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Whole genome sequence analysis of BT-474 using complete Genomics' standard and long fragment read technologies.

ABSTRACT: BACKGROUND:The cell line BT-474 is a popular cell line for studying the biology of cancer and developing novel drugs. However, there is no complete, published genome sequence for this highly utilized scientific resource. In this study we sought to provide a comprehensive and useful data set for the scientific community by generating a whole genome sequence for BT-474. FINDINGS:Five ?g of genomic DNA, isolated from an early passage of the BT-474 cell line, was used to generate a whole genome sequence (114X coverage) using Complete Genomics' standard sequencing process. To provide additional variant phasing and structural variation data we also processed and analyzed two separate libraries of 5 and 6 individual cells to depths of 99X and 87X, respectively, using Complete Genomics' Long Fragment Read (LFR) technology. CONCLUSIONS:BT-474 is a highly aneuploid cell line with an extremely complex genome sequence. This ~300X total coverage genome sequence provides a more complete understanding of this highly utilized cell line at the genomic level.

SUBMITTER: Ciotlos S

PROVIDER: S-EPMC4748558 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Whole genome sequence analysis of BT-474 using complete Genomics' standard and long fragment read technologies.

Ciotlos Serban S Mao Qing Q Zhang Rebecca Yu RY Li Zhenyu Z Chin Robert R Gulbahce Natali N Liu Sophie Jia SJ Drmanac Radoje R Peters Brock A BA

GigaScience 20160209

<h4>Background</h4>The cell line BT-474 is a popular cell line for studying the biology of cancer and developing novel drugs. However, there is no complete, published genome sequence for this highly utilized scientific resource. In this study we sought to provide a comprehensive and useful data set for the scientific community by generating a whole genome sequence for BT-474.<h4>Findings</h4>Five μg of genomic DNA, isolated from an early passage of the BT-474 cell line, was used to generate a wh ...[more]

PMID: 26865974

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Project description:BackgroundThe utility of long-read genome sequencing platforms has been shown in many fields including whole genome assembly, metagenomics, and amplicon sequencing. Less clear is the applicability of long reads to reference-guided human genomics, which is the foundation of genomic medicine. Here, we benchmark available platform-agnostic alignment tools on datasets from nanopore and single-molecule real-time platforms to understand their suitability in producing a genome representation.ResultsFor this study, we leveraged publicly-available data from sample NA12878 generated on Oxford Nanopore and sample NA24385 on Pacific Biosciences platforms. We employed state of the art sequence alignment tools including GraphMap2, long-read aligner (LRA), Minimap2, CoNvex Gap-cost alignMents for Long Reads (NGMLR), and Winnowmap2. Minimap2 and Winnowmap2 were computationally lightweight enough for use at scale, while GraphMap2 was not. NGMLR took a long time and required many resources, but produced alignments each time. LRA was fast, but only worked on Pacific Biosciences data. Each tool widely disagreed on which reads to leave unaligned, affecting the end genome coverage and the number of discoverable breakpoints. No alignment tool independently resolved all large structural variants (1,001-100,000 base pairs) present in the Database of Genome Variants (DGV) for sample NA12878 or the truthset for NA24385.ConclusionsThese results suggest a combined approach is needed for LRS alignments for human genomics. Specifically, leveraging alignments from three tools will be more effective in generating a complete picture of genomic variability. It should be best practice to use an analysis pipeline that generates alignments with both Minimap2 and Winnowmap2 as they are lightweight and yield different views of the genome. Depending on the question at hand, the data available, and the time constraints, NGMLR and LRA are good options for a third tool. If computational resources and time are not a factor for a given case or experiment, NGMLR will provide another view, and another chance to resolve a case. LRA, while fast, did not work on the nanopore data for our cluster, but PacBio results were promising in that those computations completed faster than Minimap2. Due to its significant burden on computational resources and slow run time, Graphmap2 is not an ideal tool for exploration of a whole human genome generated on a long-read sequencing platform.

