Animal models of Down syndrome (DS), trisomic for human chromosome 21 (HSA21) genes or orthologs, provide insights into better understanding and treatment options. The only existing transchromosomic ...(Tc) mouse DS model, Tc1, carries a HSA21 with over 50 protein coding genes (PCGs) disrupted. Tc1 is mosaic, compromising interpretation of results. Here, we "clone" the 34 MB long arm of HSA21 (HSA21q) as a mouse artificial chromosome (MAC). Through multiple steps of microcell-mediated chromosome transfer, we created a new Tc DS mouse model, Tc(HSA21q;MAC)1Yakaz ("TcMAC21"). TcMAC21 is not mosaic and contains 93% of HSA21q PCGs that are expressed and regulatable. TcMAC21 recapitulates many DS phenotypes including anomalies in heart, craniofacial skeleton and brain, molecular/cellular pathologies, and impairments in learning, memory and synaptic plasticity. TcMAC21 is the most complete genetic mouse model of DS extant and has potential for supporting a wide range of basic and preclinical research.
The sequencing of the human genome and ensuing wave of data generation have brought new light upon the extent and importance of alternative splicing as an RNA regulatory mechanism. Alternative ...splicing could potentially explain the complexity of protein repertoire during evolution, and defects in the splicing mechanism are responsible for diseases as complex as cancer. Among the challenges that rise in light of these discoveries are cataloguing splice variation in the human and other eukaryotic genomes, and identifying and characterizing the splicing regulatory elements that control their expression. Bioinformatics efforts tackling these two questions are just at the beginning. This article is a survey of these methods.
Abstract
Motivation
Current bioinformatics methods to detect changes in gene isoform usage in distinct phenotypes compare the relative expected isoform usage in phenotypes. These statistics model ...differences in isoform usage in normal tissues, which have stable regulation of gene splicing. Pathological conditions, such as cancer, can have broken regulation of splicing that increases the heterogeneity of the expression of splice variants. Inferring events with such differential heterogeneity in gene isoform usage requires new statistical approaches.
Results
We introduce Splice Expression Variability Analysis (SEVA) to model increased heterogeneity of splice variant usage between conditions (e.g. tumor and normal samples). SEVA uses a rank-based multivariate statistic that compares the variability of junction expression profiles within one condition to the variability within another. Simulated data show that SEVA is unique in modeling heterogeneity of gene isoform usage, and benchmark SEVA's performance against EBSeq, DiffSplice and rMATS that model differential isoform usage instead of heterogeneity. We confirm the accuracy of SEVA in identifying known splice variants in head and neck cancer and perform cross-study validation of novel splice variants. A novel comparison of splice variant heterogeneity between subtypes of head and neck cancer demonstrated unanticipated similarity between the heterogeneity of gene isoform usage in HPV-positive and HPV-negative subtypes and anticipated increased heterogeneity among HPV-negative samples with mutations in genes that regulate the splice variant machinery. These results show that SEVA accurately models differential heterogeneity of gene isoform usage from RNA-seq data.
Availability and implementation
SEVA is implemented in the R/Bioconductor package GSReg.
Supplementary information
Supplementary data are available at Bioinformatics online.
Antagonistic pleiotropy is a foundational theory that predicts aging-related diseases are the result of evolved genetic traits conferring advantages early in life. Here we examine CaMKII, a ...pluripotent signaling molecule that contributes to common aging-related diseases, and find that its activation by reactive oxygen species (ROS) was acquired more than half-a-billion years ago along the vertebrate stem lineage. Functional experiments using genetically engineered mice and flies reveal ancestral vertebrates were poised to benefit from the union of ROS and CaMKII, which conferred physiological advantage by allowing ROS to increase intracellular Ca
and activate transcriptional programs important for exercise and immunity. Enhanced sensitivity to the adverse effects of ROS in diseases and aging is thus a trade-off for positive traits that facilitated the early and continued evolutionary success of vertebrates.
Next generation sequencing technologies provide unprecedented power to explore the repertoire of genes and their alternative splice variants, collectively defining the transcriptome of a species in ...great detail. However, assembling the short reads into full-length gene and transcript models presents significant computational challenges. We review current algorithms for assembling transcripts and genes from next generation sequencing reads aligned to a reference genome, and lay out areas for future improvements.
