Sequencing Of Genomic Regions Research Articles

Improving the performance of supervised deep learning for regulatory genomics using phylogenetic augmentation.

Supervised deep learning is used to model the complex relationship between genomic sequence and regulatory function. Understanding how these models make predictions can provide biological insight into regulatory functions. Given the complexity of the sequence to regulatory function mapping (the cis-regulatory code), it has been suggested that the genome contains insufficient sequence variation to train models with suitable complexity. Data augmentation is a widely used approach to increase the data variation available for model training, however current data augmentation methods for genomic sequence data are limited. Inspired by the success of comparative genomics, we show that augmenting genomic sequences with evolutionarily related sequences from other species, which we term phylogenetic augmentation, improves the performance of deep learning models trained on regulatory genomic sequences to predict high-throughput functional assay measurements. Additionally, we show that phylogenetic augmentation can rescue model performance when the training set is down-sampled and permits deep learning on a real-world small dataset, demonstrating that this approach improves data efficiency. Overall, this data augmentation method represents a solution for improving model performance that is applicable to many supervised deep-learning problems in genomics. The open-source GitHub repository agduncan94/phylogenetic_augmentation_paper includes the code for rerunning the analyses here and recreating the figures.

Cis-regulatory control of mammalian Trps1 gene expression.

TRPS1 serves as the causative gene for tricho-rhino phalangeal syndrome, known for its craniofacial and skeletal abnormalities. The Trps1 gene encodes a protein that represses Wnt signaling through strong interactions with Wnt signaling inhibitors. The identification of genomic cis-acting regulatory sequences governing Trps1 expression is crucial for understanding its role in embryogenesis. Nevertheless, to date, no investigations have been conducted concerning these aspects of Trps1.To identify deeply conserved noncoding elements (CNEs) within the Trps1 locus, we employed a comparative genomics approach, utilizing slowly evolving fish such as coelacanth and spotted gar. These analyses resulted in the identification of eight CNEs in the intronic region of the Trps1 gene. Functional characterization of these CNEs in zebrafish revealed their regulatory potential in various tissues, including pectoral fins, heart, and pharyngeal arches. RNA in-situ hybridization experiments revealed concordance between the reporter expression pattern induced by the identified set of CNEs and the spatial expression pattern of the trps1 gene in zebrafish. Comparative in vivo data from zebrafish and mice for CNE7/hs919 revealed conserved functions of these enhancers. Each of these eight CNEs was further investigated in cell line-based reporter assays, revealing their repressive potential. Taken together, in vivo and in vitro assays suggest a context-dependent dual functionality for the identified set of Trps1-associated CNE enhancers.This functionally characterized set of CNE-enhancers will contribute to a more comprehensive understanding of the developmental roles of Trps1 and can aid in the identification of noncoding DNA variants associated with human diseases.

Genomic regulatory sequences in the pathogenesis of bipolar disorder.

The lifetime prevalence of bipolar disorder is estimated to be about 2%. Epigenetics defines regulatory mechanisms that determine relatively stable patterns of gene expression by controlling all key steps, from DNA to messenger RNA to protein. This Mini Review highlights recent discoveries of modified epigenetic control resulting from genetic variants associated with bipolar disorder in genome-wide association studies. The revealed epigenetic abnormalities implicate gene transcription and post-transcriptional regulation. In the light of these discoveries, the Mini Review focuses on the genes PACS1, MCHR1, DCLK3, HAPLN4, LMAN2L, TMEM258, GNL3, LRRC57, CACNA1C, CACNA1D, and NOVA2 and their potential biological role in the pathogenesis of bipolar disorder. Molecular mechanisms under control of these genes do not translate into a unified picture and substantially more research is needed to fill the gaps in knowledge and to solve current limitations in prognosis and treatment of bipolar disorder. In conclusion, the genetic and functional studies confirm the complex nature of bipolar disorder and indicate future research directions to explore possible targeted treatment options, eventually working toward a personalized approach.

