Knowledge Of Genome Sequence Research Articles

Associations between subjective social status and predictors of interest in genetic testing among women diagnosed with breast cancer at a young age.

Genetic testing for gene mutations which elevate risk for breast cancer is particularly important for women diagnosed at a young age. Differences remain in access and utilization to testing across social groups, and research on the predictors of interest in genetic testing for women diagnosed at a young age is limited. We examined the relationships between subjective social status (SSS) and variables previously identified as possible predictors of genetic testing, including genome sequencing knowledge, genetic worry, cancer worry, health consciousness, decision-making preferences, genetic self-efficacy, genetic-related beliefs, and subjective numeracy, among a cohort of women who were diagnosed with breast cancer at a young age. In this sample (n = 1,076), those who had higher SSS had significantly higher knowledge about the limitations of genome sequencing (Odds Ratio (OR) = 1.11; 95% CI = 1.01-1.21) and significantly higher informational norms (OR = 1.93; 95% CI = 1.19-3.14) than those with lower SSS. Similarly, education (OR = 2.75; 95% CI = 1.79-4.22), health status (OR = 2.18; 95% CI = 1.44-3.31) were significant predictors among higher SSS women compared to lower SSS women in our multivariate analysis. Lower SSS women with low self-reported income (OR = 0.13; 95% CI = 0.08-0.20) had lower odds of genetic testing interest. Our results are consistent with some prior research utilizing proxy indicators for socioeconomic status, but our research adds the importance of using a multidimensional indicator such as SSS to examine cancer and genetic testing predictor outcomes. To develop interventions to improve genetic knowledge, researchers should consider the social status and contexts of women diagnosed with breast cancer at a young age (or before 40 years old) to ensure equity in the distribution of genetic testing benefits.

Saliva proteome of partially- and fully-engorged adult female Haemaphysalis flava ticks

Tick saliva is a reservoir of bioactive proteins. Saliva protein compositions change dynamically during blood-feeding. Decipherment of protein profiles in different blood-feeding stages may bring deeper insight into tick feeding physiology and provide targets for immunologic control alternatives. However, having the infancy of tick genome sequencing, assembly, annotation, and limited knowledge of tick salivary proteins restrain the data interpretation. Here, we aimed to depict the saliva protein profile in partially- (PE) and fully-engorged (FE) Haemaphysalis flava ticks, with a special focus on the analysis of those uncharacterized proteins. Saliva was collected from PE and FE adult female H. flava ticks. Saliva proteins were analyzed by high-performance liquid chromatography-tandem mass spectrometry (HPLC/MS-MS). MS data were searched against an in-house salivary gland transcriptome library for identification of tick-derived proteins. Abundances of proteins were compared between PE and FE ticks. The uncharacterized proteins detected in saliva were further bioinformatically analyzed. In total, 614 proteins were identified including 94 host proteins and 520 tick-derived proteins. The 226 tick-derived high-confidence proteins were classified into 10 categories: transporters, enzymes, protease inhibitors, immunity-related proteins, lipocalins, glycine-rich proteins, muscle proteins, secreted proteins, uncharacterized proteins and others. A total of 98 proteins were shared in both PE and FE with 74 only in PE and 54 only in FE. Abundances of 24 shared proteins were significantly higher in PE. The profile of top 15 most abundant proteins was also different between PE and FE ticks. The 65 uncharacterized proteins detected in tick saliva were branched into subclusters 1 A, 1B, 2, 3 A, 3B and 3 C based on particular motifs like RGD, LRR, indicating their diverse predicted functions like anti-coagulation, regulation of innate immune, or other functions. This study provides and compares saliva proteomes of H. flava ticks in two feeding stages with special cluster analysis on the uncharacterized proteins. Further investigations are needed to confirm the roles of these uncharacterized proteins in ticks.