As the amount of genome sequencing data grows, so does the problem of computational gene identification, and in particular, the splicing signals that flank exon borders. Traditional methods for ...identifying splicing signals have been created and optimized using sequences from model organisms, mostly vertebrate and yeast species. However, as genome sequencing extends across the animal kingdom and includes various invertebrate species, the need for mechanisms to recognize splice signals in these organisms increases as well. With that aim in mind, we generated a model for identifying donor and acceptor splice sites that was optimized using sequences from the purple sea urchin, Strongylocentrotus purpuratus. This model was then used to assess the possibility of alternative or cryptic splicing within the highly variable immune response gene family known as 185/333.
A donor splice site model was generated from S. purpuratus sequences that incorporates non-adjacent dependences among positions within the 9 nt splice signal and uses position weight matrices to determine the probability that the site is used for splicing. The Purpuratus model was shown to predict splice signals better than a similar model created from vertebrate sequences. Although the Purpuratus model was able to correctly predict the true splice sites within the 185/333 genes, no evidence for alternative or trans-gene splicing was observed.
The data presented herein describe the first published analyses of echinoderm splice sites and suggest that the previous methods of identifying splice signals that are based largely on vertebrate sequences may be insufficient. Furthermore, alternative or trans-gene splicing does not appear to be acting as a diversification mechanism in the 185/333 gene family.
RNA-seq has revolutionized our ability to survey the cellular transcriptome in great detail. However, while several approaches have been developed, the problem of assembling the short reads into ...full-length transcripts remains challenging.
We developed a novel algorithm and software tool, CLASS (Constraint-based Local Assembly and Selection of Splice variants), for accurately assembling splice variants using local read coverage patterns of RNA-seq reads, contiguity constraints from read pairs and spliced reads, and optionally information about gene structure extracted from cDNA sequence databases. The algorithmic underpinnings of CLASS are: i) a linear program to infer exons, ii) a compact splice graph representation of a gene and its splice variants, and iii) a transcript selection scheme that takes into account contiguity constraints and, where available, knowledge about gene structure.
In comparisons against leading transcript assembly programs, CLASS is more accurate on both simulated and real reads and produces results that are easier to interpret when applied to large scale real data, and therefore is a promising analysis tool for next generation sequencing data.
CLASS is available from http://sourceforge.net/projects/splicebox.
To meet the needs of gene annotation for newly sequenced organisms, optimized spaced seeds can be implemented into cross-species sequence alignment programs to accurately align gene sequences to the ...genome of a related species. So far, seed performance has been tested for comparisons between closely related species, such as human and mouse, or on simulated data. As the number and variety of genomes increases, it becomes desirable to identify a small set of universal seeds that perform optimally or near-optimally on a large range of comparisons.
Using statistical regression methods, we investigate the sensitivity of seeds, in particular good seeds, between four cDNA-to-genome comparisons at different evolutionary distances (human-dog, human-mouse, human-chicken and human-zebrafish), and identify classes of comparisons that show similar seed behavior and therefore can employ the same seed. In addition, we find that with high confidence good seeds for more distant comparisons perform well on closer comparisons, within 98-99% of the optimal seeds, and thus represent universal good seeds.
We show for the first time that optimal and near-optimal seeds for distant species-to-species comparisons are more generally applicable to a wide range of comparisons. This finding will be instrumental in developing practical and user-friendly cDNA-to-genome alignment applications, to aid in the annotation of new model organisms.
Abstract
Motivation
Gene alternative splicing plays an important role in development, tissue specialization and disease and differences in splicing patterns can reveal important factors for ...phenotypic differentiation. While multiple computational methods exist to determine splicing differences, there is a need for user-friendly visualizations that present an intuitive view of the data and work across methods.
Results
We developed a toolkit, Jutils, for visualizing differential splicing events at the intron (splice junction) level. Jutils is method-agnostic, converting individual tools’ output into a unified representation and using it to create visualizations. Jutils creates three types of visualizations, namely heatmaps of absolute and Z-score normalized splice ratios, sashimi plots and Venn diagrams of results from multiple comparisons. Jutils is lightweight, relying solely on the unified data file for visualizations.
Availability and implementation
Jutils is implemented in Python and is available from https://github.com/Splicebox/Jutils.
PDF
