Fanconi anemia (FA) and Bloom's syndrome (BS) overlap at the clinical and molecular levels.

<p>Left panel: Comparison of the clinical and cellular features present in FA and BS. FA and BS have features that are distinct to each syndrome; however, there are broad similarities. Some individuals with mutations in <i>BLM</i> have been diagnosed with FA, exhibiting classical FA features. Right panel: Depiction of a super-complex that is formed at sites of repair of replication forks that have been impeded by an inter-strand crosslink. The super-complex consists of two complexes that form independently in the nucleus. One complex consists of the interacting proteins identified through FA mutations and the other complex consists of proteins that interact with BLM, the gene mutated in BS <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003008#pgen.1003008-Meetei1" target="_blank">[33]</a>. These two complexes are brought together by mutual interactions with the FA gene product FANCM <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003008#pgen.1003008-Deans1" target="_blank">[34]</a>. Molecular interactions between FANCJ and BLM at stalled forks have also been described <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003008#pgen.1003008-Suhasini1" target="_blank">[35]</a>. Downstream signaling effects (FAND2 ubiquitylation and ATR activation) are also depicted. Figure was redrawn from Deans and West <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003008#pgen.1003008-Deans1" target="_blank">[34]</a>.</p

UES algorithm visualization.

<p>This represents the generalized workflow to determine the SNP enrichment in an ENCODE track. A full description and details of the algorithm can be found in the Materials and Methods.</p

Overlap of lymphoma risk SNPs with regulatory regions in GM12878.

<p>The histograms represent the distribution of how many random loci overlap a specific annotation. The blue represents the mean of the empirical null distribution while the red line represents the real number of loci from the lymphoma and CLL GWAS that overlap the specific regulatory annotation. A, Overlap of SNPs with DNase hypersensitivity regions in GM12878. B, Overlap of SNPs with active promoters and strong enhancers as annotated by ChromHMM in GM12878. C, Overlap of SNPs with active promoters and strong enhancers as annotated by Segway in GM12878.</p

Enrichment of lymphoma and CLL risk SNPs in DNase-hypersensitive sites of lymphoblastoid cell lines.

<p>(A-I) These histograms represent the distribution of how many random loci overlap a specific annotation. The blue represents the mean of the empirical null distribution while the red line represents the real number of loci from the lymphoma and CLL GWAS that overlap the DNase hypersensitive site in the specified cell line: (A) GM19238 (B) GM19240 (C) GM12864 (D) GM12865 (E) GM06990 (F) GM19239 (G) GM18507 (H) GM12892 (I) GM12891. (J) Th0 (K) CD20+ (L) Summary of distribution of tissue of origin for cell lines in which lymphoma and CLL risk SNPs are either enriched (p<0.0004) in DNase hypersensitive sites or not enriched.</p

The Ashkenazi founder mutations occur on common haplotypes and are not highly correlated with anonymous single nucleotide polymorphisms likely to be used in genome-wide case-control association studies-1

<p><b>Copyright information:</b></p><p>Taken from "The Ashkenazi founder mutations occur on common haplotypes and are not highly correlated with anonymous single nucleotide polymorphisms likely to be used in genome-wide case-control association studies"</p><p>http://www.biomedcentral.com/1471-2156/8/68</p><p>BMC Genetics 2007;8():68-68.</p><p>Published online 4 Oct 2007</p><p>PMCID:PMC2093936.</p><p></p>wn true size. Anchor lines link to position of the SNP within the region. B-F) LDSelect creates bins of SNPs that have an value of 0.8 or greater with at least one other SNP in the bin. Each vertical line and arrowhead represents a SNP, with dashed lines and shaded background connecting SNPs within the same bin. Down arrowheads indicate Tag SNPs (those with ≥ 0.8 with all other SNPs in a bin). Note that this use of the term Tag-SNP is different from Haploview – with LDSelect, only one Tag-SNP per bin would be required to capture the majority of the nucleotide diversity. Singleton bins (SNPs that did not have ≥ 0.8 with any other SNP) are indicated by solid dots on a single row. SNP number refers to numbering in column 1 of Table 1

The Ashkenazi founder mutations occur on common haplotypes and are not highly correlated with anonymous single nucleotide polymorphisms likely to be used in genome-wide case-control association studies-0

