scholarly journals Population genomic scans reveal novel genes underlie convergent flowering time evolution in the introduced range of Arabidopsis thaliana

2015 ◽  
Author(s):  
Billie Gould ◽  
John R Stinchcombe
Keyword(s):  
Arabidopsis Thaliana ◽  
Flowering Time ◽  
Evolutionary Biology ◽  
Parallel Evolution ◽  
Native Range ◽  
Genetic Components ◽  
Introduced Range ◽  
Selection For ◽  
Native And Introduced Ranges ◽  
High Degree

A long-standing question in evolutionary biology is whether the evolution of convergent phenotypes results from selection on the same heritable genetic components. Using whole genome sequencing and genome scans, we tested whether the evolution of parallel longitudinal flowering time clines in the native and introduced ranges of Arabidopsis thaliana has a similar genetic basis. We found that common variants of large effect on flowering time in the native range do not appear to have been under recent strong selection in the introduced range. Genes in regions of the genome that are under selection for flowering time are also not enriched for functions related to development or environmental sensing. We instead identified a set of 53 new candidate genes putatively linked to the evolution of flowering time in the species introduced range. A high degree of conditional neutrality of flowering time variants between the native and introduced range may preclude parallel evolution at the level of genes. Overall, neither gene pleiotropy nor available standing genetic variation appears to have restricted the evolution of flowering time in the introduced range to high frequency variants from the native range or to known flowering time pathway genes.

scholarly journals Fine-scale Population Structure of North American Arabidopsis thaliana Reveals Multiple Sources of Introduction from Across Eurasia

2021 ◽  
Author(s):  
Gautam Shirsekar ◽  
Jane Devos ◽  
Sergio M. Latorre ◽  
Andreas Blaha ◽  
Maique Queiroz Dias ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Arabidopsis Thaliana ◽  
Population Structure ◽  
North American ◽  
Native Species ◽  
Large Scale ◽  
Haplotype Diversity ◽  
Native Range ◽  
Haplotypic Diversity ◽  
Introduced Range

AbstractLarge-scale movement of organisms across their habitable range, or migration, is an important evolutionary process that can contribute to observed patterns of genetic diversity and our understanding of the adaptive spread of alleles. While human migrations have been studied in great detail with modern and ancient genomes, recent anthropogenic influence on reducing the biogeographical constraints on the migration of non-native species has presented opportunities in several study systems to ask the questions about how repeated introductions shape genetic diversity in the introduced range. We present here the most comprehensive view of population structure of North American Arabidopsis thaliana by studying a set of 500 (whole-genome sequenced) and over 2800 (RAD-seq genotyped) individuals in the context of global diversity represented by Afro-Eurasian genomes. We use haplotype-sharing, phylogenetic modeling and rare-allele sharing based methods to identify putative sources of introductions of extant N. American A. thaliana from the native range of Afro-Eurasia. We find evidence of admixture among the introduced lineages that has resulted in the increased haplotype diversity and reduced mutational load. Further, we also present signals of selection in the immune-system related genes that impart qualitative disease resistance to pathogens of bacterial and oomycete origins. Thus, multiple introductions to a non-native range can quickly increase adaptive potential of a colonizing species by increasing haplotypic diversity through admixture. The results presented here lay the foundation for further investigations into the functional significance of admixture.

scholarly journals Regional Differences in the Structure of Juglans nigra Phytobiome Reflect Geographical Differences in Thousand Cankers Disease Severity

2020 ◽  
Vol 4 (4) ◽  
pp. 388-404
Author(s):  
Aaron J. Onufrak ◽  
Geoffrey M. Williams ◽  
William E. Klingeman ◽  
Melissa A. Cregger ◽  
Dawn M. Klingeman ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Geographical Variation ◽  
Disease Incidence ◽  
Juglans Nigra ◽  
Native Range ◽  
Geographical Differences ◽  
Thousand Cankers Disease ◽  
Introduced Range ◽  
Native And Introduced Ranges

