Linking the human cytogenetic map with nucleotide sequence: the CCAP clone set

Oligonucleotide PIK3CA/Chromosome 3 Dual in Situ Hybridization Automated Assay with Improved Signals, One-Hour Hybridization, and No Use of Blocking DNA

The PIK3CA gene at chromosome 3q26.32 was found to be amplified in up to 45% of patients with squamous cell carcinoma of the lung. The strong correlation between PIK3CA amplification and increased phosphatidylinositol 3-kinase (PI3K) pathway activities suggested that PIK3CA gene copy number is a potential predictive biomarker for PI3K inhibitors. Currently, all microscopic assessments of PIK3CA and chromosome 3 (CHR3) copy numbers use fluorescence in situ hybridization. PIK3CA probes are derived from bacterial artificial chromosomes whereas CHR3 probes are derived mainly from the plasmid pHS05. These manual fluorescence in situ hybridization assays mandate 12- to 18-hour hybridization and use of blocking DNA from human sources. Moreover, fluorescence in situ hybridization studies provide limited morphologic assessment and suffer from signal decay. We developed an oligonucleotide-based bright-field in situ hybridization assay that overcomes these shortcomings. This assay requires only a 1-hour hybridization with no need for blocking DNA followed by indirect chromogenic detection. Oligonucleotide probes produced discrete and uniform CHR3 stains superior to those from the pHS05 plasmid. This assay achieved successful staining in 100% of the 195 lung squamous cell carcinoma resections and in 94% of the 33 fine-needle aspirates. This robust automated bright-field dual in situ hybridization assay for the simultaneous detection of PIK3CA and CHR3 centromere provides a potential clinical diagnostic method to assess PIK3CA gene abnormality in lung tumors.

Extensive error in the number of genes inferred from draft genome assemblies

Current sequencing methods produce large amounts of data, but genome assemblies based on these data are often woefully incomplete. These incomplete and error-filled assemblies result in many annotation errors, especially in the number of genes present in a genome. In this paper we investigate the magnitude of the problem, both in terms of total gene number and the number of copies of genes in specific families. To do this, we compare multiple draft assemblies against higher-quality versions of the same genomes, using several new assemblies of the chicken genome based on both traditional and next-generation sequencing technologies, as well as published draft assemblies of chimpanzee. We find that upwards of 40% of all gene families are inferred to have the wrong number of genes in draft assemblies, and that these incorrect assemblies both add and subtract genes. Using simulated genome assemblies of Drosophila melanogaster, we find that the major cause of increased gene numbers in draft genomes is the fragmentation of genes onto multiple individual contigs. Finally, we demonstrate the usefulness of RNA-Seq in improving the gene annotation of draft assemblies, largely by connecting genes that have been fragmented in the assembly process.

The initial publication of the genome sequence of many plants, animals, and microbes is often accompanied with great fanfare. However, these genomes are almost always first-drafts, with a lot of missing data, many gaps, and many errors in the published sequences. Compounding this problem, the genes identified in draft genome sequences are also affected by incomplete genome assemblies: the number and exact structure of predicted genes may be incorrect. Here we quantify the extent of such errors, by comparing several draft genomes against completed versions of the same sequences. Surprisingly, we find huge numbers of errors in the number of genes predicted from draft assemblies, with more than half of all genes having the wrong number of copies in the draft genomes examined. Our investigation also reveals the major causes of these errors, and further analyses using additional functional data demonstrate that many of the gene predictions can be corrected. The results presented here suggest that many inferences based on published draft genomes may be erroneous, but offer a way forward for future analyses.

Clone DB: an integrated NCBI resource for clone-associated data

The National Center for Biotechnology Information (NCBI) Clone DB (http://www.ncbi.nlm.nih.gov/clone/) is an integrated resource providing information about and facilitating access to clones, which serve as valuable research reagents in many fields, including genome sequencing and variation analysis. Clone DB represents an expansion and replacement of the former NCBI Clone Registry and has records for genomic and cell-based libraries and clones representing more than 100 different eukaryotic taxa. Records provide details of library construction, associated sequences, map positions and information about resource distribution. Clone DB is indexed in the NCBI Entrez system and can be queried by fields that include organism, clone name, gene name and sequence identifier. Whenever possible, genomic clones are mapped to reference assemblies and their map positions provided in clone records. Clones mapping to specific genomic regions can also be searched for using the NCBI Clone Finder tool, which accepts queries based on sequence coordinates or features such as gene or transcript names. Clone DB makes reports of library, clone and placement data on its FTP site available for download. With Clone DB, users now have available to them a centralized resource that provides them with the tools they will need to make use of these important research reagents.

Prognostic and predictive value of 16p12.1 and 16q22.1 copy number changes in human breast cancer

The present study investigated DNA copy number changes mapping to the p and q arms of chromosome 16 in breast cancer with the goal to determine their potential in identifying breast cancer patients with poor prognosis. We identified the minimal overlapping regions on chromosome 16 that are commonly deleted and amplified in breast tumors. Fluorescence in situ hybridization was used to screen a custom-made breast carcinoma tissue microarray representing all tumor grades, in order to detect DNA copy number changes mapping to 16p12.1 and 16q22.1. We generated 16q/16p ratios for each patient and examined the correlation between DNA copy number alterations and the patients' clinical and pathological parameters. We observed lower q/p ratios in grade I invasive carcinomas, compared with grade III carcinomas, which consistently showed high q/p ratios (P < 0.0091 and 0.0075). In addition, age adjusted for grade analysis revealed that tumors from younger patients (<45 yr) had significantly higher q/p ratios, suggesting that in younger individuals those tumors might be more aggressive (P < 0.0001). The finding that higher q/p ratios occur in younger patients offers a tool to identify high-risk individuals most likely to proceed to high grade.

From cytogenetics to next-generation sequencing technologies: advances in the detection of genome rearrangements in tumorsThis paper is one of a selection of papers published in this Special Issue, entitled CSBMCB — Systems and Chemical Biology, and has undergone the Journal's usual peer review process

Genome rearrangements have long been recognized as hallmarks of human tumors and have been used to diagnose cancer. Techniques used to detect genome rearrangements have evolved from microscopic examinations of chromosomes to the more recent microarray-based approaches. The availability of next-generation sequencing technologies may provide a means for scrutinizing entire cancer genomes and transcriptomes at unparalleled resolution. Here we review the methods that have been used to detect genome rearrangements and discuss the scope and limitations of each approach. We end with a discussion of the potential that next-generation sequencing technologies may offer to the field.