Single Primer Enrichment Technology Research Articles

The Jan Sjödin faba bean mutant collection: morphological and molecular characterization.

Plant mutagenesis creates novel alleles, thereby increasing genetic and phenotypic diversity. The availability of the faba bean (Vicia faba L.) reference genome and a growing set of additional genomic resources has increased the scientific and practical value of mutant collections. We aimed to genotype and morphologically phenotype a historical faba bean mutant collection developed and characterized by Jan Sjödin (1934-2023) over half a century ago in order to increase its value to researchers. The collection was genotyped using high-throughput single-primer enrichment technology (SPET) assays. We used 11,073 informative single nucleotide polymorphism (SNP) markers spanning the faba bean genome to genotype 52 mutant lines along with the background line, cv. Primus. A range of flower, seed, leaf, and stipule mutations were observed. The analysis of population structure revealed a shallow structure with no major subpopulations. Principal component and cluster analyses revealed, to a minor extent, that the mutants clustered by their phenotype. The mutants' phenotypic variation and shallow structure indicate that the Sjödin faba bean collection has the potential to play a significant role in faba bean breeding and in genetic and functional studies.

Molecular genetic diversity and linkage disequilibrium structure of the Egyptian faba bean using Single Primer Enrichment Technology (SPET)

Faba bean is an important legume crop. The genetic diversity among faba bean genotypes is very important for the genetic improvement of target traits. A set of 128 fab bean genotypes that are originally from Egypt were used in this study to investigate the genetic diversity and population structure. The 128 genotypes were genotyped using the Single Primer Enrichment Technology (SPET) by which a set of 6759 SNP markers were generated after filtration. The SNP markers were distributed on all chromosomes with a range extending from 822 (Chr. 6) to 1872 (Chr.1). The SNP markers had wide ranges of polymorphic information content (PIC), gene diversity (GD), and minor allele frequency. The analysis of population structure divided the Egyptian faba bean population into five subpopulations. Considerable genetic distance was found among all genotypes, ranging from 0.1 to 0.4. The highly divergent genotype was highlighted in this study and the genetic distance among genotypes ranged from 0.1 and 0.6. Moreover, the structure of linkage disequilibrium was studied, and the analysis revealed a low level of LD in the Egyptian faba bean population. A slow LD decay at the genomic and chromosomal levels was observed. Interestingly, the distribution of haplotype blocks was presented in each chromosome and the number of haplotype block ranged from 65 (Chr. 4) to 156 (Chr. 1). Migration and genetic drift are the main reasons for the low LD in the Egyptian faba bean population. The results of this study shed light on the possibility of the genetic improvement of faba bean crop in Egypt and conducting genetic association analyses to identify candidate genes associated with target traits (e.g. protein content, grain yield, etc.) in this panel.

QTL analysis on a lemon population provides novel insights on the genetic regulation of the tolerance to the two-spotted spider mite attack

BackgroundAmong the Citrus species, lemon (Citrus limon Burm f.) is one of the most affected by the two-spotted spider mite (Tetranychus urticae Koch). Moreover, chemical control is hampered by the mite’s ability to develop genetic resistance against acaricides. In this context, the identification of the genetic basis of the host resistance could represent a sustainable strategy for spider mite control. In the present study, a marker-trait association analysis was performed on a lemon population employing an association mapping approach. An inter-specific full-sib population composed of 109 accessions was phenotyped through a detached-leaf assays performed in modified Huffaker cells. Those individuals, complemented with two inter-specific segregating populations, were genotyped using a target-sequencing approach called SPET (Single Primer Enrichment Technology), the resulting SNPs were employed for the generation of an integrated genetic map.ResultsThe percentage of damaged area in the full-sib population showed a quantitative distribution with values ranging from 0.36 to 9.67%. A total of 47,298 SNPs were selected for an association mapping study and a significant marker linked with resistance to spider mite was detected on linkage group 5. In silico gene annotation of the QTL interval enabled the detection of 13 genes involved in immune response to biotic and abiotic stress. Gene expression analysis showed an over expression of the gene encoding for the ethylene-responsive transcription factor ERF098-like, already characterized in Arabidopsis and in rice for its involvement in defense response.ConclusionThe identification of a molecular marker linked to the resistance to spider mite attack can pave the way for the development of marker-assisted breeding plan for the development of novel selection coupling favorable agronomical traits (e.g. fruit quality, yield) with a higher resistance toward the mite.

