scholarly journals Recent advances in gene function prediction using context-specific coexpression networks in plants

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 153 ◽  
Author(s):  
Chirag Gupta ◽  
Andy Pereira
Keyword(s):  
Gene Function ◽  
Complex Traits ◽  
Large Fraction ◽  
Genetic Correlations ◽  
Short Review ◽  
Cellular Functions ◽  
Gene Functions ◽  
Plant Genes ◽  
Context Specific ◽  
Coexpression Networks

Predicting gene functions from genome sequence alone has been difficult, and the functions of a large fraction of plant genes remain unknown. However, leveraging the vast amount of currently available gene expression data has the potential to facilitate our understanding of plant gene functions, especially in determining complex traits. Gene coexpression networks—created by integrating multiple expression datasets—connect genes with similar patterns of expression across multiple conditions. Dense gene communities in such networks, commonly referred to as modules, often indicate that the member genes are functionally related. As such, these modules serve as tools for generating new testable hypotheses, including the prediction of gene function and importance. Recently, we have seen a paradigm shift from the traditional “global” to more defined, context-specific coexpression networks. Such coexpression networks imply genetic correlations in specific biological contexts such as during development or in response to a stress. In this short review, we highlight a few recent studies that attempt to fill the large gaps in our knowledge about cellular functions of plant genes using context-specific coexpression networks.

scholarly journals Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being

2021 ◽  
Author(s):  
Lianne P. de Vries ◽  
Toos C. E. M. van Beijsterveldt ◽  
Hermine Maes ◽  
Lucía Colodro-Conde ◽  
Meike Bartels
Keyword(s):  
Complex Traits ◽  
Educational Achievement ◽  
Genetic Correlations ◽  
Well Being ◽  
Genetic Influences ◽  
Phenotypic Correlation ◽  
Twin Model ◽  
Twin Models ◽  
Adolescent Twins ◽  
Depressed Symptoms

AbstractThe distinction between genetic influences on the covariance (or bivariate heritability) and genetic correlations in bivariate twin models is often not well-understood or only one is reported while the results show distinctive information about the relation between traits. We applied bivariate twin models in a large sample of adolescent twins, to disentangle the association between well-being (WB) and four complex traits (optimism, anxious-depressed symptoms (AD), aggressive behaviour (AGG), and educational achievement (EA)). Optimism and AD showed respectively a strong positive and negative phenotypic correlation with WB, the negative correlation of WB and AGG is lower and the correlation with EA is nearly zero. All four traits showed a large genetic contribution to the covariance with well-being. The genetic correlations of well-being with optimism and AD are strong and smaller for AGG and EA. We used the results of the models to explain what information is retrieved based on the bivariate heritability versus the genetic correlations and the (clinical) implications.

scholarly journals Genome-wide association study identifies 48 common genetic variants associated with handedness

2019 ◽  
Author(s):  
Gabriel Cuellar Partida ◽  
Joyce Y Tung ◽  
Nicholas Eriksson ◽  
Eva Albrecht ◽  
Fazil Aliev ◽  
...  
Keyword(s):  
Association Study ◽  
Genetic Variants ◽  
Complex Traits ◽  
Genome Wide Association Study ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
Left Handedness ◽  
Left Handed ◽  
Genome Wide ◽  
Common Genetic Variants

AbstractHandedness, a consistent asymmetry in skill or use of the hands, has been studied extensively because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and 32 studies from the International Handedness Consortium, we conducted the world’s largest genome-wide association study of handedness (1,534,836 right-handed, 194,198 (11.0%) left-handed and 37,637 (2.1%) ambidextrous individuals). We found 41 genetic loci associated with left-handedness and seven associated with ambidexterity at genome-wide levels of significance (P < 5×10−8). Tissue enrichment analysis implicated the central nervous system and brain tissues including the hippocampus and cerebrum in the etiology of left-handedness. Pathways including regulation of microtubules, neurogenesis, axonogenesis and hippocampus morphology were also highlighted. We found suggestive positive genetic correlations between being left-handed and some neuropsychiatric traits including schizophrenia and bipolar disorder. SNP heritability analyses indicated that additive genetic effects of genotyped variants explained 5.9% (95% CI = 5.8% – 6.0%) of the underlying liability of being left-handed, while the narrow sense heritability was estimated at 12% (95% CI = 7.2% – 17.7%). Further, we show that genetic correlation between left-handedness and ambidexterity is low (rg = 0.26; 95% CI = 0.08 – 0.43) implying that these traits are largely influenced by different genetic mechanisms. In conclusion, our findings suggest that handedness, like many other complex traits is highly polygenic, and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders that has been observed in multiple observational studies.

