EGFR NCBI Gene
Description: epidermal growth factor receptor
Organism: Homo sapiens
Chromosome: 7
Map location: 7p11.2
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ERBB2 NCBI Gene
Description: erb-b2 receptor tyrosine kinase 2
Organism: Homo sapiens
Chromosome: 17
Map location: 17q12
View NCBI Gene RecordTP53 NCBI Gene
Description: tumor protein p53
Organism: Homo sapiens
Chromosome: 17
Map location: 17p13.1
View NCBI Gene RecordIL6 NCBI Gene
Description: interleukin 6
Organism: Homo sapiens
Chromosome: 7
Map location: 7p15.3
View NCBI Gene RecordBRAF NCBI Gene
Description: B-Raf proto-oncogene, serine/threonine kinase
Organism: Homo sapiens
Chromosome: 7
Map location: 7q34
View NCBI Gene RecordarXiv Research Articles
Causes and Consequences of genetic background effects illuminated by integrative genomic analysis arXiv
Published: September 2, 2013
Authors: Christopher H. Chandler, Sudarshan Chari, David Tack, Ian Dworkin
The phenotypic consequences of individual mutations are modulated by the wild type genetic background in which they occur.Although such background dependence is widely observed, we do not know whether general patterns across species and traits exist, nor about the mechanisms underlying it. We also lack knowledge on how mutations interact with genetic background to influence gene expression, and how this in turn mediates mutant phenotypes. Furthermore, how genetic background influences patterns of epistasis remains unclear. To investigate the genetic basis and genomic consequences of genetic background dependence of the scallopedE3 allele on the Drosophila melanogaster wing, we generated multiple novel genome level datasets from a mapping by introgression experiment and a tagged RNA gene expression dataset. In addition we used whole genome re-sequencing of the parental lines two commonly used laboratory strains to predict polymorphic transcription factor binding sites for SD. We integrated these data with previously published genomic datasets from expression microarrays and a modifier mutation screen. By searching for genes showing a congruent signal across multiple datasets, we were able to identify a robust set of candidate loci contributing to the background dependent effects of mutations in sd. We also show that the majority of background-dependent modifiers previously reported are caused by higher-order epistasis, not quantitative non-complementation. These findings provide a useful foundation for more detailed investigations of genetic background dependence in this system, and this approach is likely to prove useful in exploring the genetic basis of other traits as well.
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Does your gene need a background check? How genetic background impacts the analysis of mutations, genes, and evolution arXiv
Published: January 12, 2013
Authors: Chris H. Chandler, Sudarshan Chari, Ian Dworkin
The premise of genetic analysis is that a causal link exists between phenotypic and allelic variation. Yet it has long been documented that mutant phenotypes are not a simple result of a single DNA lesion, but rather are due to interactions of the focal allele with other genes and the environment. Although an experimentally rigorous approach, focusing on individual mutations and isogenic control strains, has facilitated amazing progress within genetics and related fields, a glimpse back suggests that a vast complexity has been omitted from our current understanding of allelic effects. Armed with traditional genetic analyses and the foundational knowledge they have provided, we argue that the time and tools are ripe to return to the under-explored aspects of gene function and embrace the context-dependent nature of genetic effects. We assert that a broad understanding of genetic effects and the evolutionary dynamics of alleles requires identifying how mutational outcomes depend upon the wild-type genetic background. Furthermore, we discuss how best to exploit genetic background effects to broaden genetic research programs.
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A Unified Model of Codon Reassignment in Alternative Genetic Codes arXiv
Published: October 19, 2004
Authors: Supratim Sengupta, Paul G. Higgs
Many modified genetic codes are found in specific genomes in which one or more codons have been reassigned to a different amino acid from that in the canonical code. We present a model that unifies four possible mechanisms for reassignment, based on the observation that reassignment involves a gain and a loss. The loss could be the deletion or loss of function of a tRNA or release factor. The gain could be the gain of a new type of tRNA for the reassigned codon, or the gain of function of an existing tRNA due to a mutation or a base modification. In the codon disappearance mechanism, the codon disappears from the genome during the period of reassignment. In the other mechanisms, the codon does not disappear. In the ambiguous intermediate mechanism, the gain precedes the loss; in the unassigned codon mechanism, the loss precedes the gain; and in the compensatory change mechanism, the loss and gain spread through the population simultaneously. We present simulations of the gain-loss model and demonstrate that all four mechanisms are possible. The frequencies of the different mechanisms are influenced by selection strengths, number of codons undergoing reassignment, directional mutation pressure and the possibility of selection for reduced genome size.
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Kingman and mathematical population genetics arXiv
Published: May 25, 2010
Authors: Warren J. Ewens, Geoffrey A. Watterson
Mathematical population genetics is only one of Kingman's many research interests. Nevertheless, his contribution to this field has been crucial, and moved it in several important new directions. Here we outline some aspects of his work which have had a major influence on population genetics theory.
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The genetic architecture of adaptations to high altitude in Ethiopia arXiv
Published: November 13, 2012
Authors: Gorka Alkorta-Aranburu, Cynthia M. Beall, David B. Witonsky, Amha Gebremedhin, Jonathan K. Pritchard, Anna Di Rienzo
Although hypoxia is a major stress on physiological processes, several human populations have survived for millennia at high altitudes, suggesting that they have adapted to hypoxic conditions. This hypothesis was recently corroborated by studies of Tibetan highlanders, which showed that polymorphisms in candidate genes show signatures of natural selection as well as well-replicated association signals for variation in hemoglobin levels. We extended genomic analysis to two Ethiopian ethnic groups: Amhara and Oromo. For each ethnic group, we sampled low and high altitude residents, thus allowing genetic and phenotypic comparisons across altitudes and across ethnic groups. Genome-wide SNP genotype data were collected in these samples by using Illumina arrays. We find that variants associated with hemoglobin variation among Tibetans or other variants at the same loci do not influence the trait in Ethiopians. However, in the Amhara, SNP rs10803083 is associated with hemoglobin levels at genome-wide levels of significance. No significant genotype association was observed for oxygen saturation levels in either ethnic group. Approaches based on allele frequency divergence did not detect outliers in candidate hypoxia genes, but the most differentiated variants between high- and lowlanders have a clear role in pathogen defense. Interestingly, a significant excess of allele frequency divergence was consistently detected for genes involved in cell cycle control, DNA damage and repair, thus pointing to new pathways for high altitude adaptations. Finally, a comparison of CpG methylation levels between high- and lowlanders found several significant signals at individual genes in the Oromo.
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