A novel tomato interspecific (Solanum lycopersicum var. cerasiforme and Solanum pimpinellifolium) MAGIC population facilitates trait association and candidate gene discovery in untapped exotic germplasm.

We developed a novel eight-way tomato multiparental advanced generation intercross (MAGIC) population to improve the accessibility of tomato relatives genetic resources to geneticists and breeders. The interspecific tomato MAGIC population (ToMAGIC) was obtained by intercrossing four accessions each of Solanum lycopersicum var. cerasiforme and Solanum pimpinellifolium, which are the weedy relative and the ancestor of cultivated tomato, respectively. The eight exotic ToMAGIC founders were selected based on a representation of the genetic diversity and geographical distribution of the two taxa. The resulting MAGIC population comprises 354 lines, which were genotyped using a new 12k tomato single primer enrichment technology panel and yielded 6488 high-quality single-nucleotide polymorphism (SNPs). The genotyping data revealed a high degree of homozygosity, an absence of genetic structure, and a balanced representation of the founder genomes. To evaluate the potential of the ToMAGIC population, a proof of concept was conducted by phenotyping it for fruit size, plant pigmentation, leaf morphology, and earliness. Genome-wide association studies identified strong associations for the studied traits, pinpointing both previously identified and novel candidate genes near or within the linkage disequilibrium blocks. Domesticated alleles for fruit size were recessive and were found, at low frequencies, in wild/ancestral populations. Our findings demonstrate that the newly developed ToMAGIC population is a valuable resource for genetic research in tomato, offering significant potential for identifying new genes that govern key traits in tomato. ToMAGIC lines displaying a pyramiding of traits of interest could have direct applicability for integration into breeding pipelines providing untapped variation for tomato breeding.

Development and application of Single Primer Enrichment Technology (SPET) SNP assay for population genomics analysis and candidate gene discovery in lettuce.

Single primer enrichment technology (SPET) is a novel high-throughput genotyping method based on short-read sequencing of specific genomic regions harboring polymorphisms. SPET provides an efficient and reproducible method for genotyping target loci, overcoming the limits associated with other reduced representation library sequencing methods that are based on a random sampling of genomic loci. The possibility to sequence regions surrounding a target SNP allows the discovery of thousands of closely linked, novel SNPs. In this work, we report the design and application of the first SPET panel in lettuce, consisting of 41,547 probes spanning the whole genome and designed to target both coding (~96%) and intergenic (~4%) regions. A total of 81,531 SNPs were surveyed in 160 lettuce accessions originating from a total of 10 countries in Europe, America, and Asia and representing 10 horticultural types. Model ancestry population structure clearly separated the cultivated accessions (Lactuca sativa) from accessions of its presumed wild progenitor (L. serriola), revealing a total of six genetic subgroups that reflected a differentiation based on cultivar typology. Phylogenetic relationships and principal component analysis revealed a clustering of butterhead types and a general differentiation between germplasm originating from Western and Eastern Europe. To determine the potentiality of SPET for gene discovery, we performed genome-wide association analysis for main agricultural traits in L. sativa using six models (GLM naive, MLM, MLMM, CMLM, FarmCPU, and BLINK) to compare their strength and power for association detection. Robust associations were detected for seed color on chromosome 7 at 50 Mbp. Colocalization of association signals was found for outer leaf color and leaf anthocyanin content on chromosome 9 at 152 Mbp and on chromosome 5 at 86 Mbp. The association for bolting time was detected with the GLM, BLINK, and FarmCPU models on chromosome 7 at 164 Mbp. Associations were detected in chromosomal regions previously reported to harbor candidate genes for these traits, thus confirming the effectiveness of SPET for GWAS. Our findings illustrated the strength of SPET for discovering thousands of variable sites toward the dissection of the genomic diversity of germplasm collections, thus allowing a better characterization of lettuce collections.

Evaluation of three sets of advanced backcrosses of eggplant with wild relatives from different gene pools under low N fertilization conditions.

