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      APC Mutations Are Not Confined to Hotspot Regions in Early-Onset Colorectal Cancer

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          Abstract

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          Mutation of the APC gene is a common early event in colorectal cancer, however lower rates have been reported in younger cohorts of colorectal cancer patients. In sporadic cancer, mutations are typically clustered around a mutation cluster region, a narrowly defined hotspot within the APC gene. In this study we used a sequencing strategy aimed at identifying mutations more widely throughout the APC gene in patients aged 50 years or under. We found high rates of APC mutation in our young cohort that were similar to rates seen in older patients but the mutations we found were spread throughout the gene in a pattern more similar to that seen in inherited rather than sporadic mutations. Our study has implications both for the sequencing of the APC gene in early-onset colorectal cancer and for the etiology of this disease.

          Abstract

          While overall colorectal cancer (CRC) cases have been declining worldwide there has been an increase in the incidence of the disease among patients under 50 years of age. Mutation of the APC gene is a common early event in CRC but is reported at lower rates in early-onset colorectal cancer (EOCRC) than in older patients. Here we investigate the APC mutation status of a cohort of EOCRC patients in New Zealand using a novel sequencing approach targeting regions of the gene encompassing the vast majority of known APC mutations. Using this strategy we find a higher rate (72%) of APC mutation than previously reported in EOCRC with mutations being spread throughout the gene rather than clustered in hotspots as seen with sporadic mutations in older patients. The rate of mutations falling within hotspots was similar to those previously seen in EOCRC and as such our study has implications for sequencing strategies for EOCRC patients. Overall there were low rates of both loss of heterozygosity and microsatellite instability whereas a relatively high rate (40%) of APC promoter methylation was found, possibly reflecting increasing exposure of young people to pro-oncogenic lifestyle factors.

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          Most cited references67

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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              The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

              Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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                Author and article information

                Journal
                Cancers (Basel)
                Cancers (Basel)
                cancers
                Cancers
                MDPI
                2072-6694
                18 December 2020
                December 2020
                : 12
                : 12
                : 3829
                Affiliations
                [1 ]Department of Surgery, University of Otago Christchurch, Christchurch 8011, New Zealand; frank.frizelle@ 123456cdhb.health.nz (F.A.F.); jacqui.keenan@ 123456otago.ac.nz (J.I.K.)
                [2 ]Mackenzie Cancer Research Group, Department of Pathology and Biomedical Science, University of Otago Christchurch, Christchurch 8011, New Zealand; christopher.hakkaart@ 123456otago.ac.nz
                [3 ]Department of Biochemistry, University of Otago, Dunedin 9054, New Zealand; robert.day@ 123456otago.ac.nz
                [4 ]Cancer Society Tissue Bank, University of Otago Christchurch, Christchurch 8011, New Zealand; helen.morrin@ 123456otago.ac.nz
                Author notes
                Author information
                https://orcid.org/0000-0002-0857-1815
                https://orcid.org/0000-0001-5007-2684
                https://orcid.org/0000-0002-0739-4802
                Article
                cancers-12-03829
                10.3390/cancers12123829
                7766084
                33352971
                cf504204-f863-419d-a78b-8bcd8f19069f
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 11 November 2020
                : 15 December 2020
                Categories
                Article

                early-onset,colorectal cancer,apc,sequencing,dna methylation,diet

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