scholarly journals Familial heterogeneity in breast cancer predisposition: a study of 22 Utah families

2016 ◽  
Author(s):  
Elizabeth O’Brien ◽  
Richard A. Kerber ◽  
Raymond L. White

AbstractThe problem of “missing heritability” in genome-wide analyses of complex diseases is thought to be attributable to some combination of: rare variants of moderate to large effect, common variants of very small effect, and epigenetic, epistatic, or shared environmental effects. Rare variants do not affect large numbers of people by definition, but identified genes and pathways frequently lead to important insights into pathogenesis, and become targets of chemoprevention or therapy. Family studies remain an efficient way to identify rare variants with sizable effects on disease risk. We present a genome-wide study of breast cancer in 22 large high-risk families including 154 women diagnosed with breast cancer. Appropriate marker spacing was achieved by simulation studies of founder haplotypes to reduce the chance that linkage disequilibrium produced spurious linkage peaks. For each family, we generated 100 simulations of null linkage genome-wide to estimate the probability that individual results were due to chance. We identified a total of 12 putative susceptibility regions with per-family genome-wide probability < 0.05. These regions were located on 10 chromosomes; 10 of the 22 families showed linkage at these locations; two or more families showed linkage to 6 regions on 5 chromosomes (4q, 5q, 6p, 14q, 18p, and 18q). These results indicate that there is considerable heterogeneity among families in genomic regions and thus variants predisposing to breast cancer. Moreover, they suggest that uncommon high– or medium-risk genetic variants remain to be found, and that family designs can be an efficient way to identify them.

Nutrients ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1984
Author(s):  
Majid Nikpay ◽  
Sepehr Ravati ◽  
Robert Dent ◽  
Ruth McPherson

Here, we performed a genome-wide search for methylation sites that contribute to the risk of obesity. We integrated methylation quantitative trait locus (mQTL) data with BMI GWAS information through a SNP-based multiomics approach to identify genomic regions where mQTLs for a methylation site co-localize with obesity risk SNPs. We then tested whether the identified site contributed to BMI through Mendelian randomization. We identified multiple methylation sites causally contributing to the risk of obesity. We validated these findings through a replication stage. By integrating expression quantitative trait locus (eQTL) data, we noted that lower methylation at cg21178254 site upstream of CCNL1 contributes to obesity by increasing the expression of this gene. Higher methylation at cg02814054 increases the risk of obesity by lowering the expression of MAST3, whereas lower methylation at cg06028605 contributes to obesity by decreasing the expression of SLC5A11. Finally, we noted that rare variants within 2p23.3 impact obesity by making the cg01884057 site more susceptible to methylation, which consequently lowers the expression of POMC, ADCY3 and DNAJC27. In this study, we identify methylation sites associated with the risk of obesity and reveal the mechanism whereby a number of these sites exert their effects. This study provides a framework to perform an omics-wide association study for a phenotype and to understand the mechanism whereby a rare variant causes a disease.


Genetics ◽  
2003 ◽  
Vol 164 (1) ◽  
pp. 247-258 ◽  
Author(s):  
Jinghong Li ◽  
Willis X Li

Abstract Overactivation of receptor tyrosine kinases (RTKs) has been linked to tumorigenesis. To understand how a hyperactivated RTK functions differently from wild-type RTK, we conducted a genome-wide systematic survey for genes that are required for signaling by a gain-of-function mutant Drosophila RTK Torso (Tor). We screened chromosomal deficiencies for suppression of a gain-of-function mutation tor (torGOF), which led to the identification of 26 genomic regions that, when in half dosage, suppressed the defects caused by torGOF. Testing of candidate genes in these regions revealed many genes known to be involved in Tor signaling (such as those encoding the Ras-MAPK cassette, adaptor and structural molecules of RTK signaling, and downstream target genes of Tor), confirming the specificity of this genetic screen. Importantly, this screen also identified components of the TGFβ (Dpp) and JAK/STAT pathways as being required for TorGOF signaling. Specifically, we found that reducing the dosage of thickveins (tkv), Mothers against dpp (Mad), or STAT92E (aka marelle), respectively, suppressed torGOF phenotypes. Furthermore, we demonstrate that in torGOF embryos, dpp is ectopically expressed and thus may contribute to the patterning defects. These results demonstrate an essential requirement of noncanonical signaling pathways for a persistently activated RTK to cause pathological defects in an organism.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Soo Bin Kwon ◽  
Jason Ernst

