scholarly journals A time-dependent genome-wide SNP-SNP interaction analysis of chicken body weight

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Fang-Ge Li ◽  
Hui Li
Keyword(s):  
Body Weight ◽  
Genetic Interaction ◽  
Interaction Analysis ◽  
Interaction Network ◽  
Genetic Network ◽  
Time Dependent ◽  
Model Organisms ◽  
Multiple Time ◽  
Genome Wide ◽  
Snp Interaction

Abstract Background The important property of the quantitative traits of model organisms is time-dependent. However, the methodology for investigating the genetic interaction network over time is still lacking. Our study aims to provide insights into the mechanistic basis of epistatic interactions affecting the phenotypes of model organisms. Results We performed an exhaustive genome-wide search for significant SNP-SNP interactions associated with male birds’ body weight (BW) (n = 475) at multiple time points (day of hatch (BW0) and 1, 3, 5, and 7 weeks (BW1, BW3, BW5, and BW7)). Statistical analysis detected 67, four, and two significant SNP pairs associated with BW0, BW1, and BW3, respectively, with a significance threshold at 8.67 × 10− 12 (Bonferroni-adjusted: 1%). Meanwhile, no significant SNP pairs associated with BW5 and BW7 were found. The SNP-SNP interaction networks of BW0, BW1, and BW3 were built and annotated. Conclusions With strong annotated information and a strict significant threshold, SNP-SNP interactions underpinned the gene-gene interactions that might occur between chromosomes or within the same chromosome. Comparing and combing the networks, the results indicated that the genetic network for chicken body weight was dynamic and time-dependent.

scholarly journals A Time-dependent Genome-Wide SNP-SNP Interaction Analysis of Chicken Body Weight

2019 ◽  
Author(s):  
Fang-Ge Li ◽  
Hui Li
Keyword(s):  
Body Weight ◽  
Genetic Interaction ◽  
Interaction Analysis ◽  
Interaction Network ◽  
Genetic Network ◽  
Time Dependent ◽  
Model Organisms ◽  
Multiple Time ◽  
Genome Wide ◽  
Snp Interaction

Abstract Background The important property of the quantitative traits of model organisms is time-dependent. However, the methodology for investigating the genetic interaction network over time is still lacking. Our study aims to provide insights into the mechanistic basis of epistatic interactions affecting the phenotypes of model organisms. Results We performed an exhaustive genome-wide search for significant SNP-SNP interactions associated with male birds’ body weight (BW) (n=475) at multiple time points (day of hatch (BW0) and one, three, five, and seven weeks (BW1, BW3, BW5, and BW7)). Statistical analysis detected 67, four, and two significant SNP pairs associated with BW0, BW1, and BW3, respectively, with a significance threshold at 8.67×10 −12 (Bonferroni-adjusted: 1%). Meanwhile, no significant SNP pairs associated with BW5 and BW7 were found. The SNP-SNP interaction networks of BW0, BW1, and BW3 were built and annotated. Conclusions With strong annotated information and a strict significant threshold, SNP-SNP interactions underpinned the gene-gene interactions that might occur between chromosomes or within the same chromosome. Comparing and combing the networks, the results indicated that the genetic network for chicken body weight was dynamic and time-dependent.

scholarly journals A Time-dependent Genome-Wide SNP-SNP Interaction Analysis of Chicken Body Weight

2019 ◽  
Author(s):  
Fang-Ge Li ◽  
Hui Li
Keyword(s):  
Body Weight ◽  
Genetic Interaction ◽  
Interaction Analysis ◽  
Interaction Network ◽  
Genetic Network ◽  
Time Dependent ◽  
Model Organisms ◽  
Multiple Time ◽  
Genome Wide ◽  
Snp Interaction

Abstract Background The important property of the quantitative traits of model organisms is time-dependent. However, the methodology for investigating the genetic interaction network over time is still lacking. Our study aims to provide insights into the mechanistic basis of epistatic interactions affecting the phenotypes of model organisms. Results We performed an exhaustive genome-wide search for significant SNP-SNP interactions associated with male birds’ body weight (n=475) at multiple time points (day of hatch body weight (BW0) and one, three, five and seven weeks (BW1, BW3, BW5, BW7). Statistical analysis detected 67, 4, and 2 significant SNP pairs associated with BW0, BW1, and BW3, respectively, with a significance threshold at 8.67×10 −12 (Bonferroni-adjusted: 1%). Meanwhile, no significant SNP pairs associated with BW5 and BW7 were found. The SNP-SNP interaction networks of BW0, BW1, and BW3 were built and annotated. Conclusions With strong annotated information and a strict significant threshold, SNP-SNP interactions underpinned the gene-gene interactions that might occur between chromosomes or within the same chromosome. Comparing and combing the networks, the results indicated that the genetic network for chicken body weight was dynamic and time-dependent.