EP294: Return of genome sequencing results in ostensibly healthy COVID-19 positive individuals: GENCOV Study Canada

Genome sequencing (GS) can identify genetic factors that may influence variability in COVID-19 symptoms and outcomes. In this context, GS can also be used to screen for secondary findings (SF) about inherited predispositions to several other diseases. Attitudes towards the use of GS as a screening tool in the general Canadian population is limited, warranting exploration of individuals’ uptake of SF, knowledge of GS, as well as attitudes toward healthcare and genetics. This study aims to: 1) Determine the uptake of SF (clinically actionable conditions, rare genetic conditions, carrier status, drug reactions, and polygenic risk scores for common conditions) from GS; 2) determine baseline attitudes toward genetics and healthcare; 3) assess the impact of pre-test genetic counseling (GC) interventions on GS knowledge; and, 4) assess the impact of learning SF on patient attitudes, feelings, health outcomes, and health behaviors.

Popular Computational Tools Used for miRNA Prediction and Their Future Development Prospects.

MicroRNAs (miRNAs) are 19-24 nucleotide (nt)-long noncoding, single-stranded RNA molecules that play significant roles in regulating the gene expression, growth, and development of plants and animals. From the year that miRNAs were first discovered until the beginning of the twenty-first century, researchers used experimental methods such as cloning and sequencing to identify new miRNAs and their roles in the posttranscriptional regulation of protein synthesis. Later, in the early 2000s, informatics approaches to the discovery of new miRNAs began to be implemented. With increasing knowledge about miRNA, more efficient algorithms have been developed for computational miRNA prediction. The miRNA research community, hoping for greater coverage and faster results, has shifted from cumbersome and expensive traditional experimental approaches to computational approaches. These computational methods started with homology-based comparisons of known miRNAs with orthologs in the genomes of other species; this method could identify a known miRNA in new species. Second-generation sequencing and next-generation sequencing of mRNA at different developmental stages and in specific tissues, in combination with a better search and alignment algorithm, have accelerated the process of predicting novel miRNAs in a particular species. Using the accumulated annotated miRNA sequence information, researchers have been able to design ab initio algorithms for miRNA prediction independent of genome sequence knowledge. Here, the methods recently used for miRNA computational prediction are summarized and classified into the following four categories: homology-based, target-based, scoring-based, and machine-learning-based approaches. Finally, the future developmental directions of miRNA prediction methods are discussed.

SNP Genotyping with Target Amplicon Sequencing Using a Multiplexed Primer Panel and Its Application to Genomic Prediction in Japanese Cedar, Cryptomeria japonica (L.f.) D.Don

Along with progress in sequencing technology and accumulating knowledge of genome and gene sequences, molecular breeding techniques have been developed for predicting the genetic potential of individual genotypes and for selecting superior individuals. For Japanese cedar (Cryptomeria japonica (L.f.) D.Don), which is the most common coniferous species in Japanese forestry, we constructed a custom primer panel for target amplicon sequencing in order to simultaneously determine 3034 informative single nucleotide polymorphisms (SNPs). We performed primary evaluation of the custom primer panel with actual sequencing and in silico PCR. Genotyped SNPs had a distribution over almost the entire region of the C. japonica linkage map and verified the high reproducibility of genotype calls compared to SNPs obtained by genotyping arrays. Genotyping was performed for 576 individuals of the F1 population, and genomic prediction models were constructed for growth and wood property-related traits using the genotypes. Amplicon sequencing with the custom primer panel enables efficient obtaining genotype data in order to perform genomic prediction, manage clones, and advance forest tree breeding.

