scholarly journals Common genomic regions underlie natural variation in diverse toxin responses

2018 ◽  
Author(s):  
Kathryn S. Evans ◽  
Shannon C. Brady ◽  
Joshua S. Bloom ◽  
Robyn E. Tanny ◽  
Daniel E. Cook ◽  
...  
Keyword(s):  
Phenotypic Variation ◽  
Statistical Power ◽  
Natural Variation ◽  
Growth Parameters ◽  
Heritable Variation ◽  
Phenotypic Complexity ◽  
Response Variation ◽  
Genomic Regions ◽  
Chromosome Substitution Strains ◽  
Sufficient Statistical Power

AbstractPhenotypic complexity is caused by the contributions of environmental factors and multiple genetic loci, interacting or acting independently. Studies of yeast and Arabidopsis found that the majority of natural variation across phenotypes is attributable to independent additive quantitative trait loci (QTL). Detected loci in these organisms explain most of the estimated heritable variation. By contrast, many heritable components underlying phenotypic variation in metazoan models remain undetected. Before the relative impacts of additive and interactive variance components on metazoan phenotypic variation can be dissected, high replication and precise phenotypic measurements are required to obtain sufficient statistical power to detect loci contributing to this missing heritability. Here, we used a panel of 296 recombinant inbred advanced intercross lines of Caenorhabditis elegans and a high-throughput fitness assay to detect loci underlying responses to 16 different toxins, including heavy metals, chemotherapeutic drugs, pesticides, and neuropharmaceuticals. Using linkage mapping, we identified 82 QTL that underlie variation in responses to these toxins and predicted the relative contributions of additive loci and genetic interactions across various growth parameters. Additionally, we identified three genomic regions that impact responses to multiple classes of toxins. These QTL hotspots could represent common factors impacting toxin responses. We went further to generate near-isogenic lines and chromosome-substitution strains and then experimentally validated these QTL hotspots, implicating additive and interactive loci that underlie toxin-response variation.

scholarly journals Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects

2018 ◽  
Author(s):  
Allison A. Regier ◽  
Yossi Farjoun ◽  
David Larson ◽  
Olga Krasheninina ◽  
Hyun Min Kang ◽  
...  
Keyword(s):  
Data Processing ◽  
Genome Sequencing ◽  
Statistical Power ◽  
Human Genetics ◽  
Variant Calling ◽  
Joint Analysis ◽  
Sequencing Analysis ◽  
Batch Effects ◽  
Many Sources ◽  
Genomic Regions

AbstractHundreds of thousands of human whole genome sequencing (WGS) datasets will be generated over the next few years to interrogate a broad range of traits, across diverse populations. These data are more valuable in aggregate: joint analysis of genomes from many sources increases sample size and statistical power for trait mapping, and will enable studies of genome biology, population genetics and genome function at unprecedented scale. A central challenge for joint analysis is that different WGS data processing and analysis pipelines cause substantial batch effects in combined datasets, necessitating computationally expensive reprocessing and harmonization prior to variant calling. This approach is no longer tenable given the scale of current studies and data volumes. Here, in a collaboration across multiple genome centers and NIH programs, we define WGS data processing standards that allow different groups to produce “functionally equivalent” (FE) results suitable for joint variant calling with minimal batch effects. Our approach promotes broad harmonization of upstream data processing steps, while allowing for diverse variant callers. Importantly, it allows each group to continue innovating on data processing pipelines, as long as results remain compatible. We present initial FE pipelines developed at five genome centers and show that they yield similar variant calling results – including single nucleotide (SNV), insertion/deletion (indel) and structural variation (SV) – and produce significantly less variability than sequencing replicates. Residual inter-pipeline variability is concentrated at low quality sites and repetitive genomic regions prone to stochastic effects. This work alleviates a key technical bottleneck for genome aggregation and helps lay the foundation for broad data sharing and community-wide “big-data” human genetics studies.

scholarly journals Data integration uncovers the metabolic bases of phenotypic variation in yeast

