-20-035
Author(s):  
Michael J. McLeish ◽  
Aurora Fraile ◽  
Fernando García-Arenal
Keyword(s):  
Multidisciplinary Approach ◽  
Population Genomics ◽  
Disease Risk ◽  
Plant Viruses ◽  
Computational Tools ◽  
Natural Systems ◽  
Large Numbers ◽  
Demographic Processes ◽  
Genetic Mechanisms ◽  
Virus Emergence

The genomics era has revolutionized studies of adaptive evolution by monitoring large numbers of loci throughout the genomes of many individuals. Ideally, the investigation of emergence in plant viruses requires examining the population dynamics of both virus and host, their interactions with each other, with other organisms and the abiotic environment. Genetic mechanisms that affect demographic processes are now being studied with high-throughput technologies, traditional genetics methods, and new computational tools for big-data. In this review, we discuss the utility of these approaches to monitor and detect changes in virus populations within cells and individuals, and over wider areas across species and communities of ecosystems. The advent of genomics in virology has fostered a multidisciplinary approach to tackling disease risk. The ability to make sense of the information now generated in this integrated setting is by far the most substantial obstacle to the ultimate goal of plant virology to minimize the threats to food security posed by disease. To achieve this goal, it is imperative to understand and forecast how populations respond to future changes in complex natural systems.

scholarly journals Comparative Analysis of SNP Discovery and Genotyping in Fagus sylvatica L. and Quercus robur L. Using RADseq, GBS, and ddRAD Methods

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 222
Author(s):  
Bartosz Ulaszewski ◽  
Joanna Meger ◽  
Jaroslaw Burczyk
Keyword(s):  
Population Genomics ◽  
De Novo ◽  
Genetic Studies ◽  
Genomic Libraries ◽  
Reduced Representation ◽  
Large Numbers ◽  
Broadleaved Tree Species ◽  
Fagus Sylvatica L ◽  
Reference Genomes ◽  
Future Population

Next-generation sequencing of reduced representation genomic libraries (RRL) is capable of providing large numbers of genetic markers for population genetic studies at relatively low costs. However, one major concern of these types of markers is the precision of genotyping, which is related to the common problem of missing data, which appears to be particularly important in association and genomic selection studies. We evaluated three RRL approaches (GBS, RADseq, ddRAD) and different SNP identification methods (de novo or based on a reference genome) to find the best solutions for future population genomics studies in two economically and ecologically important broadleaved tree species, namely F. sylvatica and Q. robur. We found that the use of ddRAD method coupled with SNP calling based on reference genomes provided the largest numbers of markers (28 k and 36 k for beech and oak, respectively), given standard filtering criteria. Using technical replicates of samples, we demonstrated that more than 80% of SNP loci should be considered as reliable markers in GBS and ddRAD, but not in RADseq data. According to the reference genomes’ annotations, more than 30% of the identified ddRAD loci appeared to be related to genes. Our findings provide a solid support for using ddRAD-based SNPs for future population genomics studies in beech and oak.

Evaluation of the Risk of Therapy-Associated Complications in Survivors of Hodgkin Lymphoma

Hematology ◽  
2007 ◽  
Vol 2007 (1) ◽  
pp. 192-196 ◽  
Author(s):  
Lois B. Travis
Keyword(s):  
Hodgkin Lymphoma ◽  
Health Care Providers ◽  
Late Effects ◽  
Disease Risk ◽  
Risk Measures ◽  
Epidemiologic Study ◽  
Incidence Rates ◽  
Care Providers ◽  
Large Numbers ◽  
Study Designs

Abstract Given the improvements in survival of patients with Hodgkin lymphoma (HL) in the last three decades, quantification of the late effects of successful treatment has become critical. Since the highest incidence rates of HL occur at ages 20 to 34 years, large numbers of patients remain at lifelong risk for the late effects of treatment. Deaths due to second cancers are now the most common cause of mortality among long-term survivors of HL, followed by cardiac disease. Risk measures of these and other late sequelae, however, can vary markedly between investigations, depending on the types of treatment, the rigor with which epidemiologic study designs are applied, ascertainment of events of interest, the duration and completeness of follow-up, and consideration of competing risks. Further, numerous influences apart from therapy can affect late effects, including patient age, sex, race, lifestyle factors (tobacco, alcohol, diet), comorbidities, and the underlying cancer process. In the future, it will become increasingly important for health-care providers to be able to critically evaluate the risk of late effects in HL survivors, which will include a working knowledge of various epidemiologic study designs and risk measures and an ability to judiciously review the medical literature. In this article, the methods, significance and caveats in calculating and reporting risks of complications of treatment for HL are reviewed.

scholarly journals Methodological Guidelines for Accurate Detection of Viruses in Wild Plant Species