AutoCloner: automatic homologue-specific primer design for full-gene cloning in polyploids

BackgroundPolyploid organisms such as wheat complicate even the simplest of procedures in molecular biology. Whilst knowledge of genomic sequences in crops is increasing rapidly, the scientific community is still a long way from producing a full pan-genome for every species. Polymerase chain reaction and Sanger sequencing therefore remain widely used as methods for characterizing gene sequences in many varieties of crops. High sequence similarity between genomes in polyploids means that if primers are not homeologue-specific via the incorporation of a SNP at the 3’ tail, sequences other than the target sequence will also be amplified. Current consensus for gene cloning in wheat is to manually perform many steps in a long bioinformatics pipeline.ResultsHere we present AutoCloner (www.autocloner.com), a fully automated pipeline for crop gene cloning that includes a free-to-use web interface for users. AutoCloner takes a sequence of interest from the user and performs a basic local alignment search tool (BLAST) search against the genome assembly for their particular polyploid crop. Homologous sequences are then compiled with the input sequence into a multiple sequence alignment which is mined for single-nucleotide polymorphisms (SNPs). Various combinations of potential primers that cover the entire gene of interest are then created and evaluated by Primer3; the set of primers with the highest score, as well as all possible primers at every SNP location, are then returned to the user for polymerase chain reaction (PCR). We have successfully used AutoCloner to clone various genes of interest in the Apogee wheat variety, which has no current genome sequence. In addition, we have successfully run the pipeline on ~ 80,000 high-confidence gene models from a wheat genome assembly.ConclusionAutoCloner is the first tool to fully-automate primer design for gene cloning in polyploids, where previously the consensus within the wheat community was to perform this process manually. The web interface for AutoCloner provides a simple and effective polyploid primer-design method for gene cloning, with no need for researchers to download software or input any other details other than their sequence of interest.

Two SNP Markers Identified Using Genotyping-by-Sequencing Are Associated with Remontancy in a Segregating F1 Population of Syringa meyeri ‘Palibin’ × S. pubescens ‘Penda’ Bloomerang®

Lilacs (Syringa sp.) have been used as ornamental plants since the mid-16th century and remain important in modern gardens due to their attractive and fragrant flowers. However, a short flowering season is a critical drawback for their ornamental value. Breeders have identified remontancy (reblooming) in dwarf lilac (Syringa pubescens), and have tried to introgress this trait into related species by interspecific hybridization. Molecular tools for lilac breeding are limited because of the shortage of genome sequence knowledge and currently no molecular markers are available to use in breeding for remontancy. In this study, an F1 population from crossing Syringa meyeri ‘Palibin’ × S. pubescens ‘Penda’ Bloomerang® Purple was created and subjected to genotyping-by-sequencing (GBS) analysis and phenotyped for remontancy. Plants were categorized as remontant, semi-remontant, and nonremontant based on the relative quantity of inflorescences during the second flush of flowers. A total of 20,730 single-nucleotide polymorphism (SNP) markers from GBS were used in marker-trait association to find remontant-specific marker(s) without marker position information. Two SNP markers, TP70580 (A locus) and TP82604 (B locus), were correlated with remontancy. The two loci showed a partial epistasis and additive interaction effects on the level of remontancy. Accumulation of recessive alleles at the two loci was positively correlated with increased reblooming. For example, 87% of aabb plants were remontant, and only 9% were nonremontant. In contrast, 100% of AaBB plants were nonremontant. These two SNP markers associated with remontancy will be useful in developing markers for future breeding and demonstrate the feasibility of developing markers for breeding woody ornamental taxa that lack a reference genome or extensive DNA sequence information.

Techniques for the Measurement of Cell Mediated Immune Responses to Avian Influenza Virus.

Cellular immune responses, through both T and B cells, are critical to understanding the role and regulation of lymphocytes following viral infection, as well as defining responses to vaccination. T cells play a critical role in adaptive immunity, including pathogen elimination through the engagement of CD4 and CD8 receptors, which trigger signaling mechanisms. B cells contribute to generating antibodies following exposure to foreign pathogens through interactions with CD4+ lymphocytes. While these different cell types have distinctly different modes of action in terms of contributions to protection (cytotoxic versus antibody mediated), they account for the majority of adaptive immunity induced following infection or vaccination. While the ability to measure cell-mediated immunity (CMI) has steadily improved, there is much to learn with regard to their contribution to the protection of birds against diseases induced by avian influenza virus. The rapidly increasing knowledge of genomic avian sequences, along with the increasing availability of monoclonal antibodies detecting avian cell-associated antigen markers, has made techniques to measure CMI more specific and informative for researchers.