scholarly journals Epistasis for Head Morphology in Drosophila melanogaster

2021 ◽  
Author(s):  
Ergi D Özsoy ◽  
Murat Yılmaz ◽  
Bahar Patlar ◽  
Güzin Emecen ◽  
Esra Durmaz ◽  
...  
Keyword(s):  
Drosophila Melanogaster ◽  
Genetic Interaction ◽  
Interaction Network ◽  
Gene Interaction ◽  
Model Organisms ◽  
Association Analyses ◽  
Genome Wide ◽  
Genetic Interaction Network ◽  
Single Marker ◽  
Head Morphology

Abstract Epistasis – gene-gene interaction – is common for mutations with large phenotypic effects in humans and model organisms. Epistasis impacts quantitative genetic models of speciation, response to natural and artificial selection, genetic mapping and personalized medicine. However, the existence and magnitude of epistasis between alleles with small quantitative phenotypic effects is controversial and difficult to assess. Here, we use the Drosophila melanogaster Genetic Reference Panel of sequenced inbred lines to evaluate the magnitude of naturally occurring epistasis modifying the effects of mutations in jing and inv, two transcription factors that have subtle quantitative effects on head morphology as homozygotes. We find significant epistasis for both mutations and performed single marker genome wide association analyses to map candidate modifier variants and loci affecting head morphology. A subset of these loci was significantly enriched for a known genetic interaction network, and mutations of the candidate epistatic modifier loci also affect head morphology.

scholarly journals Genome-wide mapping of unexplored essential regions in the Saccharomyces cerevisiae genome: evidence for hidden synthetic lethal combinations in a genetic interaction network

2014 ◽  
Vol 42 (15) ◽  
pp. 9838-9853 ◽  
Author(s):  
Saeed Kaboli ◽  
Takuya Yamakawa ◽  
Keisuke Sunada ◽  
Tao Takagaki ◽  
Yu Sasano ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Genetic Interaction ◽  
Interaction Network ◽  
Essential Genes ◽  
Genetic Interactions ◽  
Lethal Gene ◽  
Synthetic Lethal ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale

Abstract Despite systematic approaches to mapping networks of genetic interactions in Saccharomyces cerevisiae, exploration of genetic interactions on a genome-wide scale has been limited. The S. cerevisiae haploid genome has 110 regions that are longer than 10 kb but harbor only non-essential genes. Here, we attempted to delete these regions by PCR-mediated chromosomal deletion technology (PCD), which enables chromosomal segments to be deleted by a one-step transformation. Thirty-three of the 110 regions could be deleted, but the remaining 77 regions could not. To determine whether the 77 undeletable regions are essential, we successfully converted 67 of them to mini-chromosomes marked with URA3 using PCR-mediated chromosome splitting technology and conducted a mitotic loss assay of the mini-chromosomes. Fifty-six of the 67 regions were found to be essential for cell growth, and 49 of these carried co-lethal gene pair(s) that were not previously been detected by synthetic genetic array analysis. This result implies that regions harboring only non-essential genes contain unidentified synthetic lethal combinations at an unexpectedly high frequency, revealing a novel landscape of genetic interactions in the S. cerevisiae genome. Furthermore, this study indicates that segmental deletion might be exploited for not only revealing genome function but also breeding stress-tolerant strains.

scholarly journals Epistatic Effects on Abdominal Fat Content in Chickens: Results from a Genome-Wide SNP-SNP Interaction Analysis

PLoS ONE ◽  
2013 ◽  
Vol 8 (12) ◽  
pp. e81520 ◽  
Author(s):  
Fangge Li ◽  
Guo Hu ◽  
Hui Zhang ◽  
Shouzhi Wang ◽  
Zhipeng Wang ◽  
...  
Keyword(s):  
Interaction Analysis ◽  
Abdominal Fat ◽  
Fat Content ◽  
Epistatic Effects ◽  
Genome Wide ◽  
A Genome ◽  
Snp Interaction

scholarly journals Peptidoglycan synthesis in Mycobacterium tuberculosis is organized into networks with varying drug susceptibility

2015 ◽  
Vol 112 (42) ◽  
pp. 13087-13092 ◽  
Author(s):  
Karen J. Kieser ◽  
Catherine Baranowski ◽  
Michael C. Chao ◽  
Jarukit E. Long ◽  
Christopher M. Sassetti ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Interaction Network ◽  
Genetic Network ◽  
Drug Susceptibility ◽  
Model Organisms ◽  
Human Pathogen ◽  
Synthetic Enzymes ◽  
Alternative Pathways ◽  
Peptidoglycan Synthesis ◽  
Complex Polymer

Peptidoglycan (PG), a complex polymer composed of saccharide chains cross-linked by short peptides, is a critical component of the bacterial cell wall. PG synthesis has been extensively studied in model organisms but remains poorly understood in mycobacteria, a genus that includes the important human pathogen Mycobacterium tuberculosis (Mtb). The principle PG synthetic enzymes have similar and, at times, overlapping functions. To determine how these are functionally organized, we carried out whole-genome transposon mutagenesis screens in Mtb strains deleted for ponA1, ponA2, and ldtB, major PG synthetic enzymes. We identified distinct factors required to sustain bacterial growth in the absence of each of these enzymes. We find that even the homologs PonA1 and PonA2 have unique sets of genetic interactions, suggesting there are distinct PG synthesis pathways in Mtb. Either PonA1 or PonA2 is required for growth of Mtb, but both genetically interact with LdtB, which has its own distinct genetic network. We further provide evidence that each interaction network is differentially susceptible to antibiotics. Thus, Mtb uses alternative pathways to produce PG, each with its own biochemical characteristics and vulnerabilities.

