scholarly journals Spatial proximity determines post-speciation introgression in Solanum

2019 ◽  
Author(s):  
Jennafer A. P. Hamlin ◽  
Leonie C. Moyle
Keyword(s):  
Hypothesis Testing ◽  
Mating System ◽  
Genetic Relatedness ◽  
A Priori ◽  
Spatial Proximity ◽  
Geographical Proximity ◽  
Whole Genome ◽  
Relative Importance ◽  
Testing Framework ◽  
General Importance

ABSTRACTAn increasing number of phylogenomic studies have documented a clear ‘footprint’ of post-speciation introgression among closely-related species. Nonetheless, systematic genome-wide studies of factors influencing the likelihood of introgression remain rare. Here, we use an a priori hypothesis-testing framework, and introgression statistics, to evaluate the prevalence and frequency of introgression. Specifically, with whole genome sequences from 32 lineages of wild tomato species, we assess the effect of three factors on introgression: genetic relatedness, geographical proximity, and mating system differences. Using multiple trios within the ‘ABBA-BABA’ test, we find that one of our factors, geographic proximity, is consistently associated with evidence for recent introgression between species. Of 14 species pairs with ‘proximate’ versus ‘distant’ population comparisons, 12 showed evidence of introgression; in ten of these cases, this was more prevalent between geographically-closer populations. We found no evidence that introgression varies systematically with increasing genetic divergence between lineages or with mating system differences, although we have limited power to address the latter effect. While our analysis indicates that recent post-speciation introgression is frequent in this group, estimated levels of genetic exchange are modest (0.05-1.5% of the genome), so the relative importance of hybridization in shaping the evolutionary trajectories of these species could be limited. Regardless, similar clade-wide analyses of genomic introgression would be valuable for disentangling the major ecological, reproductive, and historical determinants of post-speciation gene flow, and for assessing the relative importance of introgression as a source of evolutionary change.IMPACT STATEMENTThe formation of new species is traditionally viewed as a tree-like branching process, in which species are discrete branches that no longer share an ongoing genealogical connection with other, equally discrete, species. Recently this view has been challenged by numerous studies examining genealogical patterns across entire genomes (all the DNA of an organism); these studies suggest that the exchange of genes between different species (known as ‘introgression’) is much more common than previously appreciated. This unexpected observation raises questions about which conditions are most important in determining whether species continue to exchange genes after they diverge. Factors such as physical proximity, differences in reproductive mechanisms, and time since species shared a common ancestor, might all contribute to determining the prevalence of introgression. But to evaluate the general importance of these factors requires more than individual cases; many species comparisons, that differ systematically in one or more of these conditions, are needed. Here we use whole-genome information from 32 lineages to evaluate patterns of introgression among multiple species in a single, closely related group—the wild tomatoes of south America. We contrast these patterns among pairs of lineages that differ in their geographical proximity, reproductive system, and time since common ancestry, to assess the individual influence of each condition on the prevalence of introgression. We find that only one of our factors—geographical proximity—is consistently associated with greater evidence for recent introgression, indicating that this is largely shaped by the geographical opportunity for hybridization, rather than other plausible biological processes. Our study is one of the first to systematically assess the influence of general ecological and evolutionary conditions on the frequency of post-speciation introgression. It also provides a straightforward, generalizable, hypothesis-testing framework for similar systematic analyses of introgression in groups of other organisms in the future.

scholarly journals Constructing Adaptive Deformation Models for Estimating DEM Error in SBAS-InSAR Based on Hypothesis Testing

2021 ◽  
Vol 13 (10) ◽  
pp. 2006
Author(s):  
Jun Hu ◽  
Qiaoqiao Ge ◽  
Jihong Liu ◽  
Wenyan Yang ◽  
Zhigui Du ◽  
...  
Keyword(s):  
Time Series ◽  
Hypothesis Testing ◽  
Surface Deformation ◽  
A Priori ◽  
Least Square ◽  
Deformation Model ◽  
Phase Time ◽  
Testing Theory ◽  
Sbas Insar ◽  
Deformation Models

The Interferometric Synthetic Aperture Radar (InSAR) technique has been widely used to obtain the ground surface deformation of geohazards (e.g., mining subsidence and landslides). As one of the inherent errors in the interferometric phase, the digital elevation model (DEM) error is usually estimated with the help of an a priori deformation model. However, it is difficult to determine an a priori deformation model that can fit the deformation time series well, leading to possible bias in the estimation of DEM error and the deformation time series. In this paper, we propose a method that can construct an adaptive deformation model, based on a set of predefined functions and the hypothesis testing theory in the framework of the small baseline subset InSAR (SBAS-InSAR) method. Since it is difficult to fit the deformation time series over a long time span by using only one function, the phase time series is first divided into several groups with overlapping regions. In each group, the hypothesis testing theory is employed to adaptively select the optimal deformation model from the predefined functions. The parameters of adaptive deformation models and the DEM error can be modeled with the phase time series and solved by a least square method. Simulations and real data experiments in the Pingchuan mining area, Gaunsu Province, China, demonstrate that, compared to the state-of-the-art deformation modeling strategy (e.g., the linear deformation model and the function group deformation model), the proposed method can significantly improve the accuracy of DEM error estimation and can benefit the estimation of deformation time series.