Supervised promoter recognition: a benchmark framework

MotivationDeep learning has become a prevalent method in identifying genomic regulatory sequences such as promoters. In a number of recent papers, the performance of deep learning models has continually been reported as an improvement over alternatives for sequence-based promoter recognition. However, the performance improvements in these models do not account for the different datasets that models are evaluated on. The lack of a consensus dataset and procedure for benchmarking purposes has made the comparison of each model’s true performance difficult to assess.ResultsWe present a framework called Supervised Promoter Recognition Framework (‘SUPR REF’) capable of streamlining the complete process of training, validating, testing, and comparing promoter recognition models in a systematic manner. SUPR REF includes the creation of biologically relevant benchmark datasets to be used in the evaluation process of deep learning promoter recognition models. We showcase this framework by comparing the models’ performances on alternative datasets, and properly evaluate previously published models on new benchmark datasets. Our results show that the reliability of deep learning ab initio promoter recognition models on eukaryotic genomic sequences is still not at a sufficient level, as overall performance is still low. These results originate from a subset of promoters, the well-known RNA Polymerase II core promoters. Furthermore, given the observational nature of these data, cross-validation results from small promoter datasets need to be interpreted with caution.

Methods of massive parallel reporter assays for investigation of enhancers

The correct deployment of genetic programs for development and differentiation relies on finely coordinated regulation of specific gene sets. Genomic regulatory elements play an exceptional role in this process. There are few types of gene regulatory elements, including promoters, enhancers, insulators and silencers. Alterations of gene regulatory elements may cause various pathologies, including cancer, congenital disorders and autoimmune diseases. The development of high-throughput genomic assays has made it possible to significantly accelerate the accumulation of information about the characteristic epigenetic properties of regulatory elements. In combination with high-throughput studies focused on the genome-wide distribution of epigenetic marks, regulatory proteins and the spatial structure of chromatin, this significantly expands the understanding of the principles of epigenetic regulation of genes and allows potential regulatory elements to be searched for in silico. However, common experimental approaches used to study the local characteristics of chromatin have a number of technical limitations that may reduce the reliability of computational identification of genomic regulatory sequences. Taking into account the variability of the functions of epigenetic determinants and complex multicomponent regulation of genomic elements activity, their functional verification is often required. A plethora of methods have been developed to study the functional role of regulatory elements on the genome scale. Common experimental approaches for in silico identification of regulatory elements and their inherent technical limitations will be described. The present review is focused on original high-throughput methods of enhancer activity reporter analysis that are currently used to validate predicted regulatory elements and to perform de novo searches. The methods described allow assessing the functional role of the nucleotide sequence of a regulatory element, to determine its exact boundaries and to assess the influence of the local state of chromatin on the activity of enhancers and gene expression. These approaches have contributed substantially to the understanding of the fundamental principles of gene regulation.

Genomics-Guided Drawing of Molecular and Pathophysiological Components of Malignant Regulatory Signatures Reveals a Pivotal Role in Human Diseases of Stem Cell-Associated Retroviral Sequences and Functionally-Active hESC Enhancers.

Repetitive DNA sequences (repeats) colonized two-third of human genome and a majority of repeats comprised of transposable genetic elements (TE). Evolutionary distinct categories of TE represent nucleic acid sequences that are repeatedly copied from and pasted into chromosomes at multiple genomic locations and acquired a multitude of regulatory functions. Here, genomics-guided maps of stemness regulatory signatures were drawn to dissect the contribution of TE to clinical manifestations of malignant phenotypes of human cancers. From patients’ and physicians’ perspectives, the clinical definition of a tumor’s malignant phenotype could be restricted to the early diagnosis of sub-types of malignancies with the increased risk of existing therapy failure and high likelihood of death from cancer. It is the viewpoint from which the understanding of stemness and malignant regulatory signatures is considered in this contribution. Genomics-guided analyses of experimental and clinical observations revealed the pivotal role of human stem cell-associated retroviral sequences (SCARS) in the origin and pathophysiology of clinically-lethal malignancies. SCARS were defined as the evolutionary- and biologically-related family of genomic regulatory sequences, the principal physiological function of which is to create and maintain the stemness phenotype during human preimplantation embryogenesis. For cell differentiation to occur, SCARS expression must be silenced and SCARS activity remains repressed in most terminally-differentiated human cells which are destined to perform specialized functions in the human body. Epigenetic reprogramming, de-repression, and sustained activity of SCARS results in various differentiation-defective phenotypes. One of the most prominent tissue- and organ-specific clinical manifestations of sustained SCARS activities is diagnosed as a pathological condition defined by a consensus of morphological, molecular, and genetic examinations as the malignant growth. Here, contemporary evidence are acquired, analyzed, and reported defining both novel diagnostic tools and druggable molecular targets readily amenable for diagnosis and efficient therapeutic management of clinically-lethal malignancies. These diagnostic and therapeutic approaches are based on monitoring of high-fidelity molecular signals of continuing SCARS activities in conjunction with genomic regulatory networks of thousands’ functionally-active embryonic enhancers affecting down-stream phenotype-altering genetic loci. Collectively, reported herein observations support a model of SCARS-activation triggered singular source code facilitating the intracellular propagation and intercellular (systemic) dissemination of disease states in the human body.

