Minimal Number Of Probes Research Articles

Abstract 2755: Germline copy number variations in melanoma families with/without CDKN2A/CDK4 mutations

Abstract Cutaneous malignant melanoma (CMM) is an etiologically heterogeneous disease with genetic, host, environmental factors, and their interactions contributing to its development. CDKN2A and CDK4 are the two established major susceptibility genes for melanoma identified so far. Recent evidence suggests that copy number variations (CNVs) may contribute to disease susceptibility in several inherited diseases including cancer. The goals of this study were 1) to assess whether the frequency of CNVs varied by CMM or CDKN2A/CDK4 mutation status; and 2) to identify rare CNVs that were related to melanoma predisposition in these high-risk families. We used genome-wide tiling CGH arrays (Nimblegen 720K exon-focused) to investigate characteristics of CNVs in 174 CMM cases, 44 high-risk unaffected family members (with dysplastic nevi/large number of moles or germline CDKN2A mutations), and 48 unrelated spouses from 50 American melanoma-prone families (21 CDKN2A+, 2 CDK4+, 27 mutation negative). We used the Nexus Copy Number™ built-in FASST2 algorithm to identify significant CNVs (significant threshold = 0.000001; minimal number of probes per segment = 5; log2 ratio>0.3 for gains and -0.3 for losses). We found that the median number of total CNVs, or gains or losses separately, did not show significant differences in CMM cases, high-risk unaffected family members, and unrelated controls. Among CMM cases, CNV frequencies were not significantly associated with germline CDKN2A/CDK4 mutation status, age at melanoma diagnosis, or number of melanomas. Similar results were obtained when number of genes and lengths of DNA segments affected by CNVs were analyzed. Restriction to large CNVs (>10 kb or >100 kb) or rare CNVs (not reported in the Toronto CNV database) did not change results significantly. On the other hand, we identified several rare large CNVs (>10 kb, not reported in unrelated controls) that either involved known melanoma genes or co-segregated with melanoma (observed in multiple CMM cases) within families. These included a 1.3Mb deletion in PARP1 in a single CMM case, a 10 kb deletion in CDKN2A in 4 of 5 CMM cases and two obligate gene carriers in a large family that was negative for CDKN2A mutations by sequencing, a 175 kb deletion in LINGO2 in 2 of 3 CMM cases in one family, a 10 kb deletion in 8q24 in 3 of 4 CMM cases in one family, a 110 kb deletion in 2q22.1 in all three cases in a family, and a 57 kb duplication in 4q32.2 in all five cases in a CDKN2A mutation positive family. The role of these CNVs, particularly those involving genes that have unknown function related to CMM development, in CMM susceptibility remain to be investigated. Citation Format: Xiaohong (Rose) Yang, Jianxin Shi, Hunter Bennett, Laura Burke, Casey Dagnall, Laurie Burdette, Belynda Hicks, Margaret Tucker, Alisa Goldstein. Germline copy number variations in melanoma families with/without CDKN2A/CDK4 mutations. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2755. doi:10.1158/1538-7445.AM2015-2755

Design of shortest double-stranded DNA sequences covering all k-mers with applications to protein-binding microarrays and synthetic enhancers

Motivation: Novel technologies can generate large sets of short double-stranded DNA sequences that can be used to measure their regulatory effects. Microarrays can measure in vitro the binding intensity of a protein to thousands of probes. Synthetic enhancer sequences inserted into an organism’s genome allow us to measure in vivo the effect of such sequences on the phenotype. In both applications, by using sequence probes that cover all k-mers, a comprehensive picture of the effect of all possible short sequences on gene regulation is obtained. The value of k that can be used in practice is, however, severely limited by cost and space considerations. A key challenge is, therefore, to cover all k-mers with a minimal number of probes. The standard way to do this uses the de Bruijn sequence of length . However, as probes are double stranded, when a k-mer is included in a probe, its reverse complement k-mer is accounted for as well.Results: Here, we show how to efficiently create a shortest possible sequence with the property that it contains each k-mer or its reverse complement, but not necessarily both. The length of the resulting sequence approaches half that of the de Bruijn sequence as k increases resulting in a more efficient array, which allows covering more longer sequences; alternatively, additional sequences with redundant k-mers of interest can be added.Availability: The software is freely available from our website http://acgt.cs.tau.ac.il/shortcake/.Contact: rshamir@tau.ac.il

Abstract 2553: Characterization of rare germline variants in somatically mutated melanoma genes in melanoma-prone families.