Development of a measure of genome sequencing knowledge for young people: The kids-KOGS.

Genome sequencing (GS) is increasingly being used to diagnose rare diseases in paediatric patients; however, no measures exist to evaluate their knowledge of this technology. We aimed to develop a robust measure of knowledge of GS (the kids‐KOGS') suitable for use in the paediatric setting as well as for general public education. The target age was 11 to 15 year olds. An iterative process involving six sequential stages was conducted to develop a set of draft true/false items. These were then administered to 539 target‐age school pupils (mean 12.8; SD ± 1.3), from the United Kingdom. Item‐response theory was used to confirm the psychometric suitability of the candidate items. None of the Items was identified as misfits. All 10 items performed well under the two‐parameter logistic model. The internal consistency of the test was 0.84 (Cronbach alpha value) indicating excellent reliability. The mean kids‐KOGS score in the sample overall was 4.24 (SD; 2.49), where 0 = low knowledge and 10 = high knowledge. Age was positively associated with score in a multivariate linear regression. The kids‐KOGS is a short and reliable tool that can be used by researchers and healthcare professionals offering GS to paediatric patients. Further validation in a clinical setting is required.

RAD-sequencing for estimating genomic relatedness matrix-based heritability in the wild: A case study in roe deer.

Estimating the evolutionary potential of quantitative traits and reliably predicting responses to selection in wild populations are important challenges in evolutionary biology. The genomic revolution has opened up opportunities for measuring relatedness among individuals with precision, enabling pedigree-free estimation of trait heritabilities in wild populations. However, until now, most quantitative genetic studies based on a genomic relatedness matrix (GRM) have focused on long-term monitored populations for which traditional pedigrees were also available, and have often had access to knowledge of genome sequence and variability. Here, we investigated the potential of RAD-sequencing for estimating heritability in a free-ranging roe deer (Capreolous capreolus) population for which no prior genomic resources were available. We propose a step-by-step analytical framework to optimize the quality and quantity of the genomic data and explore the impact of the single nucleotide polymorphism (SNP) calling and filtering processes on the GRM structure and GRM-based heritability estimates. As expected, our results show that sequence coverage strongly affects the number of recovered loci, the genotyping error rate and the amount of missing data. Ultimately, this had little effect on heritability estimates and their standard errors, provided that the GRM was built from a minimum number of loci (above 7,000). Genomic relatedness matrix-based heritability estimates thus appear robust to a moderate level of genotyping errors in the SNP data set. We also showed that quality filters, such as the removal of low-frequency variants, affect the relatedness structure of the GRM, generating lower h2 estimates. Our work illustrates the huge potential of RAD-sequencing for estimating GRM-based heritability in virtually any natural population.

Genome-Scale Metabolic Model of a Microbial Cell Factory (Brevibacillus thermoruber 423) with Multi-Industry Potentials for Exopolysaccharide Production.

Brevibacillus thermoruber 423 is a thermophilic bacterium capable of producing high levels of exopolysaccharide (EPS) that has broad applications in nutrition, feed, cosmetics, pharmaceutical, and chemical industries, not to mention in health and bionanotechnology sectors. EPS is a natural, nontoxic, and biodegradable polymer of sugar residues and plays pivotal roles in cell-to-cell interactions, adhesion, biofilm formation, and protection of cell against environmental extremes. This bacterium is a thermophilic EPS producer while exceeding other thermophilic producers by virtue of high level of polymer synthesis. Recently, B. thermoruber 423 was noted for relevance to multiple industry sectors because of its capacity to use xylose, and produce EPS, isoprenoids, ethanol/butanol, lipases, proteases, cellulase, and glucoamylase enzymes as well as its resistance to arsenic. A key step in understanding EPS production with a systems-based approach is the knowledge of microbial genome sequence. To speed biotechnology and industrial applications, this study reports on a genome-scale metabolic model (GSMM) of B. thermoruber 423, constructed using the recently available high-quality genome sequence that we have subsequently validated using physiological data on batch growth and EPS production on seven different carbon sources. The model developed contains 1454 reactions (of which 1127 are assigned an enzyme commission number) and 1410 metabolites from 925 genes. This GSMM offers the promise to enable and accelerate further systems biology and industrial scale studies, not to mention the ability to calculate metabolic flux distribution in large networks and multiomic data integration.