Improving representations of genomic sequence motifs in convolutional networks with exponential activations.

Deep convolutional neural networks (CNNs) trained on regulatory genomic sequences tend to build representations in a distributed manner, making it a challenge to extract learned features that are biologically meaningful, such as sequence motifs. Here we perform a comprehensive analysis on synthetic sequences to investigate the role that CNN activations have on model interpretability. We show that employing an exponential activation to first layer filters consistently leads to interpretable and robust representations of motifs compared to other commonly used activations. Strikingly, we demonstrate that CNNs with better test performance do not necessarily imply more interpretable representations with attribution methods. We find that CNNs with exponential activations significantly improve the efficacy of recovering biologically meaningful representations with attribution methods. We demonstrate these results generalise to real DNA sequences across several in vivo datasets. Together, this work demonstrates how a small modification to existing CNNs, i.e. setting exponential activations in the first layer, can significantly improve the robustness and interpretabilty of learned representations directly in convolutional filters and indirectly with attribution methods.

HemoMIPs-Automated analysis and result reporting pipeline for targeted sequencing data.

Targeted sequencing of genomic regions is a cost- and time-efficient approach for screening patient cohorts. We present a fast and efficient workflow to analyze highly imbalanced, targeted next-generation sequencing data generated using molecular inversion probe (MIP) capture. Our Snakemake pipeline performs sample demultiplexing, overlap paired-end merging, alignment, MIP-arm trimming, variant calling, coverage analysis and report generation. Further, we support the analysis of probes specifically designed to capture certain structural variants and can assign sex using Y-chromosome-unique probes. In a user-friendly HTML report, we summarize all these results including covered, incomplete or missing regions, called variants and their predicted effects. We developed and tested our pipeline using the hemophilia A & B MIP design from the “My Life, Our Future” initiative. HemoMIPs is available as an open-source tool on GitHub at: https://github.com/kircherlab/hemoMIPs

Population genomic SNPs from epigenetic RADs: Gaining genetic and epigenetic data from a single established next‐generation sequencing approach

Abstract Epigenetics is increasingly recognized as an important molecular mechanism underlying phenotypic variation. To study DNA methylation in ecological and evolutionary contexts, epiRADseq is a cost‐effective next‐generation sequencing (NGS) technique based on reduced representation sequencing of genomic regions surrounding non‐/methylated sites. EpiRADseq for genome‐wide methylation abundance and ddRADseq for genome‐wide single‐nucleotide polymorphism (SNP) genotyping follow very similar library and sequencing protocols, but to date these two types of dataset have been handled separately. Here we test the performance of using epiRADseq data to generate SNPs for population genomic analyses. We tested the robustness of using epiRADseq data for population genomics with two independent datasets: a newly generated single‐end dataset for the European whitefish Coregonus lavaretus, and a re‐analysis of publicly available, previously published paired‐end data on corals. Using standard bioinformatic pipelines with a reference genome and without (i.e. de novo catalogue loci), we compared the number of SNPs retained, population genetic summary statistics and population genetic structure between data drawn from ddRADseq and epiRADseq library preparations. We found that SNPs drawn from epiRADseq are similar in number to those drawn from ddRADseq, with 55%–83% of SNPs being identified by both methods. Genotyping error rate was <5% in both approaches. EpiRADseq‐specific allele dropout was low (~1%). For summary statistics, such as heterozygosity and nucleotide diversity, there is a strong correlation between methods (Spearman's rho > 0.88). Furthermore, identical patterns of population genetic structure were recovered using SNPs from epiRADseq and ddRADseq approaches. We show that SNPs obtained from epiRADseq are highly similar to those from ddRADseq and are equivalent for estimating genetic diversity and population structure. This finding is particularly relevant to researchers interested in genetics and epigenetics on the same individuals because using a single epigenomic approach to generate two datasets greatly reduces the time and financial costs compared to using these techniques separately. It also efficiently enables correction of epigenetic estimates with population genetic data. Many studies will benefit from a combinatorial approach with genetic and epigenetic markers and this demonstrates a single, efficient method to do so.

