scholarly journals Genetic divergence and phenotypic plasticity contribute to variation in cuticular hydrocarbons in the seaweed fly Coelopa frigida

2018 ◽  
Author(s):  
Emma Berdan ◽  
Swantje Enge ◽  
Göran M. Nylund ◽  
Maren Wellenreuther ◽  
Gerrit A. Martens ◽  
...  
Keyword(s):  
Cuticular Hydrocarbons ◽  
Genetic Basis ◽  
Kin Recognition ◽  
Population Level ◽  
Sequencing Data ◽  
Sexual Signal ◽  
Phenotypic Differences ◽  
Behavioral Trials ◽  
Coelopa Frigida ◽  
Natural And Sexual Selection

Cuticular hydrocarbons (CHCs) form the boundary between insects and their environments and often act as essential cues for species, mate and kin recognition. This complex polygenic trait can be highly variable both among and within species, but the causes of this variation, especially the genetic basis, are largely unknown. In this study, we investigated phenotypic and genetic variation of CHCs in the seaweed fly, C. frigida, and found that composition was affected by both genetic (sex and population) and environmental (larval diet) factors. We subsequently conducted behavioral trials that show CHCs are likely used as a sexual signal. We identified general shifts in CHC chemistry as well as individual compounds and found that the methylated compounds, mean chain length, proportion of alkenes, and normalized total CHCs differed between sexes and populations. We combined this data with whole genome re-sequencing data to examine the genetic underpinnings of these differences. We identified 11 genes related to CHC synthesis and found population level outlier SNPs in 5 that are concordant with phenotypic differences. Together these results reveal that the CHC composition of C. frigida is dynamic, strongly affected by the larval environment, and likely under natural and sexual selection.

scholarly journals Chloroplast genomes in Populus (Salicaceae): comparisons from an intensively sampled genus reveal dynamic patterns of evolution

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jiawei Zhou ◽  
Shuo Zhang ◽  
Jie Wang ◽  
Hongmei Shen ◽  
Bin Ai ◽  
...  
Keyword(s):  
Phylogenetic Analyses ◽  
Population Level ◽  
Gene Content ◽  
Sequencing Data ◽  
Cellular Functions ◽  
Chloroplast Evolution ◽  
Chloroplast Genomes ◽  
Genome Features ◽  
Genome Annotations ◽  
Genome Analyses

AbstractThe chloroplast is one of two organelles containing a separate genome that codes for essential and distinct cellular functions such as photosynthesis. Given the importance of chloroplasts in plant metabolism, the genomic architecture and gene content have been strongly conserved through long periods of time and as such are useful molecular tools for evolutionary inferences. At present, complete chloroplast genomes from over 4000 species have been deposited into publicly accessible databases. Despite the large number of complete chloroplast genomes, comprehensive analyses regarding genome architecture and gene content have not been conducted for many lineages with complete species sampling. In this study, we employed the genus Populus to assess how more comprehensively sampled chloroplast genome analyses can be used in understanding chloroplast evolution in a broadly studied lineage of angiosperms. We conducted comparative analyses across Populus in order to elucidate variation in key genome features such as genome size, gene number, gene content, repeat type and number, SSR (Simple Sequence Repeat) abundance, and boundary positioning between the four main units of the genome. We found that some genome annotations were variable across the genus owing in part from errors in assembly or data checking and from this provided corrected annotations. We also employed complete chloroplast genomes for phylogenetic analyses including the dating of divergence times throughout the genus. Lastly, we utilized re-sequencing data to describe the variations of pan-chloroplast genomes at the population level for P. euphratica. The analyses used in this paper provide a blueprint for the types of analyses that can be conducted with publicly available chloroplast genomes as well as methods for building upon existing datasets to improve evolutionary inference.

scholarly journals Nucleus-specific expression in the multinuclear mushroom-forming fungusAgaricus bisporusreveals different nuclear regulatory programs

2018 ◽  
Vol 115 (17) ◽  
pp. 4429-4434 ◽  
Author(s):  
Thies Gehrmann ◽  
Jordi F. Pelkmans ◽  
Robin A. Ohm ◽  
Aurin M. Vos ◽  
Anton S. M. Sonnenberg ◽  
...  
Keyword(s):  
Agaricus Bisporus ◽  
Sequencing Data ◽  
Carbohydrate Active Enzymes ◽  
Nuclear Level ◽  
Specific Expression ◽  
Phenotypic Differences ◽  
Gene Level ◽  
Nuclear Separation ◽  
Insight Into ◽  
Specific Mrna