Draft genome sequence and detailed characterization of biofuel production by oleaginous microalga Scenedesmus quadricauda LWG002611

BackgroundDue to scarcity of fossil fuel, the importance of alternative energy sources is ever increasing. The oleaginous microalgae have demonstrated their potential as an alternative source of energy, but have not achieved commercialization owing to some biological and technical inefficiency. Modern methods of recombinant strain development for improved efficacy are suffering due to inadequate knowledge of genome and limited molecular tools available for their manipulation.ResultsIn the present study, microalga Scenedesmus quadricauda LWG002611 was selected as the preferred organism for lipid production as it contained high biomass (0.37 g L−1 day−1) and lipid (102 mg L−1 day−1), compared to other oleaginous algae examined in the present study as well as earlier reports. It possessed suitable biodiesel properties as per the range defined by the European biodiesel standard EN14214 and petro-diesel standard EN590:2013. To investigate the potential of S. quadricauda LWG002611 in details, the genome of the organism was assembled and annotated. This was the first genome sequencing and assembly of S. quadricauda, which predicted a genome size of 65.35 Mb with 13,514 genes identified by de novo and 16,739 genes identified by reference guided annotation. Comparative genomics revealed that it belongs to class Chlorophyceae and order Sphaeropleales. Further, small subunit ribosomal RNA gene (18S rRNA) sequencing was carried out to confirm its molecular identification. S. quadricauda LWG002611 exhibited higher number of genes related to major activities compared to other potential algae reported earlier with a total of 283 genes identified in lipid metabolism. Metabolic pathways were reconstructed and multiple gene homologs responsible for carbon fixation and triacylglycerol (TAG) biosynthesis pathway were identified to further improve this potential algal strain for biofuel production by metabolic engineering approaches.ConclusionHere we present the first draft genome sequence, genetic characterization and comparative evaluation of S. quadricauda LWG002611 which exhibit high biomass as well as high lipid productivity. The knowledge of genome sequence, reconstructed metabolic pathways and identification of rate-limiting steps in TAG biosynthesis pathway will strengthen the development of molecular tools towards further improving this potentially one of the major algal strains for biofuel production.

Corseq: fast and efficient identification of favoured codons from next generation sequencing reads.

BackgroundOptimization of transgene expression can be achieved by designing coding sequences with the synonymous codon usage of genes which are highly expressed in the host organism. The identification of the so-called “favoured codons” generally requires the access to either the genome or the coding sequences and the availability of expression data.ResultsHere we describe corseq, a fast and reliable software for detecting the favoured codons directly from RNAseq data without prior knowledge of genomic sequence or gene annotation. The presented tool allows the inference of codons that are preferentially used in highly expressed genes while estimating the transcripts abundance by a new kmer based approach. corseq is implemented in Python and runs under any operating system. The software requires the Biopython 1.65 library (or later versions) and is available under the ‘GNU General Public License version 3’ at the project webpage https://sourceforge.net/projects/corseq/files.Conclusioncorseq represents a faster and easy-to-use alternative for the detection of favoured codons in non model organisms.

Preferences for learning different types of genome sequencing results among young breast cancer patients: Role of psychological and clinical factors.

