Transposon mutagenesis identifies candidate genes that cooperate with loss of transforming growth factor-beta signaling in mouse intestinal neoplasms.

Colorectal cancer (CRC) results from the accumulation of gene mutations and epigenetic alterations in colon epithelial cells, which promotes CRC formation through deregulating signaling pathways. One of the most commonly deregulated signaling pathways in CRC is the transforming growth factor ß (TGF-ß) pathway. Importantly, the effects of TGF-ß signaling inactivation in CRC are modified by concurrent mutations in the tumor cell, and these concurrent mutations determine the ultimate biological effects of impaired TGF-ß signaling in the tumor. However, many of the mutations that cooperate with the deregulated TGF-ß signaling pathway in CRC remain unknown. Therefore, we sought to identify candidate driver genes that promote the formation of CRC in the setting of TGF-ß signaling inactivation. We performed a forward genetic screen in mice carrying conditionally inactivated alleles of the TGF-ß receptor, type II (Tgfbr2) using Sleeping Beauty (SB) transposon mediated mutagenesis. We used TAPDANCE and Gene-centric statistical methods to identify common insertion sites (CIS) and, thus, candidate tumor suppressor genes and oncogenes within the tumor genome. CIS analysis of multiple neoplasms from these mice identified many candidate Tgfbr2 cooperating genes and the Wnt/ß-catenin, Hippo and MAPK pathways as the most commonly affected pathways. Importantly, the majority of candidate genes were also found to be mutated in human CRC. The SB transposon system provides an unbiased method to identify Tgfbr2 cooperating genes in mouse CRC that are functionally relevant and that may provide further insight into the pathogenesis of human CRC.

Sleeping Beauty mutagenesis reveals cooperating mutations and pathways in pancreatic adenocarcinoma.

Pancreatic cancer is one of the most deadly cancers affecting the Western world. Because the disease is highly metastatic and difficult to diagnosis until late stages, the 5-y survival rate is around 5%. The identification of molecular cancer drivers is critical for furthering our understanding of the disease and development of improved diagnostic tools and therapeutics. We have conducted a mutagenic screen using Sleeping Beauty (SB) in mice to identify new candidate cancer genes in pancreatic cancer. By combining SB with an oncogenic Kras allele, we observed highly metastatic pancreatic adenocarcinomas. Using two independent statistical methods to identify loci commonly mutated by SB in these tumors, we identified 681 loci that comprise 543 candidate cancer genes (CCGs); 75 of these CCGs, including Mll3 and Ptk2, have known mutations in human pancreatic cancer. We identified point mutations in human pancreatic patient samples for another 11 CCGs, including Acvr2a and Map2k4. Importantly, 10% of the CCGs are involved in chromatin remodeling, including Arid4b, Kdm6a, and Nsd3, and all SB tumors have at least one mutated gene involved in this process; 20 CCGs, including Ctnnd1, Fbxo11, and Vgll4, are also significantly associated with poor patient survival. SB mutagenesis provides a rich resource of mutations in potential cancer drivers for cross-comparative analyses with ongoing sequencing efforts in human pancreatic adenocarcinoma.

Sequencing methods and datasets to improve functional interpretation of sleeping beauty mutagenesis screens.

BACKGROUND: Animal models of cancer are useful to generate complementary datasets for comparison to human tumor data. Insertional mutagenesis screens, such as those utilizing the Sleeping Beauty (SB) transposon system, provide a model that recapitulates the spontaneous development and progression of human disease. This approach has been widely used to model a variety of cancers in mice. Comprehensive mutation profiles are generated for individual tumors through amplification of transposon insertion sites followed by high-throughput sequencing. Subsequent statistical analyses identify common insertion sites (CISs), which are predicted to be functionally involved in tumorigenesis. Current methods utilized for SB insertion site analysis have some significant limitations. For one, they do not account for transposon footprints - a class of mutation generated following transposon remobilization. Existing methods also discard quantitative sequence data due to uncertainty regarding the extent to which it accurately reflects mutation abundance within a heterogeneous tumor. Additionally, computational analyses generally assume that all potential insertion sites have an equal probability of being detected under non-selective conditions, an assumption without sufficient relevant data. The goal of our study was to address these potential confounding factors in order to enhance functional interpretation of insertion site data from tumors. RESULTS: We describe here a novel method to detect footprints generated by transposon remobilization, which revealed minimal evidence of positive selection in tumors. We also present extensive characterization data demonstrating an ability to reproducibly assign semi-quantitative information to individual insertion sites within a tumor sample. Finally, we identify apparent biases for detection of inserted transposons in several genomic regions that may lead to the identification of false positive CISs. CONCLUSION: The information we provide can be used to refine analyses of data from insertional mutagenesis screens, improving functional interpretation of results and facilitating the identification of genes important in cancer development and progression.