NEW STRAIN OF MUTANT MICE CHARACTERIZED BY SELECTIVE RESISTANCE TO ONE OF TWO SEPTIC SHOCK PROTOCOLS

More than 40 years ago ethyl nitrosoеurea was identified as a powerful mutagen for mammalian germ cells resulting in random point mutations in gamete DNA. This feature allowed the use of this mutagen for genetic studies on the mechanisms of various pathological and physiological processes in model organisms. In our study genome-wide mutagenesis in C3H mice by ethyl nitrosourea followed in generation F3 by selection of animals resistant to acute lethal hepatotoxicity caused by a combination of E. coli lipopolysaccharide (LPS) and D-galactosamine (D-gal). Tumor necrosis factor (TNF) is known to be a critical mediator of this pathology. Exposure to D-galactosamine increases sensitivity of hepatocytes to TNF leading to their necrosis and/or apoptosis. After double LPS/D-gal screening in F3 several mice resistant to LPS/D-gal-induced hepatotoxicity were identified, and became the founders of the corresponding “mutant” families. Using outcrossing to C57BL6 background followed by intercrossing, generations F5 and F7 were obtained. Among families of mutant animals only one family showed the resistance to the combination of LPS and D-gal, but sensitivity to TNF-D-galactosamine. This phenotype showed approximately Mendelian inheritance consistent with the recessive mutation hypothesis. This latter fact was confirmed by the sensitivity of mice from “heterozygous generations” (F4 and F6) to lethal LPS/Dgal hepatotoxicity. Primary bone marrow macrophages obtained from half of the mutant mice showed significantly reduced levels of TNF after LPS stimulation in vitro. At the same time, the serum TNF levels 1 hour after the administration of a non-lethal LPS dose did not differ in the mutant family mice and wild-type mice. These results implicate a recessive mutation either in innate TLR4-mediated signaling pathway, including proteins associated with LPS transfer, adapter molecules, components of kinase signaling cascades, transcription factors, or in enzymes involved in regulation of TLR4 cascades, such as components of the ubiquitin cycle, or in genomic regulatory sequences that control the expression of one of these genes, including the tnf gene.

Computational Analysis of IDH1, IDH2, and TP53 Mutations in Low-Grade Gliomas Including Oligodendrogliomas and Astrocytomas.

Introduction:The emergence of new omics approaches, such as genomic algorithms to identify tumor mutations and molecular modeling tools to predict the three-dimensional structure of proteins, has facilitated the understanding of the dynamic mechanisms involved in the pathogenesis of low-grade gliomas including oligodendrogliomas and astrocytomas.Methods:In this study, we targeted known mutations involved in low-grade gliomas, starting with the sequencing of genomic regions encompassing exon 4 of isocitrate dehydrogenase 1 (IDH1) and isocitrate dehydrogenase 2 (IDH2) and the four exons (5-6 and 7-8) of TP53 from 32 samples, followed by computational analysis to study the impact of these mutations on the structure and function of 3 proteins IDH1, IDH2, and p53.Results:We obtain a mutation that has an effect on the catalytic site of the protein IDH1 as R132H and on the catalytic site of the protein IDH2 as R172M. Other mutations at p53 have been identified as K305N, which is a pathogenic mutation; R175 H, which is a benign mutation; and R158G, which disrupts the structural conformation of the tumor suppressor protein.Conclusion:In low-grade gliomas, mutations in IDH1, IDH2, and TP53 may be the key to tumor progression because they have an effect on the function of the protein such as mutations R132H in IDH1 and R172M in IDH2, which change the function of the enzyme alpha-ketoglutarate, or R158G in TP53, which affects the structure of the generated protein, thus their importance in understanding gliomagenesis and for more accurate diagnosis complementary to the anatomical pathology tests.

Representation learning of genomic sequence motifs with convolutional neural networks.