The growing importance of genome sequencing means that patients will increasingly face decisions regarding what results they would like to learn. The present study examined psychological and clinical factors that might affect these preferences. 1,080 women diagnosed with breast cancer at age 40 or younger completed an online survey. We assessed their interest in learning various types of genome sequencing results: risk of preventable disease or unpreventable disease, cancer treatment response, uncertain meaning, risk to relatives' health, and ancestry/physical traits. Multivariable logistic regression was used to examine whether being "very" interested in each result type was associated with clinical factors: BRCA1/2 mutation status, prior genetic testing, family history of breast cancer, and psychological factors: cancer recurrence worry, genetic risk worry, future orientation, health information orientation, and genome sequencing knowledge. The proportion of respondents who were very interested in learning each type of result ranged from 16% to 77%. In all multivariable models, those who were very interested in learning a result type had significantly higher knowledge about sequencing benefits, greater genetic risks worry, and stronger health information orientation compared to those with less interest (p-values < .05). Our findings indicate that high interest in return of various types of genome sequencing results was more closely related to psychological factors. Shared decision-making approaches that increase knowledge about genome sequencing and incorporate patient preferences for health information and learning about genetic risks may help support patients' informed choices about learning different types of sequencing results.

Genomics and epigenomics in rheumatic diseases: what do they provide in terms of diagnosis and disease management?

Most rheumatic diseases are complex or multifactorial entities with pathogeneses that interact with both multiple genetic factors and a high number of diverse environmental factors. Knowledge of the human genome sequence and its diversity among populations has provided a crucial step forward in our understanding of genetic diseases, identifying many genetic loci or genes associated with diverse phenotypes. In general, susceptibility to autoimmunity is associated with multiple risk factors, but the mechanism of the environmental component influence is poorly understood. Studies in twins have demonstrated that genetics do not explain the totality of the pathogenesis of rheumatic diseases. One method of modulating gene expression through environmental effects is via epigenetic modifications. These techniques open a new field for identifying useful new biomarkers and therapeutic targets. In this context, the development of "-omics" techniques is an opportunity to progress in our knowledge of complex diseases, impacting the discovery of new potential biomarkers suitable for their introduction into clinical practice. In this review, we focus on the recent advances in the fields of genomics and epigenomics in rheumatic diseases and their potential to be useful for the diagnosis, follow-up, and treatment of these diseases. The ultimate aim of genomic studies in any human disease is to understand its pathogenesis, thereby enabling the prediction of the evolution of the disease to establish new treatments and address the development of personalized therapies.

Draft Genome Sequences of the Antimicrobial Producers Pseudomonas sp. TAA207 and Pseudomonas sp. TAD18 Isolated from Antarctic Sediments.

We report here the draft genome sequence of the Pseudomonas sp. TAA207 and Pseudomonas sp. TAD18 strains, isolated from Antarctic sediments during a summer campaign near coastal areas of Terra Nova Bay (Antarctica). Genome sequence knowledge allowed the identification of genes associated with the production of bioactive compounds and antibiotic resistance. Furthermore, it will be instrumental for comparative genomics and the fulfillment of both basic and application-oriented investigations.

Mining for viral fragments in methylation enriched sequencing data.

Most next generation sequencing experiments generate more data than is usable for the experimental set up. For example, methyl-CpG binding domain (MBD) affinity purification based sequencing is often used for DNA-methylation profiling, but up to 30% of the sequenced fragments cannot be mapped uniquely to the reference genome. Here we present and evaluate a methodology for the identification of viruses in these otherwise unused paired-end MBD-seq data. Viral detection is accomplished by mapping non-reference alignable reads to a comprehensive set of viral genomes. As viruses play an important role in epigenetics and cancer development, 92 (pre)malignant and benign samples, originating from two different collections of cervical samples and related cell lines, were used in this study. These samples include primary carcinomas (n = 22), low- and high-grade cervical intraepithelial neoplasia (CIN1 and CIN2/3 - n = 2/n = 30) and normal tissue (n = 20), as well as control samples (n = 17). Viruses that were detected include phages, adenoviruses, herpesviridae and HPV. HPV, which causes virtually all cervical cancers, was identified in 95% of the carcinomas, 100% of the CIN2/3 samples, both CIN1 samples and in 55% of the normal samples. Comparing the amount of mapped fragments on HPV for each HPV-infected sample yielded a significant difference between normal samples and carcinomas or CIN2/3 samples (adjusted p-values resp. <10−5, <10−5), reflecting different viral loads and/or methylation degrees in non-normal samples. Fragments originating from different HPV types could be distinguished and were independently validated by PCR-based assays in 71% of the detections. In conclusion, although limited by the a priori knowledge of viral reference genome sequences, the proposed methodology can provide a first confined but substantial insight into the presence, concentration and types of methylated viral sequences in MBD-seq data at low additional cost.