Many fungi are polykaryotic, containing multiple nuclei per cell. In the case of heterokaryons, there are different nuclear types within a single cell. It is unknown what the different nuclear types contribute in terms of mRNA expression levels in fungal heterokaryons. Each cell of the mushroomAgaricus bisporuscontains two to 25 nuclei of two nuclear types originating from two parental strains. Using RNA-sequencing data, we assess the differential mRNA contribution of individual nuclear types and its functional impact. We studied differential expression between genes of the two nuclear types, P1 and P2, throughout mushroom development in various tissue types. P1 and P2 produced specific mRNA profiles that changed through mushroom development. Differential regulation occurred at the gene level, rather than at the locus, chromosomal, or nuclear level. P1 dominated mRNA production throughout development, and P2 showed more differentially up-regulated genes in important functional groups. In the vegetative mycelium, P2 up-regulated almost threefold more metabolism genes and carbohydrate active enzymes (cazymes) than P1, suggesting phenotypic differences in growth. We identified widespread transcriptomic variation between the nuclear types ofA. bisporus. Our method enables studying nucleus-specific expression, which likely influences the phenotype of a fungus in a polykaryotic stage. Our findings have a wider impact to better understand gene regulation in fungi in a heterokaryotic state. This work provides insight into the transcriptomic variation introduced by genomic nuclear separation.

scholarly journals Patterns of genome-wide allele-specific expression in hybrid rice and the implications on the genetic basis of heterosis

2019 ◽  
Vol 116 (12) ◽  
pp. 5653-5658 ◽  
Author(s):  
Lin Shao ◽  
Feng Xing ◽  
Conghao Xu ◽  
Qinghua Zhang ◽  
Jian Che ◽  
...  
Keyword(s):  
Genetic Basis ◽  
Molecular Mechanisms ◽  
Sequencing Data ◽  
Specific Expression ◽  
Allele Specific Expression ◽  
Parental Allele ◽  
Genetic Components ◽  
Genome Wide ◽  
A Genome ◽  
Allele Specific

Utilization of heterosis has greatly increased the productivity of many crops worldwide. Although tremendous progress has been made in characterizing the genetic basis of heterosis using genomic technologies, molecular mechanisms underlying the genetic components are much less understood. Allele-specific expression (ASE), or imbalance between the expression levels of two parental alleles in the hybrid, has been suggested as a mechanism of heterosis. Here, we performed a genome-wide analysis of ASE by comparing the read ratios of the parental alleles in RNA-sequencing data of an elite rice hybrid and its parents using three tissues from plants grown under four conditions. The analysis identified a total of 3,270 genes showing ASE (ASEGs) in various ways, which can be classified into two patterns: consistent ASEGs such that the ASE was biased toward one parental allele in all tissues/conditions, and inconsistent ASEGs such that ASE was found in some but not all tissues/conditions, including direction-shifting ASEGs in which the ASE was biased toward one parental allele in some tissues/conditions while toward the other parental allele in other tissues/conditions. The results suggested that these patterns may have distinct implications in the genetic basis of heterosis: The consistent ASEGs may cause partial to full dominance effects on the traits that they regulate, and direction-shifting ASEGs may cause overdominance. We also showed that ASEGs were significantly enriched in genomic regions that were differentially selected during rice breeding. These ASEGs provide an index of the genes for future pursuit of the genetic and molecular mechanism of heterosis.

scholarly journals Genetic basis for phenotypic differences between different Toxoplasma gondii type I strains

BMC Genomics ◽  
2013 ◽  
Vol 14 (1) ◽  
pp. 467 ◽  
Author(s):  
Ninghan Yang ◽  
Andrew Farrell ◽  
Wendy Niedelman ◽  
Mariane Melo ◽  
Diana Lu ◽  
...  
Keyword(s):  
Toxoplasma Gondii ◽  
Genetic Basis ◽  
Type I ◽  
Phenotypic Differences

scholarly journals A trade-off between natural and sexual selection underlies diversification of a sexual signal

2014 ◽  
Vol 26 (2) ◽  
pp. 533-542 ◽  
Author(s):  
Justa L. Heinen-Kay ◽  
Kirstin E. Morris ◽  
Nicole A. Ryan ◽  
Samantha L. Byerley ◽  
Rebecca E. Venezia ◽  
...  
Keyword(s):  
Sexual Selection ◽  
Sexual Signal ◽  
Trade Off ◽  
Natural And Sexual Selection

scholarly journals Algorithmic methods to infer the evolutionary trajectories in cancer progression

2016 ◽  
Vol 113 (28) ◽  
pp. E4025-E4034 ◽  
Author(s):  
Giulio Caravagna ◽  
Alex Graudenzi ◽  
Daniele Ramazzotti ◽  
Rebeca Sanz-Pamplona ◽  
Luca De Sano ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Current Knowledge ◽  
Population Level ◽  
Selective Advantage ◽  
Explanatory Models ◽  
Next Generation Sequencing Data ◽  
Driver Mutations ◽  
Sequencing Data ◽  
Cross Sectional ◽  
Progression Model

