Identification of errors introduced during high throughput sequencing of the T cell receptor repertoire

<p>Abstract</p> <p>Background</p> <p>Recent advances in massively parallel sequencing have increased the depth at which T cell receptor (TCR) repertoires can be probed by >3log10, allowing for saturation sequencing of immune repertoires. The resolution of this sequencing is dependent on its accuracy, and direct assessments of the errors formed during high throughput repertoire analyses are limited.</p> <p>Results</p> <p>We analyzed 3 monoclonal TCR from TCR transgenic, Rag^-/-mice using Illumina^®sequencing. A total of 27 sequencing reactions were performed for each TCR using a trifurcating design in which samples were divided into 3 at significant processing junctures. More than 20 million complementarity determining region (CDR) 3 sequences were analyzed. Filtering for lower quality sequences diminished but did not eliminate sequence errors, which occurred within 1-6% of sequences. Erroneous sequences were pre-dominantly of correct length and contained single nucleotide substitutions. Rates of specific substitutions varied dramatically in a position-dependent manner. Four substitutions, all purine-pyrimidine transversions, predominated. Solid phase amplification and sequencing rather than liquid sample amplification and preparation appeared to be the primary sources of error. Analysis of polyclonal repertoires demonstrated the impact of error accumulation on data parameters.</p> <p>Conclusions</p> <p>Caution is needed in interpreting repertoire data due to potential contamination with mis-sequence reads. However, a high association of errors with phred score, high relatedness of erroneous sequences with the parental sequence, dominance of specific nt substitutions, and skewed ratio of forward to reverse reads among erroneous sequences indicate approaches to filter erroneous sequences from repertoire data sets.</p

SAR Target Image Generation Method Using Azimuth-Controllable Generative Adversarial Network

Sufficient synthetic aperture radar (SAR) target images are very important for the development of researches. However, available SAR target images are often limited in practice, which hinders the progress of SAR application. In this paper, we propose an azimuth-controllable generative adversarial network to generate precise SAR target images with an intermediate azimuth between two given SAR images' azimuths. This network mainly contains three parts: generator, discriminator, and predictor. Through the proposed specific network structure, the generator can extract and fuse the optimal target features from two input SAR target images to generate SAR target image. Then a similarity discriminator and an azimuth predictor are designed. The similarity discriminator can differentiate the generated SAR target images from the real SAR images to ensure the accuracy of the generated, while the azimuth predictor measures the difference of azimuth between the generated and the desired to ensure the azimuth controllability of the generated. Therefore, the proposed network can generate precise SAR images, and their azimuths can be controlled well by the inputs of the deep network, which can generate the target images in different azimuths to solve the small sample problem to some degree and benefit the researches of SAR images. Extensive experimental results show the superiority of the proposed method in azimuth controllability and accuracy of SAR target image generation

Semi-Supervised SAR ATR Framework with Transductive Auxiliary Segmentation

Convolutional neural networks (CNNs) have achieved high performance in synthetic aperture radar (SAR) automatic target recognition (ATR). However, the performance of CNNs depends heavily on a large amount of training data. The insufficiency of labeled training SAR images limits the recognition performance and even invalidates some ATR methods. Furthermore, under few labeled training data, many existing CNNs are even ineffective. To address these challenges, we propose a Semi-supervised SAR ATR Framework with transductive Auxiliary Segmentation (SFAS). The proposed framework focuses on exploiting the transductive generalization on available unlabeled samples with an auxiliary loss serving as a regularizer. Through auxiliary segmentation of unlabeled SAR samples and information residue loss (IRL) in training, the framework can employ the proposed training loop process and gradually exploit the information compilation of recognition and segmentation to construct a helpful inductive bias and achieve high performance. Experiments conducted on the MSTAR dataset have shown the effectiveness of our proposed SFAS for few-shot learning. The recognition performance of 94.18\% can be achieved under 20 training samples in each class with simultaneous accurate segmentation results. Facing variances of EOCs, the recognition ratios are higher than 88.00\% when 10 training samples each class

In Vivo Response to Methotrexate Forecasts Outcome of Acute Lymphoblastic Leukemia and Has a Distinct Gene Expression Profile