The development of new cultivars with improved nitrogen use efficiency (NUE) is key for implementing sustainable agriculture practices. Crop wild relatives (CWRs) provide valuable genetic resources for breeding programs aimed at achieving this goal. In this study, three eggplant (Solanum melongena) accessions together with their advanced backcrosses (ABs; BC3 to BC5 generations) were evaluated for 22 morpho-agronomic, physiological, and NUE traits under low nitrogen (LN) fertilization conditions. The ABs were developed with introgressions from the wild relatives Solanum insanum, Solanum dasyphyllum, and Solanum elaeagnifolium. The AB population comprised a total of 25, 59, and 59 genotypes, respectively, with overall donor wild relative genome coverage percentages of 58.8%, 46.3%, and 99.2%. The three S. melongena recurrent parents were also evaluated under control (normal) N fertilization. Reduction of N fertilization in the parents resulted in decreased chlorophyll content-related traits, aerial biomass, stem diameter, and yield and increased NUE, nitrogen uptake efficiency (NUpE), and nitrogen utilization efficiency (NUtE). However, the decrease in yield was moderate, ranging between 62.6% and 72.6%. A high phenotypic variation was observed within each of the three sets of ABs under LN conditions, with some individuals displaying improved transgressive characteristics over the recurrent parents. Using the single primer enrichment technology 5k probes platform for high-throughput genotyping, we observed a variable but high degree of recurrent parent genome recovery in the ABs attributable to the lines recombination, allowing the successful identification of 16 quantitative trait loci (QTL). Different allelic effects were observed for the introgressed QTL alleles. Several candidate genes were identified in the QTL regions associated with plant growth, yield, fruit size, and NUE-related parameters. Our results show that eggplant materials with introgressions from CWRs can result in a dramatic impact in eggplant breeding for a more sustainable agriculture.

Toward a Molecular Approach to Chronotype Assessment.

The aim of the present study was to develop a Polygenic Score-based model for molecular chronotype assessment. Questionnaire-based phenotypical chronotype assessment was used as a reference. In total, 54 extremely morning/morning (MM/M; 35 females, 39.7 ± 3.8 years) and 44 extremely evening/evening (EE/E; 20 females, 27.3 ± 7.7 years) individuals donated a buccal DNA sample for genotyping by sequencing of the entire genetic variability of 19 target genes known to be involved in circadian rhythmicity and/or sleep duration. Targeted genotyping was performed using the single primer enrichment technology and a specifically designed panel of 5526 primers. Among 2868 high-quality polymorphisms, a cross-validation approach lead to the identification of 83 chronotype predictive variants, including previously known and also novel chronotype-associated polymorphisms. A large (35 single-nucleotide polymorphisms [SNPs]) and also a small (13 SNPs) panel were obtained, both with an estimated predictive validity of approximately 80%. Potential mechanistic hypotheses for the role of some of the newly identified variants in modulating chronotype are formulated. Once validated in independent populations encompassing the whole range of chronotypes, the identified panels might become useful within the setting of both circadian public health initiatives and precision medicine.

A Deep Learning-Based System (Microscan) for the Identification of Pollen Development Stages and Its Application to Obtaining Doubled Haploid Lines in Eggplant.

The development of double haploids (DHs) is a straightforward path for obtaining pure lines but has multiple bottlenecks. Among them is the determination of the optimal stage of pollen induction for androgenesis. In this work, we developed Microscan, a deep learning-based system for the detection and recognition of the stages of pollen development. In a first experiment, the algorithm was developed adapting the RetinaNet predictive model using microspores of different eggplant accessions as samples. A mean average precision of 86.30% was obtained. In a second experiment, the anther range to be cultivated in vitro was determined in three eggplant genotypes by applying the Microscan system. Subsequently, they were cultivated following two different androgenesis protocols (Cb and E6). The response was only observed in the anther size range predicted by Microscan, obtaining the best results with the E6 protocol. The plants obtained were characterized by flow cytometry and with the Single Primer Enrichment Technology high-throughput genotyping platform, obtaining a high rate of confirmed haploid and double haploid plants. Microscan has been revealed as a tool for the high-throughput efficient analysis of microspore samples, as it has been exemplified in eggplant by providing an increase in the yield of DHs production.