scholarly journals Iterative Variable Selection for High-Dimensional Data: Prediction of Pathological Response in Triple-Negative Breast Cancer

Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 222
Author(s):  
Juan C. Laria ◽  
M. Carmen Aguilera-Morillo ◽  
Enrique Álvarez ◽  
Rosa E. Lillo ◽  
Sara López-Taruella ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Variable Selection ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
A Priori ◽  
Simulated Data ◽  
Point Of View ◽  
High Dimensional ◽  
Whole Genome ◽  
Genome Context

Over the last decade, regularized regression methods have offered alternatives for performing multi-marker analysis and feature selection in a whole genome context. The process of defining a list of genes that will characterize an expression profile remains unclear. It currently relies upon advanced statistics and can use an agnostic point of view or include some a priori knowledge, but overfitting remains a problem. This paper introduces a methodology to deal with the variable selection and model estimation problems in the high-dimensional set-up, which can be particularly useful in the whole genome context. Results are validated using simulated data and a real dataset from a triple-negative breast cancer study.

Abstract 343: Bayesian Selection of Modifier Genes in Hypertrophic Cardiomyopathy Through Whole Genome Sequencing

2015 ◽  
Vol 117 (suppl_1) ◽  
Author(s):  
Matthew Wheeler ◽  
Daryl Waggott ◽  
Megan Grove ◽  
Frederick Dewey ◽  
Cuiping Pan ◽  
...  
Keyword(s):  
Hypertrophic Cardiomyopathy ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
A Priori ◽  
Copy Number Variants ◽  
Whole Genome Sequence ◽  
Monogenic Disease ◽  
Whole Genome ◽  
Genetic Modifiers ◽  
Structural Variants

Background: Technological advances have greatly reduced the cost of whole genome sequencing. For single individuals clinical application is apparent, while exome sequencing in tens of thousands of people has allowed a more global view of genetic variation that can inform interpretation of specific variants in individuals. We hypothesized that genome sequencing of patients with monogenic cardiomyopathy would facilitate discovery of genetic modifiers of phenotype. Methods and Results: We identified 48 individuals diagnosed with cardiomyopathy and with putative mutations in MYH7, the gene encoding beta myosin heavy chain. We carried out whole genome sequencing and applied a newly developed analytical pipeline optimized for discovery of genes modifying severity of clinical presentation and outcomes. Using a combination of external priors and rare variant burden tests we scored genes as potential modifiers. There were 96 genes that reached a modifier score of 6 out of 12 or better (9=2, 8=8, 7=17, 6=69). We identified NCKAP1, a gene that regulates actin filament dynamics, and CAMSAP1, a calmodulin regulate gene that regulates microtubule dynamics, as top scoring modifiers of hypertrophic cardiomyopathy phenotypes (score=9) while LDB2, RYR2, FBN1 and ATP1A2 had modifier scores of 8. Of the top scoring genes, 21 out of 96 were identified as candidates a priori. Our candidate prioritization scheme identified the previously described modifiers of cardiomyopathy phenotype, FHOD3 and MYBPC3, as top scoring genes. We identified structural variants in 21 clinically sequenced cardiomyopathy associated genes, 13 of which were at less than 10% frequency. Copy number variants in ILK and CSRP3 were nominally associated with ejection fraction (p=0.03), while 8 genes showed copy gains (GLA, FKTN, SGCD, TTN, SOS1, ANKRD1, VCL and NEBL). Structural variants were found in CSRP3, MYL3 and TNNC1, all of which have been implicated as causative for HCM. Conclusion: Evaluation of the whole genome sequence, even in the case of putatively monogenic disease, leads to important diagnostic and scientific insights not revealed by panel-based sequencing.

scholarly journals Low-Bias RNA Sequencing of the HIV-2 Genome from Blood Plasma

2018 ◽  
Vol 93 (1) ◽  
Author(s):  
Katherine L. James ◽  
Thushan I. de Silva ◽  
Katherine Brown ◽  
Hilton Whittle ◽  
Stephen Taylor ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Blood Plasma ◽  
De Novo ◽  
A Priori ◽  
Pcr Amplification ◽  
Hiv Vaccine ◽  
Whole Genome ◽  
Plasma Samples ◽  
Target Enrichment ◽  
Rna Seq

