TMOD-13. IDENTIFYING DRIVERS IN THE CONVERGING SYNTENIC REGIONS OF SPONTANEOUS CANINE AND PEDIATRIC HIGH-GRADE GLIOMA USING IMAGING BASED CRISPR-CAS9 ARRAY SCREEN

Gliomas occur in companion dogs at rates comparable to humans, with short-snouted breeds such as boxers being more susceptible than others. The natural progression of cancer in the immuno-competent host allows companion dogs diagnosed with sporadic glioma as an optimal model for preclinical testing of therapeutic approaches with human relevance, including immunotherapies. We have recently performed comprehensive genomic and epigenetic characterization of glioma in dogs to their human counterparts and found strong convergent evolution – shared somatic mutations and aneuploidies - among syntenic regions, including those of known pediatric glioma drivers, e.g., PDGFRA, MYC, PIK3CA. Here, using arrayed CRISPR-Cas9 imaging based phenotypic screen, we will probe potential oncogenic drivers and tumor suppressor genes within syntenic aneuploidies and thus outline functional versus non-functional heterogeneity of cancer aneuploidy. Specifically, we are conducting arrayed knockout screen (one gene per well) of 400+ genes within syntenic aneuploidies across canine (n=2) and pediatric (n=2) high-grade glioma cell lines. We will first capture images by high-speed confocal imaging system at three time points post-transduction of single guide RNAs (2 per gene) targeting each of 400+ genes in their separate wells. Then, using high-throughput image analysis and semi-supervised machine learning methods, we will measure well-based phenotypic features (viability, growth, and morphology) from these images. Genes will be ranked per cross-validated predicted probability in yielding either proliferating or slow-growing cell type based on learned phenotypic features using image data of knockout cells from and across wells. The top ranked genes will then be linked to oncogenes and tumor suppressors based on pathway and ontology analysis. We expect that we will see convergence of the most impactful molecular abnormalities (based on their knockout phenotypes) on mechanisms or candidate signaling pathways for the development of new drugs and repurposing of existing drugs for kids and dogs with high-grade glioma.

A fast, general synteny detection engine

The increasingly widespread availability of genomic data has created a growing need for fast, sensitive and scalable comparative analysis methods. A key aspect of comparative genomic analysis is the study of synteny, co localized gene clusters shared among genomes due to descent from common ancestors. Synteny can provide unique insight into the origin, function, and evolution of genome architectures, but methods to identify syntenic patterns in genomic datasets are often inflexible and slow, and use diverse definitions of what counts as likely synteny. Moreover, the reliable identification of putatively syntenic regions (i.e., whether they are truly indicative of homology) with different lengths and signal to noise ratios can be difficult to quantify. Here, we present Mology, a fast, flexible, alignment-free, nonparametric method to detect regions of syntenic elements among genomes or other datasets. The core algorithm operates on consecutive, rank-ordered elements, which could be genes, operons, motifs, sequence fragments, or any other orderable element. It is agnostic to the physical distance between distinct elements and also to directionality and order within syntenic regions, although such considerations can be addressed post hoc. We describe the underlying statistical theory behind our analysis method, and employ a Monte Carlo approach to estimate the false positive rate and positive predictive values for putative syntenic regions. We also evaluate how varying amounts of noise affect recovery of true syntenic regions among Saccharomycetaceae yeast genomes with up to ~100 million years of divergence. We discuss different strategies for recursive application of our method on syntenic regions with sparser signal than considered here, as well as the general applicability of the core algorithm.

Maximum Parsimony Reconciliation in the DTLOR Model

Background: Analyses of microbial evolution often use reconciliation methods. However, the standard duplication-transfer-loss (DTL) model does not account for the fact that species trees are often not fully sampled and thus, from the perspective of reconciliation, a gene family may enter the species tree from the outside. Moreover, within the species tree, genes are often rearranged, causing them to move to new syntenic "regions." Results: We extend the DTL model to account for two events that commonly arise in the evolution of microbes: evolution occurring outside the sampled species tree and changes in the syntenic regions of genes in the genome due to rearrangement. We describe an efficient algorithm for maximum parsimony reconciliation in this new DTLOR model and then show how it can be extended to account for non-binary gene trees. Finally, we describe preliminary experimental results from the integration of our algorithm into the existing xenoGI tool for reconstructing the histories of genomic islands in closely related bacteria. Conclusions: Reconciliation in the DTLOR model can offer new insights into the evolution of microbes that is not currently possible under the DTL model.

Maximum parsimony reconciliation in the DTLOR model

Background Analyses of microbial evolution often use reconciliation methods. However, the standard duplication-transfer-loss (DTL) model does not account for the fact that species trees are often not fully sampled and thus, from the perspective of reconciliation, a gene family may enter the species tree from the outside. Moreover, within the genome, genes are often rearranged, causing them to move to new syntenic regions. Results We extend the DTL model to account for two events that commonly arise in the evolution of microbes: origin of a gene from outside the sampled species tree and rearrangement of gene syntenic regions. We describe an efficient algorithm for maximum parsimony reconciliation in this new DTLOR model and then show how it can be extended to account for non-binary gene trees to handle uncertainty in gene tree topologies. Finally, we describe preliminary experimental results from the integration of our algorithm into the existing xenoGI tool for reconstructing the histories of genomic islands in closely related bacteria. Conclusions Reconciliation in the DTLOR model can offer new insights into the evolution of microbes that is not currently possible under the DTL model.