AbstractIdentifying genomic regions with functional genomic properties that are conserved between human and mouse is an important challenge in the context of mouse model studies. To address this, we develop a method to learn a score of evidence of conservation at the functional genomics level by integrating information from a compendium of epigenomic, transcription factor binding, and transcriptomic data from human and mouse. The method, Learning Evidence of Conservation from Integrated Functional genomic annotations (LECIF), trains neural networks to generate this score for the human and mouse genomes. The resulting LECIF score highlights human and mouse regions with shared functional genomic properties and captures correspondence of biologically similar human and mouse annotations. Analysis with independent datasets shows the score also highlights loci associated with similar phenotypes in both species. LECIF will be a resource for mouse model studies by identifying loci whose functional genomic properties are likely conserved.


Animals ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 493
Author(s):  
Salvatore Mastrangelo ◽  
Filippo Cendron ◽  
Gianluca Sottile ◽  
Giovanni Niero ◽  
Baldassare Portolano ◽  
...  

Through the development of the high-throughput genotyping arrays, molecular markers and genes related to phenotypic traits have been identified in livestock species. In poultry, plumage color is an important qualitative trait that can be used as phenotypic marker for breed identification. In order to assess sources of genetic variation related to the Polverara chicken breed plumage colour (black vs. white), we carried out a genome-wide association study (GWAS) and a genome-wide fixation index (FST) scan to uncover the genomic regions involved. A total of 37 animals (17 white and 20 black) were genotyped with the Affymetrix 600 K Chicken single nucleotide polymorphism (SNP) Array. The combination of results from GWAS and FST revealed a total of 40 significant markers distributed on GGA 01, 03, 08, 12 and 21, and located within or near known genes. In addition to the well-known TYR, other candidate genes have been identified in this study, such as GRM5, RAB38 and NOTCH2. All these genes could explain the difference between the two Polverara breeds. Therefore, this study provides the basis for further investigation of the genetic mechanisms involved in plumage color in chicken.


2007 ◽  
Vol 39 (7) ◽  
pp. 870-874 ◽  
Author(s):  
David J Hunter ◽  
Peter Kraft ◽  
Kevin B Jacobs ◽  
David G Cox ◽  
Meredith Yeager ◽  
...  

Plants ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 518
Author(s):  
Siriporn Korinsak ◽  
Clive T. Darwell ◽  
Samart Wanchana ◽  
Lawan Praphaisal ◽  
Siripar Korinsak ◽  
...  

Bacterial leaf blight (BLB) is a serious disease affecting global rice agriculture caused by Xanthomonas oryzae pv. oryzae (Xoo). Most resistant rice lines are dependent on single genes that are vulnerable to resistance breakdown caused by pathogen mutation. Here we describe a genome-wide association study of 222 predominantly Thai rice accessions assayed by phenotypic screening against 20 Xoo isolates. Loci corresponding to BLB resistance were detected using >142,000 SNPs. We identified 147 genes according to employed significance thresholds across chromosomes 1–6, 8, 9 and 11. Moreover, 127 of identified genes are located on chromosomal regions outside estimated Linkage Disequilibrium influences of known resistance genes, potentially indicating novel BLB resistance markers. However, significantly associated SNPs only occurred across a maximum of six Xoo isolates indicating that the development of broad-spectrum Xoo strain varieties may prove challenging. Analyses indicated a range of gene functions likely underpinning BLB resistance. In accordance with previous studies of accession panels focusing on indica varieties, our germplasm displays large numbers of SNPs associated with resistance. Despite encouraging data suggesting that many loci contribute to resistance, our findings corroborate previous inferences that multi-strain resistant varieties may not be easily realised in breeding programs without resorting to multi-locus strategies.