scholarly journals Signal Transduction across the Nuclear Envelope: Role of the LINC Complex in Bidirectional Signaling

Cells ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 124 ◽  
Author(s):  
Miki Hieda
Keyword(s):  
Signal Transduction ◽  
Plasma Membrane ◽  
Nuclear Envelope ◽  
Cell Cycle Progression ◽  
Structural Integrity ◽  
Short Review ◽  
Linc Complex ◽  
Cellular Functions ◽  
Bidirectional Signaling ◽  
Extracellular Signal

The primary functions of the nuclear envelope are to isolate the nucleoplasm and its contents from the cytoplasm as well as maintain the spatial and structural integrity of the nucleus. The nuclear envelope also plays a role in the transfer of various molecules and signals to and from the nucleus. To reach the nucleus, an extracellular signal must be transmitted across three biological membranes: the plasma membrane, as well as the inner and outer nuclear membranes. While signal transduction across the plasma membrane is well characterized, signal transduction across the nuclear envelope, which is essential for cellular functions such as transcriptional regulation and cell cycle progression, remains poorly understood. As a physical entity, the nuclear envelope, which contains more than 100 proteins, functions as a binding scaffold for both the cytoskeleton and the nucleoskeleton, and acts in mechanotransduction by relaying extracellular signals to the nucleus. Recent results show that the Linker of Nucleoskeleton and Cytoskeleton (LINC) complex, which is a conserved molecular bridge that spans the nuclear envelope and connects the nucleoskeleton and cytoskeleton, is also capable of transmitting information bidirectionally between the nucleus and the cytoplasm. This short review discusses bidirectional signal transduction across the nuclear envelope, with a particular focus on mechanotransduction.

scholarly journals Primary Cilia and Calcium Signaling Interactions

2020 ◽  
Vol 21 (19) ◽  
pp. 7109
Author(s):  
Hannah Saternos ◽  
Sidney Ley ◽  
Wissam AbouAlaiwi
Keyword(s):  
Primary Cilia ◽  
Cell Types ◽  
Cellular Level ◽  
Cellular Functions ◽  
Complex Processes ◽  
Secondary Messenger ◽  
Body Patterning ◽  
Motile Cilia ◽  
And Migration ◽  
Context Specific

The calcium ion (Ca2+) is a diverse secondary messenger with a near-ubiquitous role in a vast array of cellular processes. Cilia are present on nearly every cell type in either a motile or non-motile form; motile cilia generate fluid flow needed for a variety of biological processes, such as left–right body patterning during development, while non-motile cilia serve as the signaling powerhouses of the cell, with vital singling receptors localized to their ciliary membranes. Much of the research currently available on Ca2+-dependent cellular actions and primary cilia are tissue-specific processes. However, basic stimuli-sensing pathways, such as mechanosensation, chemosensation, and electrical sensation (electrosensation), are complex processes entangled in many intersecting pathways; an overview of proposed functions involving cilia and Ca2+ interplay will be briefly summarized here. Next, we will focus on summarizing the evidence for their interactions in basic cellular activities, including the cell cycle, cell polarity and migration, neuronal pattering, glucose-mediated insulin secretion, biliary regulation, and bone formation. Literature investigating the role of cilia and Ca2+-dependent processes at a single-cellular level appears to be scarce, though overlapping signaling pathways imply that cilia and Ca2+ interact with each other on this level in widespread and varied ways on a perpetual basis. Vastly different cellular functions across many different cell types depend on context-specific Ca2+ and cilia interactions to trigger the correct physiological responses, and abnormalities in these interactions, whether at the tissue or the single-cell level, can result in diseases known as ciliopathies; due to their clinical relevance, pathological alterations of cilia function and Ca2+ signaling will also be briefly touched upon throughout this review.