Although convolutional neural networks (CNNs) have been applied to a variety of computational genomics problems, there remains a large gap in our understanding of how they build representations of regulatory genomic sequences. Here we perform systematic experiments on synthetic sequences to reveal how CNN architecture, specifically convolutional filter size and max-pooling, influences the extent that sequence motif representations are learned by first layer filters. We find that CNNs designed to foster hierarchical representation learning of sequence motifs—assembling partial features into whole features in deeper layers—tend to learn distributed representations, i.e. partial motifs. On the other hand, CNNs that are designed to limit the ability to hierarchically build sequence motif representations in deeper layers tend to learn more interpretable localist representations, i.e. whole motifs. We then validate that this representation learning principle established from synthetic sequences generalizes to in vivo sequences.

Биоинформатический алгоритм обработки данных высокопроизводительного секвенирования для прецизионной идентификации соматических инсерций ретроэлементов

Retroelements are considered as one of the important sources of genomic variability in modern humans. It is known that transposition activity of retroelements in germline cells generates new insertions in various genomic loci and sometimes results in genetic diseases. Retroelements activity in somatic cells is restricted by different cellular mechanisms; however, there is an evidence for it in some tissue types. Somatic insertions can trigger tumorigenesis or participate in normal functioning such as generation of neurons' plasticity. In spite of the rapid development of high-throughput sequencing methods a confident detection of somatic insertions is still quite a challenging task. That, in part, is due to the absence of adequate bioinformatic tools for the analysis of sequencing data. Here, we propose an advanced computational pipeline for the identification of somatic insertions in datasets generated by selective amplification and high-throughput sequencing of genomic regions flanking insertions of AluYa5. Particular attention is paid for the identification of various artifacts arising in course of library preparation and the parameters for their filtration. Pipeline sensitivity is confirmed by in silico experiments with artificial datasets. Using the proposed pipeline we remove at least 80% of artifacts and preserve 75% of potentially somatic insertions. The approaches used in this work can be applied for the study of other mobile elements insertion variability.

AP-1 Transcription Factors and the BAF Complex Mediate Signal-Dependent Enhancer Selection

Enhancer elements are genomic regulatory sequences that direct the selective expression of genes so that genetically identical cells can differentiate and acquire the highly specialized forms and functions required to build a functioning animal. To differentiate, cells must select from among the ∼106 enhancers encoded in the genome the thousands of enhancers that drive the gene programs that impart their distinct features. We used a genetic approach to identify transcription factors (TFs) required for enhancer selection in fibroblasts. This revealed that the broadly expressed, growth-factor-inducible TFs FOS/JUN (AP-1) play a central role in enhancer selection. FOS/JUN selects enhancers together withcell-type-specific TFs by collaboratively binding tonucleosomal enhancers and recruiting the SWI/SNF (BAF) chromatin remodeling complexto establish accessible chromatin. These experiments demonstrate how environmental signals acting via FOS/JUN and BAF coordinate with cell-type-specific TFs to select enhancer repertoires that enable differentiation during development.

Therapeutic Antibodies to KIR3DL2 and Other Target Antigens on Cutaneous T-Cell Lymphomas.

KIR3DL2 is a member of the killer cell immunoglobulin-like receptor (KIR) family that was initially identified at the surface of natural killer (NK) cells. KIR3DL2, also known as CD158k, is expressed as a disulfide-linked homodimer. Each chain is composed of three immunoglobulin-like domains and a long cytoplasmic tail containing two immunoreceptor tyrosine-based inhibitory motifs. Beside its expression on NK cells, it is also found on rare circulating T lymphocytes, mainly CD8+. Although the KIR gene number varies between haplotype, KIR3DL2 is a framework gene present in all individuals. Together with the presence of genomic regulatory sequences unique to KIR3DL2, this suggests some particular functions for the derived protein in comparison with other KIR family members. Several ligands have been identified for KIR3DL2. As for other KIRs, binding to HLA class I molecules is essential for NK development by promoting phenomena such as licensing and driving NK cell maturation. For KIR3DL2, this includes binding to HLA-A3 and -A11 and to the free heavy chain form of HLA-B27. In addition, KIR3DL2 binds to CpG oligonucleotides (ODN) and ensures their transport to endosomal toll-like receptor 9 that promotes cell activation. These characteristics have implicated KIR3DL2 in several pathologies: ankylosing spondylitis and cutaneous T-cell lymphomas such as Sézary syndrome, CD30+ cutaneous lymphoma, and transformed mycosis fungoides. Consequently, a new generation of humanized monoclonal antibodies (mAbs) directed against KIR3DL2 has been helpful in the diagnosis, follow-up, and treatment of these diseases. In addition, preliminary clinical studies of a novel targeted immunotherapy for cutaneous T-cell lymphomas using the anti-KIR3DL2 mAb IPH4102 are now underway. In this review, we discuss the various aspects of KIR3DL2 on the functions of CD4+ T cells and how targeting this receptor helps to develop innovative therapeutic strategies.

