Concurrent DNA Copy-Number Alterations and Mutations in Genes Related to Maintenance of Genome Stability in Uninvolved Mammary Glandular Tissue from Breast Cancer Patients.

Somatic mosaicism for DNA copy-number alterations (SMC-CNAs) is defined as gain or loss of chromosomal segments in somatic cells within a single organism. As cells harboring SMC-CNAs can undergo clonal expansion, it has been proposed that SMC-CNAs may contribute to the predisposition of these cells to genetic disease including cancer. Herein, the gross genomic alterations (>500 kbp) were characterized in uninvolved mammary glandular tissue from 59 breast cancer patients and matched samples of primary tumors and lymph node metastases. Array-based comparative genomic hybridization showed 10% (6/59) of patients harbored one to 359 large SMC-CNAs (mean: 1,328 kbp; median: 961 kbp) in a substantial portion of glandular tissue cells, distal from the primary tumor site. SMC-CNAs were partially recurrent in tumors, albeit with considerable contribution of stochastic SMC-CNAs indicating genomic destabilization. Targeted resequencing of 301 known predisposition and somatic driver loci revealed mutations and rare variants in genes related to maintenance of genomic integrity: BRCA1 (p.Gln1756Profs*74, p.Arg504Cys), BRCA2 (p.Asn3124Ile), NCOR1 (p.Pro1570Glnfs*45), PALB2 (p.Ser500Pro), and TP53 (p.Arg306*). Co-occurrence of gross SMC-CNAs along with point mutations or rare variants in genes responsible for safeguarding genomic integrity highlights the temporal and spatial neoplastic potential of uninvolved glandular tissue in breast cancer patients.

Draft Genome Sequence of Paracoccus sp. Strain 228, Isolated from Surface Water of the Gulf of Gdansk in the Baltic Sea.

We present here the draft genome sequence of Paracoccus sp. strain 228, isolated from the Gulf of Gdansk in the southern part of the Baltic Sea. The assembly contains 4,131,609 bp in 32 scaffolds.

High-Throughput Tabular Data Processor - Platform independent graphical tool for processing large data sets.

High-throughput technologies generate considerable amount of data which often requires bioinformatic expertise to analyze. Here we present High-Throughput Tabular Data Processor (HTDP), a platform independent Java program. HTDP works on any character-delimited column data (e.g. BED, GFF, GTF, PSL, WIG, VCF) from multiple text files and supports merging, filtering and converting of data that is produced in the course of high-throughput experiments. HTDP can also utilize itemized sets of conditions from external files for complex or repetitive filtering/merging tasks. The program is intended to aid global, real-time processing of large data sets using a graphical user interface (GUI). Therefore, no prior expertise in programming, regular expression, or command line usage is required of the user. Additionally, no a priori assumptions are imposed on the internal file composition. We demonstrate the flexibility and potential of HTDP in real-life research tasks including microarray and massively parallel sequencing, i.e. identification of disease predisposing variants in the next generation sequencing data as well as comprehensive concurrent analysis of microarray and sequencing results. We also show the utility of HTDP in technical tasks including data merge, reduction and filtering with external criteria files. HTDP was developed to address functionality that is missing or rudimentary in other GUI software for processing character-delimited column data from high-throughput technologies. Flexibility, in terms of input file handling, provides long term potential functionality in high-throughput analysis pipelines, as the program is not limited by the currently existing applications and data formats. HTDP is available as the Open Source software (https://github.com/pmadanecki/htdp).

Draft Genome Sequence of Flavobacterium sp. 316, a Baltic Sea Isolate Exhibiting a High Level of Resistance to Marine Stress Conditions.

Here, we present the draft genome sequence ofFlavobacteriumsp. 316, isolated from brackish water of the Gulf of Gdansk, southern Baltic Sea. The assembly contains 3,971,755 bp in 17 scaffolds. The sequence will facilitate postgenomic studies on bacterial stress responses in the challenging habitat of the Baltic Sea.

Analysis of large mutations in BARD1 in patients with breast and/or ovarian cancer: the Polish population as an example.

Only approximately 50% of all familial breast cancers can be explained by known genetic factors, including mutations in BRCA1 and BRCA2. One of the most extensively studied candidates for breast and/or ovarian cancer susceptibility is BARD1. Although it was suggested that large mutations may contribute substantially to the deleterious variants of BARD1, no systematic study of the large mutations in BARD1 has been performed. To further elucidate the role of large mutations in BARD1, we designed a multiplex ligation-dependent probe amplification (MLPA) assay and performed an analysis of 504 women with a familial breast and/or ovarian cancer and 313 patients with ovarian cancer. The investigation did not reveal any large mutations in the BARD1 gene. Although the analysis was not focused on identification of small mutations, we detected seven deleterious or potentially deleterious point mutations, which contribute substantially to the total number of BARD1 mutations detected so far. In conclusion, although we cannot exclude the presence of large mutations in BARD1, our study indicates that such mutations do not contribute substantially to the risk of breast and/or ovarian cancer. However, it has to be noted that our results may be specific to the Polish population.