Chromosome Distribution of Highly Conserved Tandemly Arranged Repetitive DNAs in the Siberian Sturgeon (Acipenser baerii)

Polyploid genomes present a challenge for cytogenetic and genomic studies, due to the high number of similar size chromosomes and the simultaneous presence of hardly distinguishable paralogous elements. The karyotype of the Siberian sturgeon (Acipenser baerii) contains around 250 chromosomes and is remarkable for the presence of paralogs from two rounds of whole-genome duplications (WGD). In this study, we applied the sterlet-derived acipenserid satDNA-based whole chromosome-specific probes to analyze the Siberian sturgeon karyotype. We demonstrate that the last genome duplication event in the Siberian sturgeon was accompanied by the simultaneous expansion of several repetitive DNA families. Some of the repetitive probes serve as good cytogenetic markers distinguishing paralogous chromosomes and detecting ancestral syntenic regions, which underwent fusions and fissions. The tendency of minisatellite specificity for chromosome size groups previously observed in the sterlet genome is also visible in the Siberian sturgeon. We provide an initial physical chromosome map of the Siberian sturgeon genome supported by molecular markers. The application of these data will facilitate genomic studies in other recent polyploid sturgeon species.

Genetic and comparative mapping of Lupinus luteus L. highlight syntenic regions with major orthologous genes controlling anthracnose resistance and flowering time

Anthracnose susceptibility and ill-adapted flowering time severely affect Lupinus luteus yield, which has high seed protein content, is excellent for sustainable agriculture, but requires genetic improvement to fulfil its potential. This study aimed to (1) develop a genetic map; (2) define collinearity and regions of synteny with Lupinus angustifolius; and (3) map QTLs/candidate genes for anthracnose resistant and flowering time. A few linkage groups/genomic regions tended to be associated with segregation distortion, but did not affect the map. The developed map showed collinearity, and syntenic regions with L. angustifolius. Major QTLs were mapped in syntenic regions. Alleles from the wild parent and cultivar, explained 75% of the phenotypic variance for anthracnose resistance and 83% for early flowering, respectively. Marker sequences flanking the QTLs showed high homology with the Lanr1 gene and Flowering-locus-T of L. angustifolius. This suggests orthologous genes for both traits in the L. luteus genome. The findings are remarkable, revealing the potential to combine early flowering/anthracnose resistant in fulfilling yield capacity in L. luteus, and can be a major strategy in the genetic improvement and usage of this species for sustainable protein production. Allele sequences and PCR-marker tagging of these genes are being applied in marker assisted selection.

Genomic asymmetry of the Brassica napus seed: Epigenetic contributions of DNA methylation and small RNAs to subgenome bias

Polyploidy has predominated the genetic history of the angiosperms, and allopolyploidy is known to have contributed to the vast speciation of flowering plants. Brassica napus, one of the world’s most important oilseeds, is one such polyploid species originating from the interspecific hybridization of Brassica rapa (An) and Brassica oleracea (Cn). Nascent amphidiploids must balance progenitor genomes during reproduction, though the role of epigenetic regulation in subgenome maintenance is unknown. The seed is the pivotal developmental transition into the new sporophytic generation and as such undergoes substantial epigenetic modifications. We investigated subgenome bias between the An and Cn subgenomes as well as across syntenic regions by profiling DNA methylation and siRNAs characteristic of B. napus seed development. DNA methylation and siRNA accumulation were prevalent in the Cn subgenome and most pronounced early during seed morphogenesis. Hypermethylation during seed maturation was most pronounced on non-coding elements, including promoters, repetitive elements, and siRNAs. Methylation on siRNA clusters was more prevalent in syntenic regions of the Cn subgenome and implies selective silencing of genomic loci of the seed. Together, we find compelling evidence for the asymmetrical epigenetic regulation of the An and Cn subgenomes of Brassica napus across seed development.

Genome-wide identification of novel long non-coding RNAs and their possible roles in hypoxic zebrafish brain

Long non-coding RNAs (lncRNAs) are the master regulators of numerous biological processes. Hypoxia causes oxidative stress with severe and detrimental effects on brain function and acts as a critical initiating factor in the pathogenesis of Alzheimer’s disease (AD). From the RNA-Seq in the forebrain (Fb), midbrain (Mb), and hindbrain (Hb) regions of hypoxic and normoxic zebrafish, we identified novel lncRNAs, whose potential cis targets showed involvement in neuronal development and differentiation pathways. Under hypoxia, several lncRNAs and mRNAs were differentially expressed. Co-expression studies indicated that the Fb and Hb regions’ potential lncRNA target genes were involved in the AD pathogenesis. In contrast, those in Mb (cry1b, per1a, cipca) were responsible for regulating circadian rhythm. We identified specific lncRNAs present in the syntenic regions between zebrafish and humans, possibly functionally conserved. We thus identified several conserved lncRNAs as the probable regulators of AD genes (adrb3b, cav1, stat3, bace2, apoeb, psen1, s100b).

SyRI: finding genomic rearrangements and local sequence differences from whole-genome assemblies

Genomic differences range from single nucleotide differences to complex structural variations. Current methods typically annotate sequence differences ranging from SNPs to large indels accurately but do not unravel the full complexity of structural rearrangements, including inversions, translocations, and duplications, where highly similar sequence changes in location, orientation, or copy number. Here, we present SyRI, a pairwise whole-genome comparison tool for chromosome-level assemblies. SyRI starts by finding rearranged regions and then searches for differences in the sequences, which are distinguished for residing in syntenic or rearranged regions. This distinction is important as rearranged regions are inherited differently compared to syntenic regions.