Generation of a Commercial-Scale Founder Population of Porcine Reproductive and Respiratory Syndrome Virus Resistant Pigs Using CRISPR-Cas.

Disease resistance genes in livestock provide health benefits to animals and opportunities for farmers to meet the growing demand for affordable, high-quality protein. Previously, researchers used gene editing to modify the porcine CD163 gene and demonstrated resistance to a harmful virus that causes porcine reproductive and respiratory syndrome (PRRS). To maximize potential benefits, this disease resistance trait needs to be present in commercially relevant breeding populations for multiplication and distribution of pigs. Toward this goal, a first-of-its-kind, scaled gene editing program was established to introduce a single modified CD163 allele into four genetically diverse, elite porcine lines. This effort produced healthy pigs that resisted PRRS virus infection as determined by macrophage and animal challenges. This founder population will be used for additional disease and trait testing, multiplication, and commercial distribution upon regulatory approval. Applying CRISPR-Cas to eliminate a viral disease represents a major step toward improving animal health.

Cell of origin strongly influences genetic selection in a mouse model of T-ALL.

Identifying the normal cell from which a tumor originates is crucial to understanding the etiology of that cancer. However, retrospective identification of the cell of origin in cancer is challenging because of the accumulation of genetic and epigenetic changes in tumor cells. The biologic state of the cell of origin likely influences the genetic events that drive transformation. We directly tested this hypothesis by performing a Sleeping Beauty transposon mutagenesis screen in which common insertion sites were identified in tumors that were produced by mutagenesis of cells at varying time points throughout the T lineage. Mutation and gene expression data derived from these tumors were then compared with data obtained from a panel of 84 human T-cell acute lymphoblastic leukemia samples, including copy number alterations and gene expression profiles. This revealed that altering the cell of origin produces tumors that model distinct subtypes of human T-cell acute lymphoblastic leukemia, suggesting that even subtle changes in the cell of origin dramatically affect genetic selection in tumors. These findings have broad implications for the genetic analysis of human cancers as well as the production of mouse models of cancer.

A Hyperactive Transposase Promotes Persistent Gene Transfer of a piggyBac DNA Transposon.

Nonviral vector systems are used increasingly in gene targeting and gene transfer applications. The piggyBac transposon represents an alternative integrating vector for in vivo gene transfer. We hypothesized that this system could achieve persistent gene transfer to the liver when administered systemically. We report that a novel hyperactive transposase generated higher transposition efficiency than a codon-optimized transposase in a human liver cell line. Hyperactive transposase-mediated reporter gene expression persisted at levels twice that of codon-optimized transposase in the livers of mice for the 6-month study. Of note, expression persisted in mice following partial hepatectomy, consistent with expression from an integrated transgene. We also used the hyperactive transposase to deliver the human α(1)-antitrypsin gene and achieved stable expression in serum. To determine the integration pattern of insertions, we performed large-scale mapping in human cells and recovered 60,685 unique hyperactive transposase-mediated insertions. We found that a hyperactive piggyBac transposase conferred an altered pattern of integration from that of insect piggyBac transposase, with a decreased frequency of integration near transcription start sites than previously reported. Our results support that the piggyBac transposon combined with the hyperactive transposase is an efficient integrating vector system for in vitro and in vivo applications.Molecular Therapy - Nucleic Acids (2012) 1, e50; doi:10.1038/mtna.2012.12; published online 16 October 2012.

Novel molecular and computational methods improve the accuracy of insertion site analysis in Sleeping Beauty-induced tumors.

The recent development of the Sleeping Beauty (SB) system has led to the development of novel mouse models of cancer. Unlike spontaneous models, SB causes cancer through the action of mutagenic transposons that are mobilized in the genomes of somatic cells to induce mutations in cancer genes. While previous methods have successfully identified many transposon-tagged mutations in SB-induced tumors, limitations in DNA sequencing technology have prevented a comprehensive analysis of large tumor cohorts. Here we describe a novel method for producing genetic profiles of SB-induced tumors using Illumina sequencing. This method has dramatically increased the number of transposon-induced mutations identified in each tumor sample to reveal a level of genetic complexity much greater than previously appreciated. In addition, Illumina sequencing has allowed us to more precisely determine the depth of sequencing required to obtain a reproducible signature of transposon-induced mutations within tumor samples. The use of Illumina sequencing to characterize SB-induced tumors should significantly reduce sampling error that undoubtedly occurs using previous sequencing methods. As a consequence, the improved accuracy and precision provided by this method will allow candidate cancer genes to be identified with greater confidence. Overall, this method will facilitate ongoing efforts to decipher the genetic complexity of the human cancer genome by providing more accurate comparative information from Sleeping Beauty models of cancer.