<p><b>Copyright information:</b></p><p>Taken from "The Ashkenazi founder mutations occur on common haplotypes and are not highly correlated with anonymous single nucleotide polymorphisms likely to be used in genome-wide case-control association studies"</p><p>http://www.biomedcentral.com/1471-2156/8/68</p><p>BMC Genetics 2007;8():68-68.</p><p>Published online 4 Oct 2007</p><p>PMCID:PMC2093936.</p><p></p>e indicated by arrowheads; htSNPs in only one population are shown on a yellow background while the single htSNP shared between all populations is shown on a green background

Assessment of <i>SLX4</i> Mutations in Hereditary Breast Cancers

<div><p>Background</p><p><i>SLX4</i> encodes a DNA repair protein that regulates three structure-specific endonucleases and is necessary for resistance to DNA crosslinking agents, topoisomerase I and poly (ADP-ribose) polymerase (PARP) inhibitors. Recent studies have reported mutations in <i>SLX4</i> in a new subtype of Fanconi anemia (FA), FA-P. Monoallelic defects in several FA genes are known to confer susceptibility to breast and ovarian cancers.</p><p>Methods and Results</p><p>To determine if <i>SLX4</i> is involved in breast cancer susceptibility, we sequenced the entire <i>SLX4</i> coding region in 738 (270 Jewish and 468 non-Jewish) breast cancer patients with 2 or more family members affected by breast cancer and no known <i>BRCA1</i> or <i>BRCA2</i> mutations. We found a novel nonsense (c.2469G>A, p.W823*) mutation in one patient. In addition, we also found 51 missense variants [13 novel, 23 rare (MAF<0.1%), and 15 common (MAF>1%)], of which 22 (5 novel and 17 rare) were predicted to be damaging by Polyphen2 (score = 0.65–1). We performed functional complementation studies using p.W823* and 5 <i>SLX4</i> variants (4 novel and 1 rare) cDNAs in a human <i>SLX4</i>-null fibroblast cell line, RA3331. While wild type <i>SLX4</i> and all the other variants fully rescued the sensitivity to mitomycin C (MMC), campthothecin (CPT), and PARP inhibitor (Olaparib) the p.W823* <i>SLX4</i> mutant failed to do so.</p><p>Conclusion</p><p>Loss-of-function mutations in <i>SLX4</i> may contribute to the development of breast cancer in very rare cases.</p></div

Additional file 1: of Comprehensive detection of germline variants by MSK-IMPACT, a clinical diagnostic platform for solid tumor molecular oncology and concurrent cancer predisposition testing

Supplementary Methods and Tables S1-S6. (DOCX 93 kb

Identification of the nonsense<i>SLX4</i> variant and evaluation of pathogenicity of the <i>SLX4</i> variants by complementation assay.

<p>(A) Sanger sequence traces for DNA extracted from whole blood and breast tumor of the patient with the c.2469G>A (p.W823*) <i>SLX4</i> mutation (NCBI Refseq NM_032444.2). (B) Anti-HA immunoblot showing expression of HA-tagged SLX4 variants in RA3331/E6E7/hTERT cells. Alpha-tubulin serves as loading control. (C)∼(E) Cell survival assays of the RA3331/E6E7/hTERT cell lines expressing indicated SLX4 variants in response to MMC (C), CPT (D) and the PARP inhibitor, Olaparib (E). RA3331/E6E7/hTERT fibroblast cell lines expressing empty vector, wild type SLX4 and indicated SLX4 variants were treated in triplicate with increasing concentrations of MMC (0–100 nM), CPT (0–16 nM) and Olaparib (0–50 µM). After 8 days in culture, the cell number was determined using a Coulter counter. The number of cells at each drug concentration was divided by the number of cells in the untreated sample to calculate the percentage of cell survival. The error bars indicate standard deviations based on three replicates.</p

Assessment of sustainability of forest management practices on the operational level in northwestern Russia – a case study from the Republic of Karelia

The main aim of the article is to assess the consequences of newly proposed legislative initiative on introducing intensive forest management practices in Russia. Implementation of norms and its effect on sustainable forest management practices have been analysed in this study on one enterprise operating in the Republic of Karelia. This meant modelling of forest growth, clear cuts and regeneration within 100 km radius from the mill for two alternative management scenarios with fixed demand of wood based on current norms and decreasing harvesting age to half from the current. Wood demand of the enterprise, structure and accessibility of forest resources, i.e. forest road infrastructure were taken into account in the analysis. Both forest management scenarios decreased the total growing stock significantly, and therefore considered as non-sustainable practices. In addition, forest age structure was more uneven for both scenarios at the end of the simulation period. Comparison of two alternative management practices showed that the implementation of intensive forest management in Russia requires new norms that would be based on principles of sustainable forest management.201