SILEX: a fast and inexpensive high-quality DNA extraction method suitable for multiple sequencing platforms and recalcitrant plant species

BackgroundThe use of sequencing and genotyping platforms has undergone dramatic improvements, enabling the generation of a wealth of genomic information. Despite this progress, the availability of high-quality genomic DNA (gDNA) in sufficient concentrations is often a main limitation, especially for third-generation sequencing platforms. A variety of DNA extraction methods and commercial kits are available. However, many of these are costly and frequently give either low yield or low-quality DNA, inappropriate for next generation sequencing (NGS) platforms. Here, we describe a fast and inexpensive DNA extraction method (SILEX) applicable to a wide range of plant species and tissues.ResultsSILEX is a high-throughput DNA extraction protocol, based on the standard CTAB method with a DNA silica matrix recovery, which allows obtaining NGS-quality high molecular weight genomic plant DNA free of inhibitory compounds. SILEX was compared with a standard CTAB extraction protocol and a common commercial extraction kit in a variety of species, including recalcitrant ones, from different families. In comparison with the other methods, SILEX yielded DNA in higher concentrations and of higher quality. Manual extraction of 48 samples can be done in 96 min by one person at a cost of 0.12 €/sample of reagents and consumables. Hundreds of tomato gDNA samples obtained with either SILEX or the commercial kit were successfully genotyped with Single Primer Enrichment Technology (SPET) with the Illumina HiSeq 2500 platform. Furthermore, DNA extracted from Solanum elaeagnifolium using this protocol was assessed by Pulsed-field gel electrophoresis (PFGE), obtaining a suitable size ranges for most sequencing platforms that required high-molecular-weight DNA such as Nanopore or PacBio.ConclusionsA high-throughput, fast and inexpensive DNA extraction protocol was developed and validated for a wide variety of plants and tissues. SILEX offers an easy, scalable, efficient and inexpensive way to extract DNA for various next-generation sequencing applications including SPET and Nanopore among others.

Fostering Conservation via an Integrated Use of Conventional Approaches and High-Throughput SPET Genotyping: A Case Study Using the Endangered Canarian Endemics Solanum lidii and S. vespertilio (Solanaceae).

Islands provide unique opportunities to integrated research approaches to study evolution and conservation because boundaries are circumscribed, geological ages are often precise, and many taxa are greatly imperiled. We combined morphological and hybridization studies with high-throughput genotyping platforms to streamline relationships in the endangered monophyletic and highly diverse lineage of Solanum in the Canarian archipelago, where three endemic taxa are currently recognized. Inter-taxa hybridizations were performed, and morphological expression was assessed with a common-garden approach. Using the eggplant Single Primer Enrichment Technology (SPET) platform with 5,093 probes, 74 individuals of three endemic taxa (Solanum lidii, S. vespertilio subsp. vespertilio, and S. vespertilio subsp. doramae) were sampled for SNPs. While morphological and breeding studies showed clear distinctions and some continuous variation, inter-taxon hybrids were fertile and heterotic for vigor traits. SPET genotyping revealed 1,421 high-quality SNPs and supported four, not three, distinct taxonomic entities associated with post-emergence geological, ecological and geographic factors of the islands. Given the lack of barriers to hybridization among all the taxa and their molecular differences, great care must be taken in population management. Conservation strategies must take account of the sexual and breeding systems and genotypic distribution among populations to successfully conserve and restore threatened/endangered island taxa, as exemplified by Solanum on the Canary Islands.

Construction of a high density linkage map in Oil Palm using SPET markers

A high-density genetic linkage map from a controlled cross of two oil palm (Elaeis guineensis) genotypes was constructed based on Single Primer Enrichment Technology (SPET) markers. A 5K panel of hybridization probes were used for this purpose which was derived from previously developed SNP primers in oil palm. Initially, 13,384 SNPs were detected which were reduced to 13,073 SNPs after filtering for only bi-allelic SNP. Around 75% of the markers were found to be monomorphic in the progeny, reducing the markers left for linkage mapping to 3,501. Using Lep-MAP3 software, a linkage map was constructed which contained initially 2,388 markers and had a total length of 1,370 cM. In many cases several adjacent SNP were located on the same locus, due to missing recombination events between them, leading to a total of 1,054 loci on the 16 LG. Nevertheless, the marker density of 1.74 markers per cM (0.57 cM/marker) should allow the detection of QTLs in the future. This study shows that cost efficient SPET markers are suitable for linkage map construction in oil palm and probably, also in other species.