Thousand cankers disease threatens Juglans nigra (Eastern Black Walnut) in urban and natural landscapes. Incidence and severity of thousand cankers disease is higher in the host’s introduced range in the western United States. We hypothesized that these differences are driven partly by geographical variation in the host phytobiome due to its roles in host stress tolerance, nutrient acquisition, and defense. To evaluate the role of the phytobiome in mediating thousand cankers disease, we characterized the J. nigra phytobiome of diseased and healthy trees in portions of its native (Indiana and Tennessee) and introduced (Washington) ranges. Grafted clones present in each state and open-pollinated populations were sampled. DNA was extracted from soil and branch (caulosphere) tissues and internal transcribed spacer and 16s regions were sequenced for characterization of fungal and bacterial communities. We found that microbial communities in the caulosphere and soil differ between native and introduced ranges of J. nigra and harbor different mutualistic and pathogenic microorganisms. Additionally, caulosphere microbial communities were more species rich and diverse in the native range of J. nigra, suggesting greater levels of functional redundancy and multifunctionality in the native-range phytobiome compared with the introduced range. We also found higher network complexity in the caulosphere of trees in the introduced range and evidence for two alternative stable community states associated with diseased and healthy trees. Our results provide support for the hypothesis that geographical variation in thousand cankers disease incidence and severity is partially driven by differences in the phytobiome of J. nigra in its introduced and native ranges. [Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

INHERITANCE OF FLOWERING TIME AND ITS APPLICATION FOR INDIRECT SELECTION IN THE DAVIS POPULATION OF GERBERA

HortScience ◽  
1990 ◽  
Vol 25 (11) ◽  
pp. 1357F-1358
Author(s):  
Yiran Yu ◽  
James Harding ◽  
Thomas Byrne
Keyword(s):  
Flowering Time ◽  
Genetic Correlations ◽  
Indirect Selection ◽  
Cut Flower ◽  
Narrow Sense ◽  
Narrow Sense Heritability ◽  
Components Of Variance ◽  
Genetic Components ◽  
Flower Yield ◽  
Cut Flower Yield

Genetic components of variance and heritability of flowering time were estimated for five generations of the Davis Populationof Gerbera hybrids, Composite, Estimates of narrow-sense heritability averaged 0.50 and broad-sense heritability averaged 0.77 using the NCII design. Narrow-sense heritability was also estimated with two models of parent-offspring regression, resulting in average heritability of 0.49 and 0.51. Estimates of components of variance indicated that the major genetic effect controlling flowering time is additive. However, the dominance component accounted for 28% of the total variance; the environmental component was only 23%. Flowering time is negatively correlated with cut-flower yield. The phenotypic coefficient was –0.34; genetic correlations were –0.47 when estimated from the NCII design, and –0.72 when estimated from the parent-off-spring method. A practical model was constructed to assess the efficiency of indirect selection for cut-flower yield using flowering time as a marker trait. The advantages of indirect selection accruing from increased population size and reduced generation time are discussed.

scholarly journals Thinking Globally, Acting Locally: Distantly Supervised Global-to-Local Knowledge Selection for Background Based Conversation

2020 ◽  
Vol 34 (05) ◽  
pp. 8697-8704
Author(s):  
Pengjie Ren ◽  
Zhumin Chen ◽  
Christof Monz ◽  
Jun Ma ◽  
Maarten De Rijke
Keyword(s):  
Local Knowledge ◽  
State Of The Art ◽  
Background Knowledge ◽  
Global Perspective ◽  
Conversational Context ◽  
Human Evaluation ◽  
Text Fragment ◽  
Selection For ◽  
High Degree ◽  
Transition Vector

Background Based Conversation (BBCs) have been introduced to help conversational systems avoid generating overly generic responses. In a BBC, the conversation is grounded in a knowledge source. A key challenge in BBCs is Knowledge Selection (KS): given a conversational context, try to find the appropriate background knowledge (a text fragment containing related facts or comments, etc.) based on which to generate the next response. Previous work addresses KS by employing attention and/or pointer mechanisms. These mechanisms use a local perspective, i.e., they select a token at a time based solely on the current decoding state. We argue for the adoption of a global perspective, i.e., pre-selecting some text fragments from the background knowledge that could help determine the topic of the next response. We enhance KS in BBCs by introducing a Global-to-Local Knowledge Selection (GLKS) mechanism. Given a conversational context and background knowledge, we first learn a topic transition vector to encode the most likely text fragments to be used in the next response, which is then used to guide the local KS at each decoding timestamp. In order to effectively learn the topic transition vector, we propose a distantly supervised learning schema. Experimental results show that the GLKS model significantly outperforms state-of-the-art methods in terms of both automatic and human evaluation. More importantly, GLKS achieves this without requiring any extra annotations, which demonstrates its high degree of scalability.