2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi17-vi18
Author(s):  
Crismita Dmello ◽  
Aarón Sonabend ◽  
Víctor Arrieta ◽  
Daniel Zhang ◽  
Deepak Kanojia ◽  
...  

Abstract Paclitaxel (PTX) is one the most potent and commonly used chemotherapies for breast and pancreatic cancer. Given the potency of this drug for glioblastomas (GBM) several ongoing clinical trials are investigating means of enhancing delivery of PTX across the blood-brain barrier for this disease. In spite of the efficacy of PTX, individual tumors exhibit variable susceptibility to this drug, with response rate in the range of 30%-60%. To identify predictive biomarkers for response to PTX, we performed a genome-wide CRISPR knock-out screen using human glioma cells. The most enriched genes in the CRISPR screen underwent further selection based on their correlation with survival in the breast cancer patient cohorts treated with PTX and not in patients treated with other chemotherapies, a finding that was validated on a second independent patient cohort. This led to the discovery of endoplasmic reticulum (ER) protein SSR3 as a putative predictive biomarker for PTX. SSR3 protein levels showed positive correlation with response to PTX in breast cancer cells, glioma cells, in multiple intracranial glioma xenografts and in GBM patient derived explant cultures. Knockout of SSR3 turned the cells resistant to PTX while its overexpression sensitized the cells to PTX. In gliomas, SSR3-mediated susceptibility to PTX relates to modulation of phosphorylation of ER stress sensor IRE1α. Thus, by using genome-wide screen combined with patient response data, we discovered a biomarker that demonstrates causal and correlative relationship with response to PTX in breast cancer and GBM. Prospective validation of this biomarker is warranted for its broad implementation for precision oncology.


2021 ◽  
Vol 11 ◽  
Author(s):  
Matthew J. Rybin ◽  
Melina Ramic ◽  
Natalie R. Ricciardi ◽  
Philipp Kapranov ◽  
Claes Wahlestedt ◽  
...  

Genome instability is associated with myriad human diseases and is a well-known feature of both cancer and neurodegenerative disease. Until recently, the ability to assess DNA damage—the principal driver of genome instability—was limited to relatively imprecise methods or restricted to studying predefined genomic regions. Recently, new techniques for detecting DNA double strand breaks (DSBs) and single strand breaks (SSBs) with next-generation sequencing on a genome-wide scale with single nucleotide resolution have emerged. With these new tools, efforts are underway to define the “breakome” in normal aging and disease. Here, we compare the relative strengths and weaknesses of these technologies and their potential application to studying neurodegenerative diseases.


2021 ◽  
Author(s):  
Richard F Oppong ◽  
Pau Navarro ◽  
Chris S Haley ◽  
Sara Knott

We describe a genome-wide analytical approach, SNP and Haplotype Regional Heritability Mapping (SNHap-RHM), that provides regional estimates of the heritability across locally defined regions in the genome. This approach utilises relationship matrices that are based on sharing of SNP and haplotype alleles at local haplotype blocks delimited by recombination boundaries in the genome. We implemented the approach on simulated data and show that the haplotype-based regional GRMs capture variation that is complementary to that captured by SNP-based regional GRMs, and thus justifying the fitting of the two GRMs jointly in a single analysis (SNHap-RHM). SNHap-RHM captures regions in the genome contributing to the phenotypic variation that existing genome-wide analysis methods may fail to capture. We further demonstrate that there are real benefits to be gained from this approach by applying it to real data from about 20,000 individuals from the Generation Scotland: Scottish Family Health Study. We analysed height and major depressive disorder (MDD). We identified seven genomic regions that are genome-wide significant for height, and three regions significant at a suggestive threshold (p-value <1x10^(-5) ) for MDD. These significant regions have genes mapped to within 400kb of them. The genes mapped for height have been reported to be associated with height in humans, whiles those mapped for MDD have been reported to be associated with major depressive disorder and other psychiatry phenotypes. The results show that SNHap-RHM presents an exciting new opportunity to analyse complex traits by allowing the joint mapping of novel genomic regions tagged by either SNPs or haplotypes, potentially leading to the recovery of some of the "missing" heritability.


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