Identification of novel SNPs by next-generation sequencing of the genomic region containing the APC gene in colorectal cancer patients in China

Efficient genome-wide genotyping strategies and data integration in crop plants

Next-generation sequencing (NGS) has revolutionized plant and animal research by providing powerful genotyping methods. This review describes and discusses the advantages, challenges and, most importantly, solutions to facilitate data processing, the handling of missing data, and cross-platform data integration. Next-generation sequencing technologies provide powerful and flexible genotyping methods to plant breeders and researchers. These methods offer a wide range of applications from genome-wide analysis to routine screening with a high level of accuracy and reproducibility. Furthermore, they provide a straightforward workflow to identify, validate, and screen genetic variants in a short time with a low cost. NGS-based genotyping methods include whole-genome re-sequencing, SNP arrays, and reduced representation sequencing, which are widely applied in crops. The main challenges facing breeders and geneticists today is how to choose an appropriate genotyping method and how to integrate genotyping data sets obtained from various sources. Here, we review and discuss the advantages and challenges of several NGS methods for genome-wide genetic marker development and genotyping in crop plants. We also discuss how imputation methods can be used to both fill in missing data in genotypic data sets and to integrate data sets obtained using different genotyping tools. It is our hope that this synthetic view of genotyping methods will help geneticists and breeders to integrate these NGS-based methods in crop plant breeding and research.

Identification of novel SNPs in differentially expressed genes and its association with horn cancer of Bos indicus bullocks by next-generation sequencing

The use of polymorphic markers like SNPs promises to provide comprehensive tool for analysing genome and identifying genomic regions that contribute to cancer phenotype. Horn cancer is the most common cancer among Bos indicus animals. Increased expression of some genes due to polymorphisms increases risk of HC incidence. We successfully amplified 91 SNPs located in 69 genes in 52 samples, each of HC and HN. Equimolar concentration of amplicons from 69 PCR products of each sample was pooled and subjected to sequencing using Ion Torrent PGM. Data obtained were analysed using DNASTAR software package and case control analysis using SAS software. We found SNP present in BPIFA1 gene of B. indicus shows association with event of HC which reflects its potential to be a genetic marker. Bioinformatic analysis to detect structural and functional impact nsSNP of BPIFA1 added another layer of confirmation to our result. We successfully identified SNP associated with HC as well as demonstrated efficient approach for limited number of SNP discovery and validation in targeted genomics regions in large number of samples combining PCR amplification and Ion Torrent PGM sequencing which suits small-scale laboratories with limited budget.

Next-generation sequencing of colorectal cancers in chinese: identification of a recurrent frame-shift and gain-of-function Indel mutation in the TFDP1 gene

Abstract Re-sequencing of target genes is a highly effective approach for identifying mutations in cancers. Mutations, including indels (insertions, deletions, and the combination of the two), play important roles in carcinogenesis. Combining genomic DNA capture using high-density oligonucleotide microarrays (NimbleGen, Inc.) with next-generation high-throughput sequencing, we identified approximately 1600 indels for colorectal cancers in the Chinese population. Among them, 5 indels were localized to exonic regions of genes, including the TFDP1 (transcription factor Dp-1) gene. TFDP1 is an important transcription factor that coordinates with E2F proteins, thereby promoting transcription of E2F target genes and regulating the cell cycle and differentiation. We report here the identification of a recurrent frame-shift indel mutation (named indel84) in the TFDP1 gene in colorectal cancers by next-generation sequencing. We found in a validation set that TFDP1 indel84 is present in 70% of colorectal cancer (CRC) tissues. Wild-type TFDP1 encodes a protein of 410 amino acids with a potential DNA binding site at its N-terminal followed by several functional protein domains. The TFDP1 indel cDNA would generate an alternative TFDP1 protein missing the first 120 amino acids and potentially affecting the DNA binding domain. We further demonstrated that the TFDP1 indel84 mutation generated a gain-of-function phenotype by increasing cell proliferation, migration, and invasion of CRC cells. Our study identified a key molecular event for CRC that might have great diagnostic and therapeutic potentials.

Next-generation sequencing applied to molecular diagnostics

Next-generation sequencing technologies have begun to revolutionize the field of cancer genetics through rapid and accurate assessment of a patient's DNA makeup with minimal cost. These technologies have already led to the realization of the inter- and intra-tumor genetic heterogeneity and the identification of novel mutations and chimeric genes, however, several challenges lie ahead. Given the low number of recurrent somatic genetic aberrations in common types of cancer, the identification of 'driver' genetic aberrations has proven challenging. Furthermore, implementation of next-generation sequencing and/or some of its derivatives into routine practice as diagnostic tests will require in-depth understanding of the pitfalls of these technologies and a great degree of bioinformatic expertise. This article focuses on the contribution of next-generation sequencing technologies to diagnosis and cancer prognostication and prediction.

Genome-wide genetic marker discovery and genotyping using next-generation sequencing

The advent of next-generation sequencing (NGS) has revolutionized genomic and transcriptomic approaches to biology. These new sequencing tools are also valuable for the discovery, validation and assessment of genetic markers in populations. Here we review and discuss best practices for several NGS methods for genome-wide genetic marker development and genotyping that use restriction enzyme digestion of target genomes to reduce the complexity of the target. These new methods -- which include reduced-representation sequencing using reduced-representation libraries (RRLs) or complexity reduction of polymorphic sequences (CRoPS), restriction-site-associated DNA sequencing (RAD-seq) and low coverage genotyping -- are applicable to both model organisms with high-quality reference genome sequences and, excitingly, to non-model species with no existing genomic data.