2020 ◽  
Author(s):  
Marianyela Petrizzelli ◽  
Dominique de Vienne ◽  
Thibault Nidelet ◽  
Camille Noûs ◽  
Christine Dillmann
Keyword(s):  
Phenotypic Variation ◽  
Enrichment Analysis ◽  
Production Traits ◽  
Phenotypic Complexity ◽  
Powerful Approach ◽  
Novel Method ◽  
Constraint Based Modeling ◽  
The Relationship ◽  
Yeast Genetic ◽  
Levels Of Integration

The relationship between different levels of integration is a key feature for understanding the genotype-phenotype map.Here, we describe a novel method of integrated data analysis that incorporates protein abundance data into constraint-based modeling to elucidate the biological mechanisms underlying phenotypic variation. Specifically, we studied yeast genetic diversity at three levels of phenotypic complexity in a population of yeast obtained by pairwise crosses of eleven strains belonging to two species, Saccha-romyces cerevisiae and S. uvarum. The data included protein abundances, integrated traits (life-history/fermentation) and computational estimates of metabolic fluxes.Results highlighted that the negative correlation between production traits such as population carrying capacity (K) and traits associated with growth and fermentation rates (Jmax) is explained by a differential usage of energy production pathways: a high K was associated with high TCA fluxes, while a high Jmax was associated with high glycolytic fluxes. Enrichment analysis of protein sets confirmed our results.This powerful approach allowed us to identify the molecular and metabolic bases of integrated trait variation, and therefore has a broad applicability domain.

scholarly journals Characterization of the genetic architecture underlying eye size variation within Drosophila melanogaster and Drosophila simulans

2019 ◽  
Author(s):  
Pedro Gaspar ◽  
Saad Arif ◽  
Lauren Sumner-Rooney ◽  
Maike Kittelmann ◽  
Andrew J. Bodey ◽  
...  
Keyword(s):  
Drosophila Melanogaster ◽  
Natural Variation ◽  
Size Variation ◽  
Eye Size ◽  
Specific Variation ◽  
Gene Regulatory ◽  
Morphological Differences ◽  
Genomic Regions ◽  
Insect Eye

AbstractThe compound eyes of insects exhibit striking variation in size, reflecting adaptation to different lifestyles and habitats. However, the genetic and developmental bases of variation in insect eye size is poorly understood, which limits our understanding of how these important morphological differences evolve. To address this, we further explored natural variation in eye size within and between four species of the Drosophila melanogaster species subgroup. We found extensive variation in eye size among these species, and flies with larger eyes generally had a shorter inter-ocular distance and vice versa. We then carried out quantitative trait loci (QTL) mapping of intra-specific variation in eye size and inter-ocular distance in both D. melanogaster and D. simulans. This revealed that different genomic regions underlie variation in eye size and inter-ocular distance in both species, which we corroborated by introgression mapping in D. simulans. This suggests that although there is a trade-off between eye size and inter-ocular distance, variation in these two traits is likely to be caused by different genes and so can be genetically decoupled. Finally, although we detected QTL for intra-specific variation in eye size at similar positions in D. melanogaster and D. simulans, we observed differences in eye fate commitment between strains of these two species. This indicates that different developmental mechanisms and therefore, most likely, different genes contribute to eye size variation in these species. Taken together with the results of previous studies, our findings suggest that the gene regulatory network that specifies eye size has evolved at multiple genetic nodes to give rise to natural variation in this trait within and among species.

scholarly journals Genome-Wide Association Study and Selection Signatures Detect Genomic Regions Associated with Seed Yield and Oil Quality in Flax

2018 ◽  
Vol 19 (8) ◽  
pp. 2303 ◽  
Author(s):  
Frank You ◽  
Jin Xiao ◽  
Pingchuan Li ◽  
Zhen Yao ◽  
Gaofeng Jia ◽  
...  
Keyword(s):  
Association Study ◽  
Seed Yield ◽  
Phenotypic Variation ◽  
Genome Wide Association Study ◽  
Oil Quality ◽  
Genome Wide Association ◽  
Selection Signatures ◽  
Genome Wide ◽  
A Genome ◽  
Genomic Regions