William Evans and colleagues investigate the genomic determinants of methotrexate resistance and interpatient differences in methotrexate response in patients newly diagnosed with childhood acute lymphoblastic leukemia

Association of the germline TP53 R337H mutation with breast cancer in southern Brazil

<p>Abstract</p> <p>Background</p> <p>The germline <it>TP53</it>-R337H mutation is strongly associated with pediatric adrenocortical tumors (ACT) in southern Brazil; it has low penetrance and limited tissue specificity in most families and therefore is not associated with Li-Fraumeni syndrome. However, other tumor types, mainly breast cancer, have been observed in carriers of several unrelated kindreds, raising the possibility that the R337H mutation may also contribute to breast tumorigenesis in a genetic background-specific context.</p> <p>Methods</p> <p>We conducted a case-control study to determine the prevalence of the R337H mutation by sequencing <it>TP</it>53 exon 10 in 123 women with breast cancer and 223 age- and sex-matched control subjects from southern Brazil. Fisher's test was used to compare the prevalence of the R337H.</p> <p>Results</p> <p>The R337H mutation was found in three patients but in none of the controls (p = 0.0442). Among the carriers, two had familial history of cancer meeting the Li-Fraumeni-like criteria. Remarkably, tumors in each of these three cases underwent loss of heterozygosity by eliminating the mutant <it>TP53 </it>allele rather than the wild-type allele. Polymorphisms were identified within the <it>TP53 </it>(R72P and Ins16) and <it>MDM2 </it>(SNP309) genes that may further diminish <it>TP53 </it>tumor suppressor activity.</p> <p>Conclusion</p> <p>These results demonstrate that the R337H mutation can significantly increase the risk of breast cancer in carriers, which likely depends on additional cooperating genetic factors. These findings are also important for understanding how low-penetrant mutant <it>TP53 </it>alleles can differentially influence tumor susceptibility.</p

Agrobacterium tumefaciens-Mediated Transformation of Maize Embryos Using a Standard Binary Vector System

We have achieved routine transformation of maize (Zea mays) using an Agrobacterium tumefaciensstandard binary (non-super binary) vector system. Immature zygotic embryos of the hybrid line Hi II were infected with A. tumefaciens strain EHA101 harboring a standard binary vector and cocultivated in the presence of 400 mg L−1 l-cysteine. Inclusion of l-cysteine in cocultivation medium lead to an improvement in transient β-glucuronidase expression observed in targeted cells and a significant increase in stable transformation efficiency, but was associated with a decrease in embryo response after cocultivation. The average stable transformation efficiency (no. of bialaphos-resistant events recovered per 100 embryos infected) of the present protocol was 5.5%. Southern-blot and progeny analyses confirmed the integration, expression, and inheritance of the bar andgustransgenes in R0, R1, and R2 generations of transgenic events. To our knowledge, this represents the first report in which fertile, stable transgenic maize has been routinely produced using an A. tumefaciensstandard binary vector system

Identification of errors introduced during high throughput sequencing of the T cell receptor repertoire

<p>Abstract</p> <p>Background</p> <p>Recent advances in massively parallel sequencing have increased the depth at which T cell receptor (TCR) repertoires can be probed by >3log10, allowing for saturation sequencing of immune repertoires. The resolution of this sequencing is dependent on its accuracy, and direct assessments of the errors formed during high throughput repertoire analyses are limited.</p> <p>Results</p> <p>We analyzed 3 monoclonal TCR from TCR transgenic, Rag^-/-mice using Illumina^®sequencing. A total of 27 sequencing reactions were performed for each TCR using a trifurcating design in which samples were divided into 3 at significant processing junctures. More than 20 million complementarity determining region (CDR) 3 sequences were analyzed. Filtering for lower quality sequences diminished but did not eliminate sequence errors, which occurred within 1-6% of sequences. Erroneous sequences were pre-dominantly of correct length and contained single nucleotide substitutions. Rates of specific substitutions varied dramatically in a position-dependent manner. Four substitutions, all purine-pyrimidine transversions, predominated. Solid phase amplification and sequencing rather than liquid sample amplification and preparation appeared to be the primary sources of error. Analysis of polyclonal repertoires demonstrated the impact of error accumulation on data parameters.</p> <p>Conclusions</p> <p>Caution is needed in interpreting repertoire data due to potential contamination with mis-sequence reads. However, a high association of errors with phred score, high relatedness of erroneous sequences with the parental sequence, dominance of specific nt substitutions, and skewed ratio of forward to reverse reads among erroneous sequences indicate approaches to filter erroneous sequences from repertoire data sets.</p