scholarly journals An expression atlas of human primary cells: inference of gene function from coexpression networks

BMC Genomics ◽  
2013 ◽  
Vol 14 (1) ◽  
pp. 632 ◽  
Author(s):  
Neil A Mabbott ◽  
J Baillie ◽  
Helen Brown ◽  
Tom C Freeman ◽  
David A Hume
Keyword(s):  
Gene Function ◽  
Primary Cells ◽  
Human Primary Cells ◽  
Expression Atlas ◽  
Coexpression Networks

scholarly journals Patterns of diverse gene functions in genomic neighborhoods predict gene function and phenotype

2019 ◽  
Author(s):  
Matej Mihelčić ◽  
Tomislav Šmuc ◽  
Fran Supek
Keyword(s):  
Gene Function ◽  
Structural Variation ◽  
Predictive Power ◽  
State Of The Art ◽  
Gene Clustering ◽  
High Confidence ◽  
Gene Functions ◽  
Predict Gene Function ◽  
Guilt By Association ◽  
Clustering Patterns

AbstractGenes with similar roles in the cell are known to cluster on chromosomes, thus benefiting from coordinated regulation. This allows gene function to be inferred by transferring annotations from genomic neighbors, following the guilt-by-association principle. We performed a systematic search for co-occurrence of >1000 gene functions in genomic neighborhoods across 1669 prokaryotic, 49 fungal and 80 metazoan genomes, revealing prevalent patterns that cannot be explained by clustering of functionally similar genes. It is a very common occurrence that pairs of dissimilar gene functions – corresponding to semantically distant Gene Ontology terms – are significantly co-located on chromosomes. These neighborhood associations are often as conserved across genomes as the known associations between similar functions, suggesting selective benefits from clustering of certain diverse functions, which may conceivably play complementary roles in the cell. We propose a simple encoding of chromosomal gene order, the neighborhood function profiles (NFP), which draws on diverse gene clustering patterns to predict gene function and phenotype. NFPs yield a 26-46% increase in predictive power over state-of-the-art approaches that propagate function across neighborhoods, thus providing hundreds of novel, high-confidence gene function inferences per genome. Furthermore, we demonstrate that the effect of structural variation on gene function distribution across chromosomes may be used to predict phenotype of individuals from their genome sequence.

scholarly journals CRISPR-TSKO facilitates efficient cell type-, tissue-, or organ-specific mutagenesis in Arabidopsis

2018 ◽  
Author(s):  
Ward Decaestecker ◽  
Rafael Andrade Buono ◽  
Marie L. Pfeiffer ◽  
Nick Vangheluwe ◽  
Joris Jourquin ◽  
...  
Keyword(s):  
Lateral Roots ◽  
Cell Types ◽  
Loss Of Function ◽  
Cellular Functions ◽  
Functional Studies ◽  
Organ Specific ◽  
Plant Genes ◽  
Mutant Lines ◽  
Functional Analyses ◽  
Efficient Selection

AbstractDetailed functional analyses of many fundamentally-important plant genes via conventional loss-of-function approaches are impeded by severe pleiotropic phenotypes. In particular, mutations in genes that are required for basic cellular functions and/or reproduction often interfere with the generation of homozygous mutant plants, precluding further functional studies. To overcome this limitation, we devised a CRISPR-based tissue-specific knockout system, CRISPR-TSKO, enabling the generation of somatic mutations in particular plant cell types, tissues, and organs. In Arabidopsis, CRISPR-TSKO mutations in essential genes caused well-defined, localized phenotypes in the root cap, stomatal lineage, or entire lateral roots. The underlying modular cloning system allows for efficient selection, identification, and functional analysis of mutant lines directly in the first transgenic generation. The efficacy of CRISPR-TSKO opens new avenues to discover and analyze gene functions in spatial and temporal contexts of plant life while avoiding pleiotropic effects of system-wide loss of gene function.

