Comprehensive Human Genetic Maps: Individual and Sex-Specific Variation in Recombination

Broman, Karl W.; Murray, Jeffrey C.; Sheffield, Val C.; White, R.; Weber, James L.

doi:10.1086/302011

Cited by 1,026 publications

(973 citation statements)

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“…Marker distances were assigned from the Decode map if available. For markers not mapped by Decode, the original distance provided on the Marshfield website 36 was transformed by linear interpolation from adjacent markers with known Decode map values. 37 Phenotype Data on smoking behavior were collected in every survey (1991,1993,1995,1997,2000) and most subjects participated more than once.…”

Section: Dna Collection and Genotypingmentioning

confidence: 99%

Linkage analysis of smoking initiation and quantity in Dutch sibling pairs

et al. 2004

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The heritability of smoking initiation (SI) and number of cigarettes smoked (NC) was determined in 3657 Dutch twin pairs. For SI a heritability of 36% was found and for NC of 51%. Both SI and NC were also significantly influenced by environmental factors shared by family members. The etiological factors that influence these traits partly overlap. Linkage analyses were performed on data of 536 DZ twins and siblings from 192 families, forming 592 sibling pairs. Results suggested QTLs on chromosome 6 (LOD ¼ 3.05) and chromosome 14 (LOD ¼ 1.66) for SI and on chromosome 3 (LOD ¼ 1.98) for NC. Strikingly, on chromosome 10 a peak was found in the same region for both SI (LOD ¼ INTRODUCTIONLarge-scale population-based twin and family studies have shown that genetic factors contribute to individual differences in smoking behavior. 1-4 Several different, possibly correlated, dimensions of smoking behavior can be distinguished: smoking initiation (SI), number of cigarettes smoked per day and nicotine dependence (ND). 5 Koopmans et al 6 investigated the heritability of SI and the number of cigarettes smoked per day (NC) in adolescent Dutch twins by considering a single liability model, an independent liability model and a combined model. The combined model best described the data and showed that 39% of the variance in SI and 86% of the variance in NC was explained by genetic influences. Kendler et al 7 found that liabilities to SI and ND were substantially correlated but not identical, and that heritable factors played an important role in both SI and in ND.The next step after obtaining evidence for significant heritability is to identify chromosomal regions involved in smoking behavior, either by linkage or association approaches. 8 Both human and animal studies have explored candidate genes for smoking behavior. Association studies point to dopamine receptor genes, dopamine transporter genes, cytochrome P450 and serotonergic genes. 9,10 Association studies have relatively high statistical power, and can detect quantitative trait loci (QTLs) with only small effects. A possible disadvantage of the candidate gene approach is that the focus is on known pathways, which may lead us to overlook genes that are etiologically important, because of our ignorance of other biological systems involved. In contrast, linkage analysis will identify chromosomal regions that harbor known and

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Section: Dna Collection and Genotypingmentioning

confidence: 99%

Linkage analysis of smoking initiation and quantity in Dutch sibling pairs

et al. 2004

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“…Brown et al (1999) also noted elevated LOH rates at 8p12-22 in ovarian (Talbot and Cuticchia, 1999). b Distances in centimorgans (cM) from the Marshfield Chromosome 19 Sex-Averaged linkage map (Broman et al, 1998). c Distances in centirays (cR) from the International Radiation Hybrid Mapping Consortium (GeneMap'99) (Deloukas et al, 1998).…”