Neural progenitor cells and their role in the development and evolutionary expansion of the neocortex.

The evolutionary expansion of the mammalian brain, notably the neocortex, provides a platform for the higher cognitive abilities that characterize humans. Cortical expansion is accompanied by increased folding of the pial surface, which gives rise to a gyrencephalic (folded) rather than lissencephalic (unfolded) neocortex. This expansion reflects the prolonged and increased proliferation of neural stem and progenitor cells (NPCs). Distinct classes of NPCs can be distinguished based on either cell biological criteria (apical progenitors [APs], basal progenitors [BPs]) or lineage (primary progenitors and secondary progenitors). Cortical expansion in development and evolution is linked to an increased abundance and proliferative capacity of BPs, notably basal radial glial cells, a recently characterized type of secondary progenitor derived from apical radial glial cells, the primary progenitors. To gain insight into the molecular basis underlying the prolonged and increased proliferation of NPCs and in particular BPs, comparative genomic and transcriptomic approaches, mostly for human versus mouse, have been employed and applied to specific NPC types and subpopulations. These have revealed two principal sets of molecular changes. One concerns differences in the expression of common genes between species with different degrees of cortical expansion. The other comprises human-specific genes or genomic regulatory sequences. Various systems that allow functional testing of these genomic and gene expression differences between species have emerged, including transient and stable transgenesis, genome editing, cerebral organoids, and organotypic slice cultures. These provide future avenues for uncovering the molecular basis of cortical expansion. WIREs Dev Biol 2017, 6:e256. doi: 10.1002/wdev.256 For further resources related to this article, please visit the WIREs website.

Bovine herpesvirus-1: Genetic diversity of field strains from cattle with respiratory disease, genital, fetal disease and systemic neonatal disease and their relationship to vaccine strains

Bovine herpesvirus-1 (BoHV-1) causes disease in cattle with varied clinical forms. In the U.S. there are two BoHV1 subtypes, BoHV-1.1 and BoHV-1.2b. Control programs in North America incorporate modified live (MLV) or killed (KV) viral vaccines. However, BoHV-1 strains continue to be isolated from diseased animals or fetuses after vaccination. It is possible to differentiate BoHV-1 wild-type from MLV vaccine strains by determining their single nucleotide polymorphism (SNP) patterns through either whole-genome sequencing or PCR sequencing of genomic regions containing vaccine-defining SNPs. To determine the BoHV-1 subtype in clinical isolates and their relationship to MLV strains, 8 isolates from varied clinical disease at three different laboratories in the U.S. were sequenced and phylogenetically analyzed. Five samples were isolated within the past 5 years from New York and 3 were archived samples recovered 35 years prior from Oklahoma and Louisiana. Based on phylogenetic analysis, four of the cases appeared to be due to an MLV vaccine: 3 cases of aborted fetuses and one neonate with systemic BoHV-1 disease. One aborted fetus was from a herd with no reported history of MLV vaccination in two years. The remaining four isolates did not group with any MLV vaccines: two were associated with bovine respiratory disease, one with vulvovaginitis, and a fourth was determined to be a BoHV-1.2b respiratory isolate. Recovery of BoHV-1.1 that is very closely related to an MLV vaccine virus from a herd not receiving vaccines in an extended period prior to its isolation suggests that MLV viruses may remain latent or circulate within herds for long periods.

Whole Gene Capture Analysis of 15 CRC Susceptibility Genes in Suspected Lynch Syndrome Patients.