Single Primer Enrichment Technology (SPET) for High-Throughput Genotyping in Tomato and Eggplant Germplasm.

Single primer enrichment technology (SPET) is a new, robust, and customizable solution for targeted genotyping. Unlike genotyping by sequencing (GBS), and like DNA chips, SPET is a targeted genotyping technology, relying on the sequencing of a region flanking a primer. Its reliance on single primers, rather than on primer pairs, greatly simplifies panel design, and allows higher levels of multiplexing than PCR-based genotyping. Thanks to the sequencing of the regions surrounding the target SNP, SPET allows the discovery of thousands of closely linked, novel SNPs. In order to assess the potential of SPET for high-throughput genotyping in plants, a panel comprising 5k target SNPs, designed both on coding regions and introns/UTRs, was developed for tomato and eggplant. Genotyping of two panels composed of 400 tomato and 422 eggplant accessions, comprising both domesticated material and wild relatives, generated a total of 12,002 and 30,731 high confidence SNPs, respectively, which comprised both target and novel SNPs in an approximate ratio of 1:1.6, and 1:5.5 in tomato and eggplant, respectively. The vast majority of the markers was transferrable to related species that diverged up to 3.4 million years ago (Solanum pennellii for tomato and S. macrocarpon for eggplant). Maximum Likelihood phylogenetic trees and PCA outputs obtained from the whole dataset highlighted genetic relationships among accessions and species which were congruent with what was previously reported in literature. Better discrimination among domesticated accessions was achieved by using the target SNPs, while better discrimination among wild species was achieved using the whole SNP dataset. Our results reveal that SPET genotyping is a robust, high-throughput technology for genetic fingerprinting, with a high degree of cross-transferability between crops and their cultivated and wild relatives, and allows identification of duplicates and mislabeled accessions in genebanks.

Single primer enrichment technology as a tool for massive genotyping: a benchmark on black poplar and maize.

The advent of molecular breeding is advocated to improve the productivity and sustainability of second-generation bioenergy crops. Advanced molecular breeding in bioenergy crops relies on the ability to massively sample the genetic diversity. Genotyping-by-sequencing has become a widely adopted method for cost-effective genotyping. It basically requires no initial investment for design as compared with array-based platforms which have been shown to offer very robust assays. The latter, however, has the drawback of being limited to analyse only the genetic diversity accounted during selection of a set of polymorphisms and design of the assay. In contrast, genotyping-by-sequencing with random sampling of genomic loci via restriction enzymes or random priming has been shown to be fast and convenient but lacks the ability to target specific regions of the genome and to maintain high reproducibility across laboratories. Here we present a first adoption of single-primer enrichment technology (SPET) which provides a highly efficient and scalable system to obtain targeted sequence-based large genotyping data sets, bridging the gaps between array-based systems and traditional sequencing-based protocols. To fully explore SPET performance, we conducted a benchmark study in ten Zea mays lines and a large-scale study of a natural black poplar population of 540 individuals with the aim of discovering polymorphisms associated with biomass-related traits. Our results showed the ability of this technology to provide dense genotype information on a customized panel of selected polymorphisms, while yielding hundreds of thousands of untargeted variable sites. This provided an ideal resource for association analysis of natural populations harbouring unexplored allelic diversities and structure such as in black poplar. The improvement of sequencing throughput and the development of efficient library preparation methods has made it feasible to carry out targeted genotyping-by-sequencing experiments cost-competitively with either random complexity reduction systems or traditional array-based platforms, while maintaining the key advantages of both technologies.