scholarly journals Towards an Integrated Map of Genetic Interactions in Cancer Cells

2017 ◽  
Author(s):  
Benedikt Rauscher ◽  
Florian Heigwer ◽  
Luisa Henkel ◽  
Thomas Hielscher ◽  
Oksana Voloshanenko ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Genetic Variants ◽  
Genetic Interaction ◽  
Human Cancer ◽  
Genetic Network ◽  
Genetic Interactions ◽  
Model Organisms ◽  
Genetic Screens ◽  
New Genotype ◽  
Analytical Approaches

ABSTRACTCancer genomes often harbor hundreds of molecular aberrations. Such genetic variants can be drivers or passengers of tumorigenesis and, as a side effect, create new vulnerabilities for potential therapeutic exploitation. To systematically identify genotype-dependent vulnerabilities and synthetic lethal interactions, forward genetic screens in different genetic backgrounds have been conducted. We devised MINGLE, a computational framework that integrates CRISPR/Cas9 screens originating from many different libraries and laboratories to build genetic interaction maps. It builds on analytical approaches that were established for genetic network discovery in model organisms. We applied this method to integrate and analyze data from 85 CRISPR/Cas9 screens in human cancer cell lines combining functional data with information on genetic variants to explore the relationships of more than 2.1 million gene-background relationships. In addition to known dependencies, our analysis identified new genotype-specific vulnerabilities of cancer cells. Experimental validation of predicted vulnerabilities associated with aberrant Wnt/β-catenin signaling identifiedGANABandPRKCSHas new positive regulators of Wnt/β-catenin signaling. By clustering genes with similar genetic interaction profiles, we drew the largest genetic network in cancer cells to date. Our scalable approach highlights how diverse genetic screens can be integrated to systematically build informative maps of genetic interactions in cancer, which can grow dynamically as more data is included.

Abstract 178: RCBTB1 Genotypes Modulate Smoking Effect on Carotid Intima-Media Thickness: A Finding from a Genome-Wide Interaction Analysis

2012 ◽  
Vol 32 (suppl_1) ◽  
Author(s):  
Chuanhui Dong ◽  
Liyong Wang ◽  
Digna Cabral ◽  
Ashley Beecham ◽  
Susan H Blanton ◽  
...  
Keyword(s):  
Cigarette Smoking ◽  
Interaction Analysis ◽  
Intima Media Thickness ◽  
Carotid Intima Media Thickness ◽  
Carotid Imt ◽  
Media Thickness ◽  
Genome Wide ◽  
Cigarette Pack ◽  
A Genome ◽  
Snp Interaction

Objective: Smoking is an established risk factor for atherosclerotic disease. However, the degree of the cigarette smoking-induced damage varies from individual to individual, partly due to the between-individual difference in genetic makeup. The aim of this study was to identify genetic loci influencing the effect of cigarette smoking on carotid intima-media thickness (IMT) by performing a genome-wide association smoking-by-SNP interaction analysis. Methods and results: Genome-wide genotyping was performed using the Affymetrix SNP array 6.0 among 1,010 individuals who underwent B-mode ultrasound examination of carotid IMT from the population-based Northern Manhattan Study. Cigarette pack-years was calculated as number of years smoked multiplied by number of cigarettes smoked per day, then divided by 20. After quality control, a total of 722,379 single nucleotide polymorphisms (SNPs) were included in the final analysis. Generalized linear modeling was conducted to look for smoking-by-SNP interaction on carotid IMT while controlling for age, sex, hypertension, diabetes, dyslipidemia, body mass index, waist-to-hip ratio, and the top 3 principal components estimated to capture ancestry by EIGENSTRAT. Ten SNPs near or within 5 genes showed an interactive effect with cigarette smoking on IMT with a p value <1.0E-5. Among them, 3 SNPs (including 1 exonic splice enhancer SNP rs3751283, P=8.3E-7) are near or within regulator of chromosome condensation and BTB domain containing protein 1 (RCBTB1) gene on 13q14. Specifically, for SNP rs3751283, the mean IMT was substantially increased among CC-carriers (0.70 mm, 0.76 mm, 0.81 mm for 0, <20, and ≥20 cigarette pack-years, respectively, P=2.6E-6), slightly increased with smoking pack-years among TC-carriers (0.72 mm, 0.74 mm, 0.75 mm for 0, <20, and ≥20 cigarette pack-years, respectively, P=0.03), but very similar (0.73 mm) among TT-carriers for the three smoking groups (P=0.84). Conclusion: Our genome-wide interaction analysis reveals multiple genes, especially RCBTB1, that may modify the effect of smoking on carotid IMT. These genes will be further evaluated in our full dataset with additional genotyping. Also, larger independent studies are needed to validate these findings.

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