2016 ◽  
Vol 82 (6) ◽  
pp. 1966-1975 ◽  
Author(s):  
Christelle Lacroix ◽  
Kurra Renner ◽  
Ellen Cole ◽  
Eric W. Seabloom ◽  
Elizabeth T. Borer ◽  
...  
Keyword(s):  
Plant Species ◽  
Disease Risk ◽  
Virus Detection ◽  
Plant Viruses ◽  
Wild Plants ◽  
Wild Plant ◽  
Content Type ◽  
Wild Plant Species ◽  
Methodological Guidelines ◽  
Wild Hosts

ABSTRACTEcological understanding of disease risk, emergence, and dynamics and of the efficacy of control strategies relies heavily on efficient tools for microorganism identification and characterization. Misdetection, such as the misclassification of infected hosts as healthy, can strongly bias estimates of disease prevalence and lead to inaccurate conclusions. In natural plant ecosystems, interest in assessing microbial dynamics is increasing exponentially, but guidelines for detection of microorganisms in wild plants remain limited, particularly so for plant viruses. To address this gap, we explored issues and solutions associated with virus detection by serological and molecular methods in noncrop plant species as applied to the globally importantBarley yellow dwarf virusPAV (Luteoviridae), which infects wild native plants as well as crops. With enzyme-linked immunosorbent assays (ELISA), we demonstrate how virus detection in a perennial wild plant species may be much greater in stems than in leaves, although leaves are most commonly sampled, and may also vary among tillers within an individual, thereby highlighting the importance of designing effective sampling strategies. With reverse transcription-PCR (RT-PCR), we demonstrate how inhibitors in tissues of perennial wild hosts can suppress virus detection but can be overcome with methods and products that improve isolation and amplification of nucleic acids. These examples demonstrate the paramount importance of testing and validating survey designs and virus detection methods for noncrop plant communities to ensure accurate ecological surveys and reliable assumptions about virus dynamics in wild hosts.

Life on the Edge: Geminiviruses at the Interface Between Crops and Wild Plant Hosts

2019 ◽  
Vol 6 (1) ◽  
pp. 411-433 ◽  
Author(s):  
Fernando García-Arenal ◽  
Francisco Murilo Zerbini
Keyword(s):  
Genetic Variation ◽  
Ecological Factors ◽  
Plant Viruses ◽  
Crop Plants ◽  
Wild Plants ◽  
Wild Plant ◽  
Cultivated Plants ◽  
Emerging Pathogens ◽  
Epidemiological Features ◽  
Virus Emergence

Viruses constitute the largest group of emerging pathogens, and geminiviruses (plant viruses with circular, single-stranded DNA genomes) are the major group of emerging plant viruses. With their high potential for genetic variation due to mutation and recombination, their efficient spread by vectors, and their wide host range as a group, including both wild and cultivated hosts, geminiviruses are attractive models for the study of the evolutionary and ecological factors driving virus emergence. Studies on the epidemiological features of geminivirus diseases have traditionally focused primarily on crop plants. Nevertheless, knowledge of geminivirus infection in wild plants, and especially at the interface between wild and cultivated plants, is necessary to provide a complete view of their ecology, evolution, and emergence. In this review, we address the most relevant aspects of geminivirus variability and evolution in wild and crop plants and geminiviruses’ potential to emerge in crops.

scholarly journals Competitive Displacement between Bemisia tabaci MEAM1 and MED and Evidence for Multiple Invasions of MED

Insects ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 35
Author(s):  
Xiao-Tian Tang ◽  
Li Cai ◽  
Yuan Shen ◽  
Li-Li Xu ◽  
Yu-Zhou Du
Keyword(s):  
Bemisia Tabaci ◽  
Mitochondrial Gene ◽  
Economic Loss ◽  
Plant Viruses ◽  
Competitive Displacement ◽  
Severe Damage ◽  
Large Numbers ◽  
Multiple Introduction ◽  
Invasive Whitefly ◽  
Multiple Invasions

Despite the severe ecological damage and economic loss caused by invasive species, the factors contributing to successful invasion or displacement remain elusive. The whitefly, Bemisia tabaci (Gennadius), is an important invasive agricultural pest worldwide, causing severe damage to numerous crops by feeding or transmitting plant viruses. In this study, we monitored the dynamics of two invasive whitefly cryptic species, Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED), in Jiangsu, China, from 2005–2016. We found that B. tabaci MED quickly established and asserted dominance over MEAM1, resulting in their population displacement in Jiangsu in only three years (from 2005 to 2008). We further investigated the possible mechanisms underlying the successful invasion and competitive displacement from a genetic perspective. Based on sequencing of mitochondrial gene sequences from large numbers of whitefly samples, multiple invasion events of MED were validated by our genetic analyses. MED invaded Jiangsu starting from multiple introduction sites with secondary and/or subsequent invasive events. This may favor their invasion and displacement of MEAM1. This study advances our understanding of the mechanisms that enabled the successful invasion of MED.