Abstract CDKN2A and CDK4 are the two major susceptibility genes for melanoma identified so far. However, these two genes only account for melanoma susceptibility in a small proportion of melanoma-prone families, suggesting the existence of other susceptibility genes. In addition, melanoma is among the tumors with the highest mutation rate and a large number of mutated genes have been identified that affect multiple key biological pathways. The goal of this study is to examine whether rare germline sequence variants and/or copy number variations (CNVs) in these genes may influence melanoma risk in melanoma-prone families without known CDKN2A/CDK4 mutations. Methods: We conducted exome sequencing in blood-derived DNA in 75 melanoma cases from 23 American melanoma families with ≥3 affected members. We evaluated rare non-synonymous variants, defined as allele frequency less than 0.1% reported in public databases (dbSNP, 1000 Genomes, or NHLBI's Exome Variant Server), in 37 genes (including BRAF, NRAS, KIT,PTEN, CDKN2A, GRIN2A, etc.) that are frequently mutated in melanoma. We also screened CNVs in these genes using data from the Nimblegen 3x720k exon-focused CGH tiling arrays, in which blood-derived DNA from 79 melanoma cases and 25 spouses were analyzed in the same mutation-negative families. We used the Nexus Copy Number™ built-in FASST2 algorithm to identify significant CNVs (significant threshold=0.000001; minimal number of probes per segment=5; log2 ratio>0.3 for gains and -0.3 for losses). Results: We identified 10 rare variants in 10 genes that showed partial/complete co-segregation with disease and were absent in our internal controls (N∼400). Four of these variants occurred in all cases within their respective families and 3 of them were novel. We did not identify any disease-related CNVs in these genes except for a deletion in exon 1β of CDKN2A/ p14ARF in 6 out of 7 melanoma cases in one big family. Our findings suggest that rare variants in somatically mutated genes may confer susceptibility to melanoma risk in a subset of families. However, these variants need to be validated, checked for functional relevance, and evaluated in a large number of cases and controls to determine their role in disease susceptibility. Citation Format: Xiaohong (Rose) Yang, Laura Burke, Kevin Jacobs, Michael Cullen, Joseph Boland, Laurie Burdett, Michael Malasky, Melissa Rotunno, Meredith Yeager, Stephen Chanock, Margaret Tucker, Alisa Goldstein. Characterization of rare germline variants in somatically mutated melanoma genes in melanoma-prone families. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2553. doi:10.1158/1538-7445.AM2013-2553

Selection based heuristics for the non-unique oligonucleotide probe selection problem in microarray design

In order to accurately measure the gene expression levels in microarray experiments, it is crucial to design unique, highly specific and highly sensitive oligonucleotide probes for the identification of biological agents such as genes in a sample. Unique probes are difficult to obtain for closely related genes such as the known strains of HIV genes. The non-unique probe selection problem is to select a probe set that is able to uniquely identify targets in a biological sample, while containing a minimal number of probes. This is an NP-hard problem. We introduce original deterministic greedy heuristics for finding near minimal non-unique probe sets. The heuristics, guided by selection functions defined over a probe set, decide at each moment which probes are the best to be included in, or excluded from, a candidate solution. Our methods substantially outperform the only two known greedy heuristics in the literature for the non-unique probe selection problem. We also obtained results that are very close to, and sometimes better than, those of the current state-of-the-art methods for the non-unique probe selection problem, namely integer linear programming and optimal cutting-plane approaches.

Efficient oligonucleotide probe selection for pan-genomic tiling arrays

BackgroundArray comparative genomic hybridization is a fast and cost-effective method for detecting, genotyping, and comparing the genomic sequence of unknown bacterial isolates. This method, as with all microarray applications, requires adequate coverage of probes targeting the regions of interest. An unbiased tiling of probes across the entire length of the genome is the most flexible design approach. However, such a whole-genome tiling requires that the genome sequence is known in advance. For the accurate analysis of uncharacterized bacteria, an array must query a fully representative set of sequences from the species' pan-genome. Prior microarrays have included only a single strain per array or the conserved sequences of gene families. These arrays omit potentially important genes and sequence variants from the pan-genome.ResultsThis paper presents a new probe selection algorithm (PanArray) that can tile multiple whole genomes using a minimal number of probes. Unlike arrays built on clustered gene families, PanArray uses an unbiased, probe-centric approach that does not rely on annotations, gene clustering, or multi-alignments. Instead, probes are evenly tiled across all sequences of the pan-genome at a consistent level of coverage. To minimize the required number of probes, probes conserved across multiple strains in the pan-genome are selected first, and additional probes are used only where necessary to span polymorphic regions of the genome. The viability of the algorithm is demonstrated by array designs for seven different bacterial pan-genomes and, in particular, the design of a 385,000 probe array that fully tiles the genomes of 20 different Listeria monocytogenes strains with overlapping probes at greater than twofold coverage.ConclusionPanArray is an oligonucleotide probe selection algorithm for tiling multiple genome sequences using a minimal number of probes. It is capable of fully tiling all genomes of a species on a single microarray chip. These unique pan-genome tiling arrays provide maximum flexibility for the analysis of both known and uncharacterized strains.

An Optimal Cutting-Plane Algorithm for Solving the Non-Unique Probe Selection Problem

The non-unique probe selection problem consists of selecting oligonucleotide probes for use in hybridization experiments in which target viruses or bacteria are to be identified in biological samples. The presence or absence of these targets is determined by observing whether selected probes bind to their corresponding sequences. The goal is to select a probe set that is able to uniquely identify targets while containing a minimal number of probes. This paper contributes the first exact method for finding optimal solutions to the non-unique probe selection problem within practical computational limits, without the a priori elimination of candidate probes. Previously published methods have employed heuristics to find approximate solutions that are not probably optimal, and as a result, no knowledge has been obtained regarding the quality of those solutions relative to optimality. We demonstrate that our approach consistently finds an optimal solution to the non-unique probe selection problem within 10 min, and is capable of reducing the number of probes required over state-of-the-art heuristic techniques by as much as 20%.

A New Approach to the Non-unique Probe Selection Problem

Identification of biological agents in a sample is a relevant problem in medicine. A model to this problem consists of selecting optimal oligonucleotide probe sets for use in hybridization experiments in which target viruses or bacteria are to be identified in biological samples. In such an experiment the presence or absence of these targets is determined by observing whether selected probes bind to their corresponding sequences. The problem is to select a probe set that is able to uniquely identify targets while containing a minimal number of probes. In this paper we describe a heuristic algorithm that produced feasible solution sets that for large, real data sets contain significantly fewer probes than those obtained using other methods. A description of the problem, our approach, and the results are presented. We developed a C++ program and a GUI (Graphical User Interface) to run real and simulated instances of the problem.