scholarly journals Comparison of methods for estimating genetic correlation between complex traits using GWAS summary statistics

2020 ◽  
Author(s):  
Yiliang Zhang ◽  
Youshu Cheng ◽  
Wei Jiang ◽  
Yixuan Ye ◽  
Qiongshi Lu ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Complex Traits ◽  
Association Studies ◽  
Genetic Correlations ◽  
Real Data ◽  
Estimation Methods ◽  
Easy Access ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Correlation Estimation

AbstractGenetic correlation is the correlation of additive genetic effects on two phenotypes. It is an informative metric to quantify the overall genetic similarity between complex traits, which provides insights into their polygenic genetic architecture. Several methods have been proposed to estimate genetic correlations based on data collected from genome-wide association studies (GWAS). Due to the easy access of GWAS summary statistics and computational efficiency, methods only requiring GWAS summary statistics as input have become more popular than methods utilizing individual-level genotype data. Here, we present a benchmark study for different summary-statistics-based genetic correlation estimation methods through simulation and real data applications. We focus on two major technical challenges in estimating genetic correlation: marker dependency caused by linkage disequilibrium (LD) and sample overlap between different studies. To assess the performance of different methods in the presence of these two challenges, we first conducted comprehensive simulations with diverse LD patterns and sample overlaps. Then we applied these methods to real GWAS summary statistics for a wide spectrum of complex traits. Based on these experiments, we conclude that methods relying on accurate LD estimation are less robust in real data applications compared to other methods due to the imprecision of LD obtained from reference panels. Our findings offer a guidance on how to appropriately choose the method for genetic correlation estimation in post-GWAS analysis in interpretation.

scholarly journals Epistatic Networks Associated with Parent-of-Origin Effects on Metabolic Traits

2019 ◽  
Author(s):  
Juan F Macias-Velasco ◽  
Celine L. St. Pierre ◽  
Jessica P Wayhart ◽  
Li Yin ◽  
Larry Spears ◽  
...  
Keyword(s):  
Complex Traits ◽  
Reciprocal Cross ◽  
Expression Profiles ◽  
Specific Interaction ◽  
Imprinted Genes ◽  
Cross Model ◽  
Metabolic Traits ◽  
Parent Of Origin ◽  
Origin Effects ◽  
Context Specific

ABSTRACTParent-of-origin effects (POE) are unexpectedly common in complex traits, including metabolic and neurological diseases. POE can also be modified by the environment, but the architecture of these gene-by-environmental effects on phenotypes remains to be unraveled. Previously, quantitative trait loci (QTL) showing context-specific POE on metabolic traits were mapped in the F16 generation of an advanced intercross between LG/J and SM/J inbred mice. However, these QTL were not enriched for known imprinted genes, suggesting another mechanism is needed to explain these POE phenomena. Here, we use a simple yet powerful F1 reciprocal cross model to test the hypothesis that non-imprinted genes can generate complex POE on metabolic traits through genetic interactions with imprinted genes. Male and female mice from a F1 reciprocal cross of LG/J and SM/J strains were fed either high or low fat diets. We generated expression profiles from three metabolically-relevant tissues: hypothalamus, white adipose, and liver. We identified two classes of parent-of-origin expression biases: genes showing parent-of-origin-dependent allele-specific expression and biallelic genes that are differentially expressed by reciprocal cross. POE patterns of both gene classes are highly tissue-and context-specific, sometimes occurring only in one sex and/or diet cohort in a particular tissue. We then constructed tissue-specific interaction networks among genes from these two classes of POE. A key subset of gene pairs show significant epistasis in the F16 LG/J x SM/J advanced intercross data in cases where the biallelic gene fell within a previously-identified metabolic POE QTL interval. We highlight one such interaction in adipose, between Nnat and Mogat1, which associates with POE on multiple adiposity traits. Both genes localize to the endoplasmic reticulum of adipocytes and play a role in adipogenesis. Additionally, expression of both genes is significantly correlated in human visceral adipose tissue. The genes and networks we present here represent a set of actionable interacting candidates that can be probed to further identify the machinery driving POE on complex traits.

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