Abstract 5335: A highly efficient targeted bisulfite sequencing method for accurate DNA methylation profiling

Abstract Background DNA methylation plays an important role in gene regulation. Bisulfite sequencing (BS), in which unmethylated cytosines are converted to uracil while methylated cytosines remain intact, is considered as the gold standard for DNA methylation detection with single nucleotide resolution. Due to the high cost of whole genome BS and the low throughput of amplicon BS, there remains the need for new targeted bisulfite sequencing methods with high efficiency and flexibility. Results We developed a targeted bisulfite sequencing method, by incorporating single primer enrichment (SPE) and molecular barcoding (UMI) technology. This enables flexible and scalable targeted DNA methylation analysis with high efficiency. We first studied the ability of our assay to detect CpG methylation at various levels in reference materials. We also evaluated its utility in profiling CpG methylation in different cell line DNA, and compared the results with published data from alternative technologies (WBS, RRBS and microarray). Conclusions We demonstrated the successful implementation of SPE and UMI technology on bisulfite converted DNA with high enrichment specificity and low bias. We showed that our method accurately detected CpG methylation at different levels, in concordance with expected titration mixture or published datasets. Comparing to reported amplicon BS, our technology enables much higher multiplexing scale and much simpler workflow. Comparing to probe capture based enrichment, our technology enables much lower DNA input, much higher sequencing efficiency (on-target) and shorter turnaround time. Citation Format: Quan Peng, Daniel Kim, Mohammad Nezami Ranjbar, Sascha Strauss, Scott Winter, Yexun Wang. A highly efficient targeted bisulfite sequencing method for accurate DNA methylation profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5335.

Abstract 2785: A comprehensive RNA-based assay for treatment prediction in non-small cell lung cancer patients

Abstract Purpose: In late-stage lung cancer an increasing number of genomic aberrations is used to predict either sensitivity to, or resistance against, targeted therapies. These include gene mutations, gene fusions, amplifications and in the near future different relevant splice variants. Currently, detection of each type of aberration is carried out with different tests. We have set out to develop a novel all-in-one assay to detect the various types of aberrations, e.g. mutations, gene fusions and overexpression. The latter is assumed to be the biological marker that is underlying gene amplification. Methods: Our assay is based on the Single Primer Enrichment Technology (SPET), allowing amplification of a target region using only a single sequence-specific primer. Our first custom-designed panel targets a comprehensive list of hotspots with therapeutic and prognostic significance in lung cancer, including EGFR, ALK, MET, KRAS, NRAS, PIK3CA, ROS1, BRAF, FGFR1 and RET. Using total RNA as input, we will be able to efficiently detect mutations, gene fusions and aberrant expression levels of selected genes. This test may also detect tumor-specific aberrations in platelets. Results: As a proof of principle we analyzed RNA derived from 8 lung cancer-derived cell lines, from two frozen tumor biopsies, and from 10 FFPE biopsies all with confirmed genomic alterations by clinically approved assays. In total, conventional methods detected 18 small mutations, five gene fusions and three gene amplifications, that are all covered by our assay. Of these, 14 mutations, and four gene fusions were readily detected with our assay. The detection of three mutations failed because of low coverage of the target region, probably due to a less optimal design of the specific primer. One small deletion, and one gene fusion were not detected with our RNA-based assay, despite a high read coverage. Quantification of the expression level of the amplified genes is still under investigation. Conclusion: Our preliminary data indicate this novel RNA-based assay not only efficiently identifies all crucial mutations in lung cancer cell lines, but also in small frozen and FFPE tumor biopsies of lung cancer patients. Our next goal is to test this novel method on RNA derived from platelets from cancer patients, providing a minimal invasive procedure to monitor the state of disease in those patients. Citation Format: Klaas Kok, Jaicong Wei, Anna Rybczynska, Martijn Terpstra, Anthonie van der Wekken, Jeroen Hilterman, Ed Schuuring, Rolf Sijmons, Harry Groen, Anke van den Berg. A comprehensive RNA-based assay for treatment prediction in non-small cell lung cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2785. doi:10.1158/1538-7445.AM2017-2785