scholarly journals Familial heterogeneity in breast cancer predisposition: a study of 22 Utah families

2016 ◽  
Author(s):  
Elizabeth O’Brien ◽  
Richard A. Kerber ◽  
Raymond L. White
Keyword(s):  
Breast Cancer ◽  
Rare Variants ◽  
Disease Risk ◽  
Breast Cancer Predisposition ◽  
Large Numbers ◽  
Genome Wide ◽  
A Genome ◽  
Medium Risk ◽  
Genomic Regions ◽  
Marker Spacing

AbstractThe problem of “missing heritability” in genome-wide analyses of complex diseases is thought to be attributable to some combination of: rare variants of moderate to large effect, common variants of very small effect, and epigenetic, epistatic, or shared environmental effects. Rare variants do not affect large numbers of people by definition, but identified genes and pathways frequently lead to important insights into pathogenesis, and become targets of chemoprevention or therapy. Family studies remain an efficient way to identify rare variants with sizable effects on disease risk. We present a genome-wide study of breast cancer in 22 large high-risk families including 154 women diagnosed with breast cancer. Appropriate marker spacing was achieved by simulation studies of founder haplotypes to reduce the chance that linkage disequilibrium produced spurious linkage peaks. For each family, we generated 100 simulations of null linkage genome-wide to estimate the probability that individual results were due to chance. We identified a total of 12 putative susceptibility regions with per-family genome-wide probability < 0.05. These regions were located on 10 chromosomes; 10 of the 22 families showed linkage at these locations; two or more families showed linkage to 6 regions on 5 chromosomes (4q, 5q, 6p, 14q, 18p, and 18q). These results indicate that there is considerable heterogeneity among families in genomic regions and thus variants predisposing to breast cancer. Moreover, they suggest that uncommon high– or medium-risk genetic variants remain to be found, and that family designs can be an efficient way to identify them.

scholarly journals An insight into osteoarthritis susceptibility: Integration of immunological and genetic background

2020 ◽  
Author(s):  
Debora Stefik ◽  
Vladimir Vranic ◽  
Nemanja Ivkovic ◽  
Dzihan Abazovic ◽  
Dusan Maric ◽  
...  
Keyword(s):  
Risk Factors ◽  
Early Onset ◽  
Genetic Background ◽  
Disease Risk ◽  
Joint Disease ◽  
Inflammatory Joint Disease ◽  
Complex Interplay ◽  
Diarthrodial Joints ◽  
Genetic Mechanisms ◽  
Insight Into

Osteoarthritis (OA) is a progressive degenerative disease that affects all synovial joints, causing the disability of the main locomotor diarthrodial joints. OA pathogenesis is caused by a complex interplay between a number of genetic and environmental risk factors, involved in the early onset and progression of this chronic inflammatory joint disease. Uncovering the underlying immunological and genetic mechanisms will enable an insight into OA pathophysiology and lead to novel and integrative approaches in the treatment of OA patients, together with a reduction of the disease risk, or a delay of its onset in susceptible patients.

scholarly journals Uncovering the genetic blueprint of the C. elegans nervous system

2020 ◽  
Vol 117 (52) ◽  
pp. 33570-33577
Author(s):  
István A. Kovács ◽  
Dániel L. Barabási ◽  
Albert-László Barabási
Keyword(s):  
Gene Expression ◽  
Expression Profiling ◽  
Expression Patterns ◽  
Computational Framework ◽  
Computational Tools ◽  
C Elegans ◽  
Junction Formation ◽  
Cell Gene Expression ◽  
Genetic Mechanisms ◽  
Cell Gene

Despite rapid advances in connectome mapping and neuronal genetics, we lack theoretical and computational tools to unveil, in an experimentally testable fashion, the genetic mechanisms that govern neuronal wiring. Here we introduce a computational framework to link the adjacency matrix of a connectome to the expression patterns of its neurons, helping us uncover a set of genetic rules that govern the interactions between neurons in contact. The method incorporates the biological realities of the system, accounting for noise from data collection limitations, as well as spatial restrictions. The resulting methodology allows us to infer a network of 19 innexin interactions that govern the formation of gap junctions in Caenorhabditis elegans, five of which are already supported by experimental data. As advances in single-cell gene expression profiling increase the accuracy and the coverage of the data, the developed framework will allow researchers to systematically infer experimentally testable connection rules, offering mechanistic predictions for synapse and gap junction formation.

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