Section: Discussionmentioning

confidence: 99%

High rates of loss of heterozygosity on chromosome 19p13 in human breast cancer

et al. 2001

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The oestrogen receptor (ER) is a nuclear steroid receptor that upon activation by its ligands (e.g. oestrogen) initiates a cascade of events resulting in increased cellular proliferation in its target tissues (Warner et al, 1999). Since oestrogen is one of the most potent mitogens for breast cancer cells, it is no surprise that ER is the most important target for endocrine therapy of breast cancer (Osborne, 1998). Recently, a number of factors which regulate nuclear hormone receptor activity have been identified. Cofactors capable of increasing receptor action, termed coactivators, include transcriptional intermediary factor 1 (TIF1), nuclear receptor interacting protein (NRIP1), nuclear receptor coactivator 2 (TIF2), steroid receptor coactivator 1 (SRC1), amplified in breast cancer 1 (AIB1), the cyclic AMP (cAMP)-response element binding protein (CREB) binding protein (CBP) (Glass et al, 1997;Shibata et al, 1997) and many more. The family of corepressors (negative regulators) of ER is smaller; the best characterized ones being the nuclear receptor corepressor (N-CoR) (Horlein et al, 1995;Shibata et al, 1997) the silencing mediator of retinoid and thyroid receptors (SMRT) (Chen and Evans, 1995;Sande and Privalsky, 1996) and the repressor of ER activity (REA) (Montano et al, 1999). The overexpression of coactivators or the loss of corepressors could lead to deregulation of oestrogen-dependent pathways related to mammary epithelial cell proliferation, and thus to breast tumorigenesis. And indeed, some of the ER cofactors have recently been characterized as playing major roles in breast tumorigenesis (Horlein et al, 1995;Anzick et al, 1997;Shibata et al, 1997). The ER coactivator AIB1 was cloned during a search on the long arm of chromosome 20 for genes whose expression and copy number are elevated in human breast cancer, and subsequent analysis in 105 breast tumour specimens confirmed its overexpression (Anzick et al, 1997). Interestingly, the breast/ovarian tumour suppressor gene BRCA1 has recently been characterized as an ER corepressor (Fan, 1999) again suggesting that ER coregulators are crucial in breast tumorigenesis. Thus, it might be expected that other ER coactivators and corepressors might play similar important roles in breast cancer development and progression.The nuclear matrix protein SAFB (Renz, 1996;Oesterreich, 1997) has been shown to be an ER corepressor . ER and SAFB interact in in-vitro binding assays (Glutathione-S-Transferase [GST]-pulldown assays) and in cell lines (co-immunoprecipitation experiments). In cell lines, there is binding of SAFB to ER in the presence or absence of oestradiol; however, binding is significantly increased by the antioestrogen tamoxifen. Overexpression of SAFB results in repression of oestrogen-mediated transactivation of gene expression by the ER. Furthermore, as a result of SAFB overexpression, the antagonist activity of tamoxifen on ER can be enhanced, and the agonist activity of tamoxifen can be inhibited.These results led us to investigate whether the ER corep...

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“…The MLINK program of the FASTLINK computer package was utilized for two-point linkage analysis [5], while multipoint analysis was performed using ALLEGRO [6] with map distances from the Marshfield genetic map [7], DeCode genetic map [8], or estimated using Map-O-Mat [9]. Some of the families were too large to analyze in their entirety using ALLEGRO and were therefore broken into two or more branches for the analysis, then the logarithmic odds (LOD) scores from each branch of the family were summed.…”

Section: Linkage Analysismentioning

confidence: 99%

Novel sequence variants in the TMIE gene in families with autosomal recessive nonsyndromic hearing impairment

et al. 2005

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To date, 37 genes have been identified for nonsyndromic hearing impairment (NSHI). Identifying the functional sequence variants within these genes and knowing their population-specific frequencies is of public health value, in particular for genetic screening for NSHI. To determine putatively functional sequence variants in the transmembrane inner ear (TMIE) gene in Pakistani and Jordanian families with autosomal recessive (AR) NSHI, four Jordanian and 168 Pakistani families with ARNSHI that is not due to GJB2 (CX26) were submitted to a genome scan. Twopoint and multipoint parametric linkage analyses were performed, and families with logarithmic odds (LOD) scores of 1.0 or greater within the TMIE region underwent further DNA sequencing. The evolutionary conservation and location in predicted protein domains of amino acid residues where sequence variants occurred were studied to elucidate the possible effects of these sequence variants on function. Of seven families that were screened for TMIE, putatively functional sequence variants were found to segregate with hearing impairment in four families but were not seen in not less than 110 ethnically matched control chromosomes. The previously reported c. 241C>T (p.R81C) variant was observed in two Pakistani families. Two novel variants, c.92A>G (p.E31G) and the splice site mutation c.212-2A>C, were identified in one Pakistani and one Jordanian family, respectively. The c.92A>G (p.E31G) variant occurred at a residue that is conserved in the mouse and is predicted to be extracellular. Conservation and potential functionality of previously published mutations were also examined. The prevalence of functional TMIE variants in Pakistani families is 1.7% [95% confidence interval (CI) 0.3-4.8]. Further studies on the spectrum, prevalence rates, and functional effect of sequence variants in the TMIE gene in other populations should demonstrate the true importance of this gene as a cause of hearing impairment.

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Comprehensive Human Genetic Maps: Individual and Sex-Specific Variation in Recombination

Cited by 1,026 publications

References 29 publications

Linkage analysis of smoking initiation and quantity in Dutch sibling pairs

Linkage analysis of smoking initiation and quantity in Dutch sibling pairs

High rates of loss of heterozygosity on chromosome 19p13 in human breast cancer

Novel sequence variants in the TMIE gene in families with autosomal recessive nonsyndromic hearing impairment

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