Abstract 487: A comprehensive target enrichment panel for fusion detection

Abstract Growing interest in cancer classification and progression has accelerated the rate of novel gene fusions discovery with increasing recognition of their roles as biomarkers. RNA-Seq is an attractive method for expressed fusion discovery and detection because of its ability to provide unbiased fusion sequencing information. The ability to detect low expressing fusion transcripts, however, require high sequencing depth and represents a significant financial barrier and identification of clinically relevant fusion sequences from a large data set can be a bioinformatics challenge. To address these challenges we have tested the Ovation® Fusion Panel Target Enrichment System V2, a targeted RNA sequencing method using the Single Primer Enrichment Technology (SPET), with a number of control and clinical samples. Initial studies were performed using a comprehensive target enrichment panel targeting 502 genes with three samples from Horizon DX containing known fusions. Target enriched libraries were constructed with 10 ng and 100 ng inputs and the data was analyzed using the NuFuseD pipeline (available as a point and click BaseSpace application or downloadable linux package) which has been optimized for fusion analysis from this data. Expected fusions were identified at both input levels, even when down sampled to 500K reads, with fewer fusion calls compared to other publically available fusion detection software (Chimerascan and SOAPFuse), suggesting a lower false positive rate. NuFuseD fusion calls are provided with a P-value to help prioritize the identified fusions for subsequent validation. Additionally, NuFuseD detected novel fusions in the control samples demonstrating the advantage of a comprehensive panel compared to more restricted panels. We further validated the target panel using control RNA (UHR and Human Brain) and fresh or FFPE cell lines (NCI-H2228, HCC1937) to further demonstrate our ability to identify known fusions. Finally, the system was evaluated at an external site using patient FFPE samples. These samples (N=8) were from a set of breast, liver and ovarian cancers, containing a unique fusion in 4 of the samples based on DNA based sequencing. Only 1 of the 4 expected fusions were identified using whole transcriptome data (100 million reads) while 3 of the 4 fusions were detected with this assay (10 million reads) demonstrating its ability to generate targeted RNA sequencing libraries with increased sensitivity of gene fusion detection and reduced sequencing costs compared to standard RNA-Seq methods. Citation Format: Ashesh Saraiya, Brandon Young, Tobias Meißner, Brian L. Jones, Stephanie C. Huelga, Doug A. Amorese. A comprehensive target enrichment panel for fusion detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 487. doi:10.1158/1538-7445.AM2017-487

Mutation patterns in small cell and non-small cell lung cancer patients suggest a different level of heterogeneity between primary and metastatic tumors.

Several studies have shown heterogeneity in lung cancer, with parallel existence of multiple subclones characterized by their own specific mutational landscape. The extent to which minor clones become dominant in distinct metastasis is not clear. The aim of our study was to gain insight in the evolution pattern of lung cancer by investigating genomic heterogeneity between primary tumor and its distant metastases. Whole exome sequencing (WES) was performed on 24 tumor and five normal samples of two small cell lung carcinoma (SCLC) and three non-SCLC (NSCLC) patients. Validation of somatic variants in these 24 and screening of 33 additional samples was done by single primer enrichment technology. For each of the three NSCLC patients, about half of the mutations were shared between all tumor samples, whereas for SCLC patients, this percentage was around 95. Independent validation of the non-ubiquitous mutations confirmed the WES data for the vast majority of the variants. Phylogenetic trees indicated more distance between the tumor samples of the NSCLC patients as compared to the SCLC patients. Analysis of 30 independent DNA samples of 16 biopsies used for WES revealed a low degree of intra-tumor heterogeneity of the selected sets of mutations. In the primary tumors of all five patients, variable percentages (19-67%) of the seemingly metastases-specific mutations were present albeit at low read frequencies. Patients with advanced NSCLC have a high percentage of non-ubiquitous mutations indicative of branched evolution. In contrast, the low degree of heterogeneity in SCLC suggests a parallel and linear model of evolution.

An Efficient Method for Identifying Gene Fusions by Targeted RNA Sequencing from Fresh Frozen and FFPE Samples.

Fusion genes are known to be key drivers of tumor growth in several types of cancer. Traditionally, detecting fusion genes has been a difficult task based on fluorescent in situ hybridization to detect chromosomal abnormalities. More recently, RNA sequencing has enabled an increased pace of fusion gene identification. However, RNA-Seq is inefficient for the identification of fusion genes due to the high number of sequencing reads needed to detect the small number of fusion transcripts present in cells of interest. Here we describe a method, Single Primer Enrichment Technology (SPET), for targeted RNA sequencing that is customizable to any target genes, is simple to use, and efficiently detects gene fusions. Using SPET to target 5701 exons of 401 known cancer fusion genes for sequencing, we were able to identify known and previously unreported gene fusions from both fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tissue RNA in both normal tissue and cancer cells.