Genomic analyses identify recurrent MEF2D fusions in acute lymphoblastic leukemia

Chromosomal rearrangements are initiating events in acute lymphoblastic leukaemia (ALL). Here using RNA sequencing of 560 ALL cases, we identify rearrangements between MEF2D (myocyte enhancer factor 2D) and five genes (BCL9, CSF1R, DAZAP1, HNRNPUL1 and SS18) in 22 B progenitor ALL (B-ALL) cases with a distinct gene expression profile, the most common of which is MEF2DBCL9. Examination of an extended cohort of 1,164 B-ALL cases identified 30 cases with MEF2D rearrangements, which include an additional fusion partner, FOXJ2; thus, MEF2D-rearranged cases comprise 5.3% of cases lacking recurring alterations. MEF2D-rearranged ALL is characterized by a distinct immunophenotype, DNA copy number alterations at the rearrangement sites, older diagnosis age and poor outcome. The rearrangements result in enhanced MEF2D transcriptional activity, lymphoid transformation, activation of HDAC9 expression and sensitive to histone deacetylase inhibitor treatment. Thus, MEF2D-rearranged ALL represents a distinct form of high-risk leukaemia, for which new therapeutic approaches should be considered.This work was supported in part by the American Lebanese Syrian Associated Charities of St. Jude Children’s Research Hospital; by a Stand Up to Cancer Innovative Research Grant and St. Baldrick’s Foundation Scholar Award (to C.G.M.); by a St. Baldrick’s Consortium Award (S.P.H.), by a Leukemia and Lymphoma Society Specialized Center of Research grant (S.P.H. and C.G.M.), by a Lady Tata Memorial Trust Award (I.I.), by a Leukemia and Lymphoma Society Special Fellow Award and Alex’s Lemonade Stand Foundation Young Investigator Awards (K.R.), by an Alex’s Lemonade Stand Foundation Award (M.L.) and by National Cancer Institute Grants CA21765 (St Jude Cancer Center Support Grant), U01 CA157937 (C.L.W. and S.P.H.), U24 CA114737 (to Dr Gastier-Foster), NCI Contract HHSN261200800001E (to Dr Gastier-Foster), U10 CA180820 (ECOG-ACRIN Operations) and CA180827 (E.P.); U10 CA180861 (C.D.B. and G.M.); U24 CA196171 (The Alliance NCTN Biorepository and Biospecimen Resource); CA145707 (C.L.W. and C.G.M.); and grants to the COG: U10 CA98543 (Chair’s grant and supplement to support the COG ALL TARGET project), U10 CA98413 (Statistical Center) and U24 CA114766 (Specimen Banking). This project has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Contract Number HHSN261200800001E

Deregulation of DUX4 and ERG in acute lymphoblastic leukemia

Chromosomal rearrangements deregulating hematopoietic transcription factors are common in acute lymphoblastic leukemia (ALL).1,2 Here, we show that deregulation of the homeobox transcription factor gene DUX4 and the ETS transcription factor gene ERG are hallmarks of a subtype of B-progenitor ALL that comprises up to 7% of B-ALL. DUX4 rearrangement and overexpression was present in all cases, and was accompanied by transcriptional deregulation of ERG, expression of a novel ERG isoform, ERGalt, and frequent ERG deletion. ERGalt utilizes a non-canonical first exon whose transcription was initiated by DUX4 binding. ERGalt retains the DNA-binding and transactivating domains of ERG, but inhibits wild-type ERG transcriptional activity and is transforming. These results illustrate a unique paradigm of transcription factor deregulation in leukemia, in which DUX4 deregulation results in loss-of-function of ERG, either by deletion or induction of expression of an isoform that is a dominant negative inhibitor of wild type ERG function