A genome-wide association study (GWAS) was performed on a set of 260 lines which belong to three different bi-parental flax mapping populations. These lines were sequenced to an averaged genome coverage of 19× using the Illumina Hi-Seq platform. Phenotypic data for 11 seed yield and oil quality traits were collected in eight year/location environments. A total of 17,288 single nucleotide polymorphisms were identified, which explained more than 80% of the phenotypic variation for days to maturity (DTM), iodine value (IOD), palmitic (PAL), stearic, linoleic (LIO) and linolenic (LIN) acid contents. Twenty-three unique genomic regions associated with 33 quantitative trait loci (QTL) for the studied traits were detected, thereby validating four genomic regions previously identified. The 33 QTL explained 48–73% of the phenotypic variation for oil content, IOD, PAL, LIO and LIN but only 8–14% for plant height, DTM and seed yield. A genome-wide selective sweep scan for selection signatures detected 114 genomic regions that accounted for 7.82% of the flax pseudomolecule and overlapped with the 11 GWAS-detected genomic regions associated with 18 QTL for 11 traits. The results demonstrate the utility of GWAS combined with selection signatures for dissection of the genetic structure of traits and for pinpointing genomic regions for breeding improvement.

scholarly journals Identification of quantitative trait loci associated with canopy temperature in soybean

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Sumandeep K. Bazzer ◽  
Larry C. Purcell
Keyword(s):  
Quantitative Trait Loci ◽  
Phenotypic Variation ◽  
Quantitative Trait ◽  
Recombinant Inbred Lines ◽  
Canopy Temperature ◽  
Growth And Yield ◽  
Indirect Measure ◽  
Trait Loci ◽  
Genomic Regions ◽  
The Impact

Abstract A consistent risk for soybean (Glycine max L.) production is the impact of drought on growth and yield. Canopy temperature (CT) is an indirect measure of transpiration rate and stomatal conductance and may be valuable in distinguishing differences among genotypes in response to drought. The objective of this study was to map quantitative trait loci (QTLs) associated with CT using thermal infrared imaging in a population of recombinant inbred lines developed from a cross between KS4895 and Jackson. Heritability of CT was 35% when estimated across environments. QTL analysis identified 11 loci for CT distributed on eight chromosomes that individually explained between 4.6 and 12.3% of the phenotypic variation. The locus on Gm11 was identified in two individual environments and across environments and explained the highest proportion of phenotypic variation (9.3% to 11.5%) in CT. Several of these CT loci coincided with the genomic regions from previous studies associated with canopy wilting, canopy temperature, water use efficiency, and other morpho-physiological traits related with drought tolerance. Candidate genes with biological function related to transpiration, root development, and signal transduction underlie these putative CT loci. These genomic regions may be important resources in soybean breeding programs to improve tolerance to drought.

scholarly journals A Systematic Review of Bilateral Upper Limb Training Devices for Poststroke Rehabilitation

2012 ◽  
Vol 2012 ◽  
pp. 1-17 ◽  
Author(s):  
A. (Lex) E. Q. van Delden ◽  
C. (Lieke) E. Peper ◽  
Gert Kwakkel ◽  
Peter J. Beek
Keyword(s):  
Upper Limb ◽  
Statistical Power ◽  
Relevant Literature ◽  
Qualitative Evaluation ◽  
Clinical Results ◽  
Mesh Term ◽  
Active Involvement ◽  
Bilateral Training ◽  
Sufficient Statistical Power ◽  
Rule Out