A Statistical Predictive Model to Prioritize Site Selection for Stress Corrosion Cracking Direct Assessment

2006 ◽  
Author(s):  
Anthony Merle ◽  
P. F. Ehlers
Keyword(s):  
Stress Corrosion ◽  
Stress Corrosion Cracking ◽  
Environmental Parameters ◽  
Predictive Modelling ◽  
Corrosion Cracking ◽  
Direct Assessment ◽  
Degree Of Certainty ◽  
Regression Techniques ◽  
Selection For ◽  
High Degree

Pipeline stress-corrosion cracking (SCC) is an ongoing integrity concern for pipeline operators. A number of different strategies are currently employed to locate and mitigate SCC. Ultrasonic in-line inspection tools have proven capable of locating SCC, but reliability of these tools in gas pipelines remains in question. Rotating hydrotest programs are effectively employed by some companies but may not provide useful information as to the location of SCC along the pipeline. NACE Standard RP0204-2004 (SCC Direct Assessment Methodology) outlines factors to consider and methodologies to employ to predict where SCC is likely to occur, but even this document acknowledges that there are no well-established methods for predicting the presence of SCC with a high degree of certainty. Predictive modelling attempts to date have focused on establishing quantitative relationships between environmental factors and SCC formation and growth; these models have achieved varying degrees of success. A statistical approach to SCC predictive modelling has been developed. In contrast to previous models that attempted to determine direct correlations between environmental parameters and SCC, the new model statistically analyzed data from dig sites where SCC was and was not found. Regression techniques were used to create a multi-variable logistic regression model. The model was applied to the entire pipeline and verification digs were performed. The dig results indicated that the model was able to predict locations of SCC along the pipeline.

scholarly journals Natural Selection at an Exceptionally Long GGC Repeat in the Human RASGEF1C and Divergent Genotypes in Late-onset Neurocognitive Disorder

2021 ◽  
Author(s):  
Z Jafarian ◽  
S Khamse ◽  
H Afshar ◽  
Khorram Khorshid HR ◽  
A Delbari ◽  
...  
Keyword(s):  
Natural Selection ◽  
Evolutionary Biology ◽  
Late Onset ◽  
Core Promoter ◽  
Human Subjects ◽  
Specific Gene ◽  
Protein Coding ◽  
Repeat Allele ◽  
Complex Disorders ◽  
Selection For

Abstract Across the human protein-coding genes, the neuron-specific gene, RASGEF1C, contains the longest (GGC)-repeat, spanning its core promoter and 5′ untranslated region (RASGEF1C-201 ENST00000361132.9). RASGEF1C expression dysregulation occurs in late-onset neurocognitive disorders (NCDs), such as Alzheimer’s disease. Here we sequenced the GGC-repeat in a sample of human subjects (N = 269), consisting of late-onset NCDs (N = 115) and controls (N = 154). We also studied the status of this STR across vertebrates. The 6-repeat allele of this repeat was the predominant allele in the controls (frequency = 0.85) and NCD patients (frequency = 0.78). The NCD genotype compartment consisted of an excess of genotypes that lacked the 6-repeat (Mid-P exact = 0.004). We also detected divergent genotypes that were present in five NCD patients and not in the controls (Mid-P exact = 0.007). This STR expanded beyond 2-repeats specifically in primates, and was at maximum length in human. We conclude that there is natural selection for the 6-repeat allele of the RASGEF1C (GGC)-repeat in human, and significant divergence from that allele in late-onset NCDs. Indication of natural selection for predominantly abundant STR alleles and divergent genotypes enhance the perspective of evolutionary biology and disease pathogenesis in human complex disorders.

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