ABSTRACTAccurate determination of the genetic diversity present in the HIV quasispecies is critical for the development of a preventative vaccine: in particular, little is known about viral genetic diversity for the second type of HIV, HIV-2. A better understanding of HIV-2 biology is relevant to the HIV vaccine field because a substantial proportion of infected people experience long-term viral control, and prior HIV-2 infection has been associated with slower HIV-1 disease progression in coinfected subjects. The majority of traditional and next-generation sequencing methods have relied on target amplification prior to sequencing, introducing biases that may obscure the true signals of diversity in the viral population. Additionally, target enrichment through PCR requiresa priorisequence knowledge, which is lacking for HIV-2. Therefore, a target enrichment free method of library preparation would be valuable for the field. We applied an RNA shotgun sequencing (RNA-Seq) method without PCR amplification to cultured viral stocks and patient plasma samples from HIV-2-infected individuals. Libraries generated from total plasma RNA were analyzed with a two-step pipeline: (i)de novogenome assembly, followed by (ii) read remapping. By this approach, whole-genome sequences were generated with a 28× to 67× mean depth of coverage. Assembled reads showed a low level of GC bias, and comparison of the genome diversities at the intrahost level showed low diversity in the accessory genevpxin all patients. Our study demonstrates that RNA-Seq is a feasible full-genomede novosequencing method for blood plasma samples collected from HIV-2-infected individuals.IMPORTANCEAn accurate picture of viral genetic diversity is critical for the development of a globally effective HIV vaccine. However, sequencing strategies are often complicated by target enrichment prior to sequencing, introducing biases that can distort variant frequencies, which are not easily corrected for in downstream analyses. Additionally, detaileda priorisequence knowledge is needed to inform robust primer design when employing PCR amplification, a factor that is often lacking when working with tropical diseases localized in developing countries. Previous work has demonstrated that direct RNA shotgun sequencing (RNA-Seq) can be used to circumvent these issues for hepatitis C virus (HCV) and norovirus. We applied RNA-Seq to total RNA extracted from HIV-2 blood plasma samples, demonstrating the applicability of this technique to HIV-2 and allowing us to generate a dynamic picture of genetic diversity over the whole genome of HIV-2 in the context of low-bias sequencing.

Hypothesis testing framework for active object detection

2013 ◽  
Author(s):  
Nikolay Atanasov ◽  
Bharath Sankaran ◽  
Jerome Le Ny ◽  
Thomas Koletschka ◽  
George J. Pappas ◽  
...  
Keyword(s):  
Object Detection ◽  
Hypothesis Testing ◽  
Active Object ◽  
Testing Framework

scholarly journals Microsatellite analysis of the mating system of Bruguiera gymnorrhiza and Kandelia obovata

2018 ◽  
Vol 197 ◽  
pp. 06003
Author(s):  
Mohammad Basyuni ◽  
Shigeyuki Baba ◽  
Hirosuke Oku ◽  
Ridha Wati ◽  
Annisa Fitri
Keyword(s):  
Mating System ◽  
System Analysis ◽  
Genetic Relatedness ◽  
Mixed Mating ◽  
Bruguiera Gymnorrhiza ◽  
Mangrove Tree ◽  
Mixed Mating Model ◽  
Mating Model ◽  
Inbreeding Level ◽  
Cross Fertilization

Microsatellite loci were used for estimating mating system for three populations of B. gymnorrhiza and K. obovata (Rhizophoracea) in Okinawa, Japan. Mother trees and thirty offspring of individual samples representing the population of both species were genotyped at five microsatellites. The mating system was examined using two approaches: a mixed mating model of multilocus testing, implemented by MLTR program and outcrossing rate from the level of inbreeding. Mating system analysis showed multilocus outcrossing rates (tm) for both species was 0.850-1.000 and 0.780-0.938 respectively. By contrast, according to inbreeding level, tm was lower than MLRT: 0.495-1.028 and 0.480-0.612 of both species respectively. However, biparental inbreeding (tm- ts) was diverse from zero both species for all three populations, showing that cross-fertilization events may ensue between the relatives both species. This data as well means the genetic relatedness (r) for B. gymnorrhiza and K. obovata were 0.108±0.025 and 0.032±0.09 respectively. Average relatedness was below 0.25, the value for a half-sib relationship. These results suggest that postulation of a half-sib relationship among progeny of open-pollinated families is opposed for both mangrove tree species.

scholarly journals Spatial proximity and asynchronous refuge sharing networks both explain patterns of tick genetic relatedness among lizards, but in different years

2020 ◽  
Vol 45 (4) ◽  
pp. 493-501
Author(s):  
Caroline K. Wohlfeil ◽  
Stephanie S. Godfrey ◽  
Stephan T. Leu ◽  
Jessica Clayton ◽  
Michael G. Gardner
Keyword(s):  
Genetic Relatedness ◽  
Spatial Proximity
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