Introduction. In stroke rehabilitation, bilateral upper limb training is gaining ground. As a result, a growing number of mechanical and robotic bilateral upper limb training devices have been proposed.Objective. To provide an overview and qualitative evaluation of the clinical applicability of bilateral upper limb training devices.Methods. Potentially relevant literature was searched in the PubMed, Web of Science, and Google Scholar databases from 1990 onwards. Devices were categorized as mechanical or robotic (according to the PubMed MeSH term of robotics).Results. In total, 6 mechanical and 14 robotic bilateral upper limb training devices were evaluated in terms of mechanical and electromechanical characteristics, supported movement patterns, targeted part and active involvement of the upper limb, training protocols, outcomes of clinical trials, and commercial availability.Conclusion. Initial clinical results are not yet of such caliber that the devices in question and the concepts on which they are based are firmly established. However, the clinical outcomes do not rule out the possibility that the concept of bilateral training and the accompanied devices may provide a useful extension of currently available forms of therapy. To actually demonstrate their (surplus) value, more research with adequate experimental, dose-matched designs, and sufficient statistical power are required.

scholarly journals Evolution of sperm competition: Natural variation and genetic determinants of Caenorhabditis elegans sperm size

2018 ◽  
Author(s):  
Clotilde Gimond ◽  
Anne Vielle ◽  
Nuno Silva-Soares ◽  
Stefan Zdraljevic ◽  
Patrick T. McGrath ◽  
...  
Keyword(s):  
Caenorhabditis Elegans ◽  
Sperm Competition ◽  
Natural Variation ◽  
Competitive Ability ◽  
Molecular Mechanisms ◽  
Genetic Determinants ◽  
Heritable Variation ◽  
C Elegans ◽  
Male Sperm ◽  
Sperm Size

ABSTRACTSperm morphology is critical for sperm competition and thus for reproductive fitness. In the male-hermaphrodite nematode Caenorhabditis elegans, sperm size is a key feature of sperm competitive ability. Yet despite extensive research, the molecular mechanisms regulating C. elegans sperm size and the genetic basis underlying its natural variation remain unknown. Examining 97 genetically distinct C. elegans strains, we observe significant heritable variation in male sperm size but genome-wide association mapping did not yield any QTL (Quantitative Trait Loci). While we confirm larger male sperm to consistently outcompete smaller hermaphrodite sperm, we find natural variation in male sperm size to poorly predict male fertility and competitive ability. In addition, although hermaphrodite sperm size also shows significant natural variation, male and hermaphrodite sperm size do not correlate, implying a sex-specific genetic regulation of sperm size. To elucidate the molecular basis of intraspecific sperm size variation, we focused on recently diverged laboratory strains, which evolved extreme sperm size differences. Using mutants and quantitative complementation tests, we demonstrate that variation in the gene nurf-1 – previously shown to underlie the evolution of improved hermaphrodite reproduction – also explains the evolution of reduced male sperm size. This result illustrates how adaptive changes in C. elegans hermaphrodite function can cause the deterioration of a male-specific fitness trait due to a sexually antagonistic variant, representing an example of intralocus sexual conflict with resolution at the molecular level. Our results further provide first insights into the genetic determinants of C. elegans sperm size, pointing at an involvement of the NURF chromatin remodelling complex.

scholarly journals INFLUENCE OF CULTURE AGE, CYTOKININ LEVEL IN CULTURE, AND “RETIPPING” ON GROWTH AND THE INCIDENCE OF VARIATION IN TISSUE-CULTURED RHODODENDRONS

HortScience ◽  
1992 ◽  
Vol 27 (6) ◽  
pp. 585a-585
Author(s):  
Virginia M. Keith ◽  
Mark H. Brand
Keyword(s):  
Phenotypic Variation ◽  
Growth Parameters ◽  
Cytokinin Level ◽  
Culture Age ◽  
Regenerated Plants ◽  
Isopentenyl Adenine

Significant occurrences of phenotypic variation have been noted in micropropagated Rhododendron. Studies were undertaken to determine what aspects of micropropagation lead to variation. Rhododendron `Molly Fordham' was used to evaluate growth parameters and the incidence of variation in plants that originated from 3 month and 54 month old cultures. Plants from 3-month-old cultures were significantly wider than plants from 54-month-old cultures. Rhododendron `Aglo', `Molly Fordham', and `Scintillation' were used to evaluate growth and the incidence of variation in plants grown from microcutting bases and rerooted microcutting tips (retips). Three-month-old retips were significantly taller and wider than bases of the same age, but possessed fewer branches. The influence of in vitro N6-[2-isopentenyl]adenine (2-iP) concentration on the growth and phenotype of regenerated plants of `Aglo', `Molly Fordham', and `Scintillation' was examined. Data taken 3 months post-acclimation indicate that growth and the incidence of variation in response to 2-iP concentration is cultivar dependent.