Project description:BackgroundWhile mutations in the PIK3CA gene play important roles in human breast carcinogenesis, PIK3R1 gene alterations are recognized as actionable mutations for clinical cancer treatment. We aimed to elucidate the role of PIK3R1 in cell proliferation on breast carcinoma and to correlate the PIK3R1 expression with patients' outcome using human tumor tissue arrays.MethodsUsing human BT-474 (estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)-high) breast carcinoma cell line as in vitro model, the role of PIK3R1 in cell proliferation was elucidated by knock-down of the PIK3R1 gene (ΔPIK3R1) in this cell line. Between January 2000 to December 2015, the records of a cohort of 440 patients in our hospital were retrospectively reviewed, including patients' survival. The correlations between PIK3R1 expression and patient prognosis, such as overall survival (OS) and disease-free survival (DFS), were elucidated by human breast cancer tumor tissue array immunostaining.ResultsAfter the PIK3R1 gene was silenced in the BT-474 line, there was an increased cell number and a decrease in the G0G1-fraction, and increased S-fraction and the S+G2M-fraction for the ΔPIK3R1-BT-474 cell line, as compared to their cell wild type (WT) line. Western blot analysis showed that decreased PIK3R1 protein levels were accompanied by an increase of the p-AKT and p-mTOR proteins in the ΔPIK3R1-BT-474 cell line, compared to the equivalent WT line. Using a human tumor tissue array, patients with high-expressed PIK3R1 protein had better outcomes in terms of DFS and OS, compared to those with low-expressed PIK3R1 protein, when breast cancer was at an early stage (stage I/II), but not across all stages of breast cancer in human patients.ConclusionsWe concluded that downregulated PIK3R1 in BT-474 cells resulted in an increased cell growth and upregulated AKT-mTOR signaling. Clinically, the high-expressed PIK3R1 protein in tumors correlates positively with patients' outcome in stage I and II breast cancer.

Project description:BackgroundAccumulating evidence suggests that the androgen receptor (AR) and its endogenous ligands influence disease progression in breast cancer (BCa). However, AR-mediated changes in BCa differ among the various BCa subtypes according to their hormone receptor profile [i.e., presence/absence of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2, (HER2)]. Thus, we explored the androgen-regulated transcriptomic changes in the ER+PR+HER2+ BCa cell line, BT-474, and compared them with PR-mediated changes.MethodsWe performed RNA sequencing analysis in treated BT-474 cells with dihydrotestosterone (DHT) and progesterone. Validation of the top ten differentially androgen-regulated genes and a number of other genes found in enriched signaling pathways was performed by qRT-PCR in BT-474 and other BCa cell lines. In addition, a parallel reaction monitoring targeted proteomic approach was developed to verify selected transcripts at the protein level.ResultsIn total 19,450 transcripts were detected, of which 224 were differentially regulated after DHT treatment. The increased expression of two well-known androgen-regulated genes, KLK2 (p < 0.05) and KLK3 (p < 0.001), confirmed the successful androgen stimulation in BT-474 cells. The transcription factor, ZBTB16, was the most highly upregulated gene, with ~ 1000-fold change (p < 0.001). Pathway enrichment analysis revealed downregulation of the DNA replication processes (p < 0.05) and upregulation of the androgen signaling and fatty acid metabolism pathways (p < 0.05). Changes related to progesterone treatment showed opposite effects in gene expression than DHT treatment. Similar expression profiles were observed among other BCa cell lines expressing high levels of AR (ZR75.1 and MBA-MB-453). The parallel reaction monitoring targeted proteomic analysis further confirmed that altered protein expression (KLK3, ALOX15B) in the supernatant and cell lysate of DHT-treated BT-474 cells, compared to control cells.DiscussionOur findings suggest that AR modulates the metabolism of BT-474 cells by affecting the expression of a large number of genes and proteins. Based on further pathway analysis, we suggest that androgen receptor acts as a tumor suppressor in the BT-474 cells.

Dataset Information

Whole genome sequence analysis of BT-474 using complete Genomics' standard and long fragment read technologies.

Publications

Whole genome sequence analysis of BT-474 using complete Genomics' standard and long fragment read technologies.

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