Background and AimsLynch Syndrome (LS) is caused by pathogenic germline variants in one of the mismatch repair (MMR) genes. However, up to 60% of MMR-deficient colorectal cancer cases are categorized as suspected Lynch Syndrome (sLS) because no pathogenic MMR germline variant can be identified, which leads to difficulties in clinical management. We therefore analyzed the genomic regions of 15 CRC susceptibility genes in leukocyte DNA of 34 unrelated sLS patients and 11 patients with MLH1 hypermethylated tumors with a clear family history.MethodsUsing targeted next-generation sequencing, we analyzed the entire non-repetitive genomic sequence, including intronic and regulatory sequences, of 15 CRC susceptibility genes. In addition, tumor DNA from 28 sLS patients was analyzed for somatic MMR variants.ResultsOf 1979 germline variants found in the leukocyte DNA of 34 sLS patients, one was a pathogenic variant (MLH1 c.1667+1delG). Leukocyte DNA of 11 patients with MLH1 hypermethylated tumors was negative for pathogenic germline variants in the tested CRC susceptibility genes and for germline MLH1 hypermethylation. Somatic DNA analysis of 28 sLS tumors identified eight (29%) cases with two pathogenic somatic variants, one with a VUS predicted to pathogenic and LOH, and nine cases (32%) with one pathogenic somatic variant (n = 8) or one VUS predicted to be pathogenic (n = 1).ConclusionsThis is the first study in sLS patients to include the entire genomic sequence of CRC susceptibility genes. An underlying somatic or germline MMR gene defect was identified in ten of 34 sLS patients (29%). In the remaining sLS patients, the underlying genetic defect explaining the MMRdeficiency in their tumors might be found outside the genomic regions harboring the MMR and other known CRC susceptibility genes.

Cloning and characterization of drought stress-induced NAC transcription factors fromBrassica junceaandSinapis alba

The plant specific NAC [for NAM (no apical meristem), ATAF, CUC (cup-shaped cotyledon)] TFs are one of the largest plant TF families that play important roles in plant development and stress tolerance. Suppression subtractive hybridization (SSH) analysis with using drought stressed plants of S. alba lead to the identification of several stress responsive ESTs. Two of them homologous to Arabidopsis NAC14 and NAC19 were selected for cloning of full length CDS and expression analysis in Brassica and related species with contrasting drought tolerance. NAC14 and NAC19 genes were cloned from drought tolerant Sinapis alba and Brassica juncea cvs. RGN73 and Varuna, and drought sensitive B. juncea cvs. RLM619, BEC144 and BioYSR. Sequencing of genomic region coding for these NACs revealed that both NAC14 and NAC19 contain 3 exons and 2 introns each. In silico analysis of protein structure led to development of 3D models of these stress responsive NAC TFs. Although both proteins have 7 strands of β sheets, the NAC14 had 5 β sheets of type A and 2 β sheets of type B, while NAC14 have all 7 β sheets of type A. These proteins also differed in helix content, β turns and g turns. This suggest their functional diversity under abiotic stresses. Real-time RT-PCR expression analysis revealed that both the genes were up-regulated under drought stress in the leaves of B. juncea genotypes Varuna and BioYSR. In addition, NAC14 was up-regulated in the leaves of RLM619, while NAC19 was up-regulated in the leaves of S. alba and BEC144 under drought stress as compared to control conditions. Interestingly, drought stress did not up-regulate these genes in RGN73. This study revealed genotypic variation in the drought regulation of NAC TFs in B. juncea and S. alba.

The TTSMI database: a catalog of triplex target DNA sites associated with genes and regulatory elements in the human genome.

A triplex target DNA site (TTS), a stretch of DNA that is composed of polypurines, is able to form a triple-helix (triplex) structure with triplex-forming oligonucleotides (TFOs) and is able to influence the site-specific modulation of gene expression and/or the modification of genomic DNA. The co-localization of a genomic TTS with gene regulatory signals and functional genome structures suggests that TFOs could potentially be exploited in antigene strategies for the therapy of cancers and other genetic diseases. Here, we present the TTS Mapping and Integration (TTSMI; http://ttsmi.bii.a-star.edu.sg) database, which provides a catalog of unique TTS locations in the human genome and tools for analyzing the co-localization of TTSs with genomic regulatory sequences and signals that were identified using next-generation sequencing techniques and/or predicted by computational models. TTSMI was designed as a user-friendly tool that facilitates (i) fast searching/filtering of TTSs using several search terms and criteria associated with sequence stability and specificity, (ii) interactive filtering of TTSs that co-localize with gene regulatory signals and non-B DNA structures, (iii) exploration of dynamic combinations of the biological signals of specific TTSs and (iv) visualization of a TTS simultaneously with diverse annotation tracks via the UCSC genome browser.