scholarly journals Not just methods: User expertise explains the variability of outcomes of genome-wide studies

2016 ◽  
Author(s):  
Katie E. Lotterhos ◽  
Olivier François ◽  
Michael G.B. Blum
Keyword(s):  
Summer School ◽  
Statistical Power ◽  
A Priori ◽  
Simulated Data ◽  
Genome Scan ◽  
Genome Wide ◽  
The Difference ◽  
Difficult Challenge ◽  
Genomic Regions ◽  
Candidate Loci

AbstractGenome scan approaches promise to map genomic regions involved in adaptation of individuals to their environment. Outcomes of genome scans have been shown to depend on several factors including the underlying demography, the adaptive scenario, and the software or method used. We took advantage of a pedagogical experiment carried out during a summer school to explore the effect of an unexplored source of variability, which is the degree of user expertise.Participants were asked to analyze three simulated data challenges with methods presented during the summer school. In addition to submitting lists, participants evaluated a priori their level of expertise. We measured the quality of each genome scan analysis by computing a score that depends on false discovery rate and statistical power. In an easy and a difficult challenge, less advanced participants obtained similar scores compared to advanced ones, demonstrating that participants with little background in genome scan methods were able to learn how to use complex software after short introductory tutorials. However, in a challenge ofintermediate difficulty, advanced participants obtained better scores. To explain the difference, we introduce a probabilistic model that shows that a larger variation in scores is expected for SNPs of intermediate difficulty of detection. We conclude that practitioners should develop their statistical and computational expertise to follow the development of complex methods. To encourage training, we release the website of the summer school where users can submit lists of candidate loci, which will be scored and compared to the scores obtained by previous users.

scholarly journals Construction of a Genetic Linkage Map and Locations of Halo Blight and Brown Spot Resistance Loci in Common Bean (Phaseolus vulgaris L.) using RAPD Markers

HortScience ◽  
1997 ◽  
Vol 32 (3) ◽  
pp. 451D-451
Author(s):  
H.M. Ariyarathne ◽  
Dermot P. Coyne ◽  
Geunhwa Jung
Keyword(s):  
Linkage Map ◽  
Pseudomonas Syringae ◽  
Phenotypic Variation ◽  
Rapd Markers ◽  
Major Gene ◽  
Interval Mapping ◽  
Brown Spot ◽  
Halo Blight ◽  
Genomic Regions ◽  
Ri Lines

Halo blight (HB), brown spot (BS), and rust incited by the bacterial pathogens Pseudomonas syringae pv. phaseolicola (Psp), Pseudomonas syringae pv. syringae (Pss) and the fungal pathogen Uromyces appendiculatus, respectively, are important diseases of common beans. The objectives were to construct a RAPD linkage map, and to locate HB and BS resistance genes and genes for some other traits. One-hundred-seventy RAPD markers were mapped in 78 RI lines of the cross BelNeb 1 and A 55. Eleven main and nine minor linkage groups were identified. MAPMAKER/QTL, interval mapping, was used to identify genomic regions involved in the genetic control of the traits. One region was found to control HB leaf reactions to strain HB16 while three regions controlled reactions to strain HB 83. These regions accounted for 22% and 18%, 17%, and 17% of phenotypic variation of resistance, respectively. Four putative QTLs were identified for resistance to BS, and accounted for 37%, 26%, 23%, and 19% of the phenotypic variation. Rust resistance was determined by a single major gene to both rust strains US85NP 5-1 and D82vc74fh. However, linked markers were not identified. The V gene controlling flower and stem color was tightly linked with the Operon marker O10.620.

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