Tracking the sources of blood meals of parasitic arthropods using shotgun proteomics and unidentified tandem mass spectral libraries

Identifying the species on which hematophagous arthropods feed is crucial for studying the factors that affect pathogen distributions and that can aid public health. Here we describe a protocol to identify the species a parasitic arthropod has previously fed upon by identifying the source of the remnants of a previous blood meal via shotgun proteomics and spectral matching. The protocol is a nontargeted approach that uses the entire detected blood proteome for source identification; it does not require a priori knowledge of genome or protein sequences. Instead, reference spectral libraries are compiled from the blood of multiple host species by using SpectraST, which takes ∼4 d; the identification of the species from which a previous blood meal of a hematophagous arthropod was taken is achieved with spectral matching against the reference spectral libraries, which takes approximately another 4 d. This method is robust against random degradation of the blood meal and can identify unknown blood remnants months after the feeding event.

Inference of alternative splicing from RNA-Seq data with probabilistic splice graphs

Motivation: Alternative splicing and other processes that allow for different transcripts to be derived from the same gene are significant forces in the eukaryotic cell. RNA-Seq is a promising technology for analyzing alternative transcripts, as it does not require prior knowledge of transcript structures or genome sequences. However, analysis of RNA-Seq data in the presence of genes with large numbers of alternative transcripts is currently challenging due to efficiency, identifiability and representation issues.Results: We present RNA-Seq models and associated inference algorithms based on the concept of probabilistic splice graphs, which alleviate these issues. We prove that our models are often identifiable and demonstrate that our inference methods for quantification and differential processing detection are efficient and accurate.Availability: Software implementing our methods is available at http://deweylab.biostat.wisc.edu/psginfer.Contact: cdewey@biostat.wisc.eduSupplementary information: Supplementary data are available at Bioinformatics online.

The 25 kDa Subunit of Cleavage Factor Im Is a RNA-Binding Protein That Interacts with the Poly(A) Polymerase in Entamoeba histolytica

In eukaryotes, polyadenylation of pre-mRNA 3´ end is essential for mRNA export, stability and translation. Taking advantage of the knowledge of genomic sequences of Entamoeba histolytica, the protozoan responsible for human amoebiasis, we previously reported the putative polyadenylation machinery of this parasite. Here, we focused on the predicted protein that has the molecular features of the 25 kDa subunit of the Cleavage Factor Im (CFIm25) from other organisms, including the Nudix (nucleoside diphosphate linked to another moiety X) domain, as well as the RNA binding domain and the PAP/PAB interacting region. The recombinant EhCFIm25 protein (rEhCFIm25) was expressed in bacteria and used to generate specific antibodies in rabbit. Subcellular localization assays showed the presence of the endogenous protein in nuclear and cytoplasmic fractions. In RNA electrophoretic mobility shift assays, rEhCFIm25 was able to form specific RNA-protein complexes with the EhPgp5 mRNA 3´ UTR used as probe. In addition, Pull-Down and LC/ESI-MS/MS tandem mass spectrometry assays evidenced that the putative EhCFIm25 was able to interact with the poly(A) polymerase (EhPAP) that is responsible for the synthesis of the poly(A) tail in other eukaryotic cells. By Far-Western experiments, we confirmed the interaction between the putative EhCFIm25 and EhPAP in E. histolytica. Taken altogether, our results showed that the putative EhCFIm25 is a conserved RNA binding protein that interacts with the poly(A) polymerase, another member of the pre-mRNA 3´ end processing machinery in this protozoan parasite.