The genomic evolution inherent to cancer relates directly to a renewed focus on the voluminous next-generation sequencing data and machine learning for the inference of explanatory models of how the (epi)genomic events are choreographed in cancer initiation and development. However, despite the increasing availability of multiple additional -omics data, this quest has been frustrated by various theoretical and technical hurdles, mostly stemming from the dramatic heterogeneity of the disease. In this paper, we build on our recent work on the “selective advantage” relation among driver mutations in cancer progression and investigate its applicability to the modeling problem at the population level. Here, we introduce PiCnIc (Pipeline for Cancer Inference), a versatile, modular, and customizable pipeline to extract ensemble-level progression models from cross-sectional sequenced cancer genomes. The pipeline has many translational implications because it combines state-of-the-art techniques for sample stratification, driver selection, identification of fitness-equivalent exclusive alterations, and progression model inference. We demonstrate PiCnIc’s ability to reproduce much of the current knowledge on colorectal cancer progression as well as to suggest novel experimentally verifiable hypotheses.

scholarly journals Genetic architecture of male courtship behavior differences in the parasitoid wasp genus Nasonia (Hymenoptera; Pteromalidae)

2019 ◽  
Author(s):  
J Gadau ◽  
C. Pietsch ◽  
S. Gerritsma ◽  
S. Ferber ◽  
L. van de Zande ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Genetic Basis ◽  
Mapping Population ◽  
Courtship Behavior ◽  
Parasitoid Wasp ◽  
Phenotypic Variance ◽  
Male Courtship ◽  
Phenotypic Differences ◽  
A Genome ◽  
Male Courtship Behavior

AbstractVery little is known about the genetic basis of behavioral variation in courtship behavior, which can contribute to speciation by prezygotic isolation of closely related species. Here, we analyze the genetic basis and architecture of species differences in the male courtship behavior of two closely related parasitoid wasps Nasonia vitripennis and N. longicornis. Both species occur microsympatrically in parts of their ranges and have been found in the same host pupae. Despite strong postzygotic isolation mechanisms between these two Nasonia species, viable hybrid females can be produced in the laboratory if both species are cured of their Wolbachia endosymbionts. We used haploid F2 hybrid males derived from virgin F1 hybrid females of two independent mapping populations to study the genetic architecture of five quantitative and two qualitative components of their courtship behavior. A total of 14 independent Quantitative Trait Loci (QTL) were found in the first mapping population (320 males), which explained 4-25% of the observed phenotypic variance. Ten of these QTL were confirmed by a second independent mapping population (112 males) and no additional ones were found. A genome-wide scan for two-loci interactions revealed many unique but mostly additive interactions explaining an additional proportion of the observed phenotypic variance. Courtship QTL were found on all five chromosomes and four loci were associated with more than one QTL, indicating either possible pleiotropic effects of individual QTL or individual loci contributing to multiple courtship components. Our results indicate that these two evolutionary young species have rapidly evolved multiple significant phenotypic differences in their courtship behavior that have a polygenic and highly interactive genetic architecture. Based on the location of the QTL and the published Nasonia genome sequence we were able to identify a series of candidate genes for further study.

scholarly journals Statistical model integrating interactions into genotype-phenotype association mapping: an application to reveal 3D-genetic basis underlying Autism

2020 ◽  
Author(s):  
Qing Li ◽  
Chen Cao ◽  
Deshan Perera ◽  
Jingni He ◽  
Xingyu Chen ◽  
...  
Keyword(s):  
Association Mapping ◽  
Genetic Basis ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Autism Spectrum ◽  
Genetic Interactions ◽  
Whole Genome Sequencing Data ◽  
Biological Interactions ◽  
Sequencing Data ◽  
Current Standard

AbstractBiological interactions are prevalent in the functioning organisms. Correspondingly, statistical geneticists developed various models to identify genetic interactions through genotype-phenotype association mapping. The current standard protocols in practice test single variants or single regions (that contain multiple local variants) sequentially along the genome, followed by functional annotations that involve various aspects including interactions. The testing of genetic interactions upfront is rare in practice due to the burden of testing a huge number of combinations, which lead to the multiple-test problem and the risk of overfitting. In this work, we developed interaction-integrated linear mixed model (ILMM), a novel model that integrates a priori knowledge into linear mixed models. ILMM enables statistical integration of genetic interactions upfront and overcomes the problems associated with combination searching.Three dimensional (3D) genomic interactions assessed by Hi-C experiments have led to unprecedented biological discoveries. However, the contribution of 3D genomic interactions to the genetic basis of complex diseases has yet to be quantified. Using 3D interacting regions as a priori information, we conducted both simulations and real data analysis to test ILMM. By applying ILMM to whole genome sequencing data for Autism Spectrum Disorders, or ASD (MSSNG) and transcriptome sequencing data (GTEx), we revealed the 3D-genetic basis of ASD and 3D-eQTLs for a substantial proportion of gene expression in brain tissues. Moreover, we have revealed a potential mechanism involving distal regulation between FOXP2 and DNMT3A conferring the risk of ASD.Software is freely available in our GitHub: https://github.com/theLongLab/Jawamix5

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