CausalOps -- Towards an Industrial Lifecycle for Causal Probabilistic Graphical Models

Causal probabilistic graph-based models have gained widespread utility, enabling the modeling of cause-and-effect relationships across diverse domains. With their rising adoption in new areas, such as automotive system safety and machine learning, the need for an integrated lifecycle framework akin to DevOps and MLOps has emerged. Currently, a process reference for organizations interested in employing causal engineering is missing. To address this gap and foster widespread industrial adoption, we propose CausalOps, a novel lifecycle framework for causal model development and application. By defining key entities, dependencies, and intermediate artifacts generated during causal engineering, we establish a consistent vocabulary and workflow model. This work contextualizes causal model usage across different stages and stakeholders, outlining a holistic view of creating and maintaining them. CausalOps' aim is to drive the adoption of causal methods in practical applications within interested organizations and the causality community

Systematic Inference of Copy-Number Genotypes from Personal Genome Sequencing Data Reveals Extensive Olfactory Receptor Gene Content Diversity

Copy-number variations (CNVs) are widespread in the human genome, but comprehensive assignments of integer locus copy-numbers (i.e., copy-number genotypes) that, for example, enable discrimination of homozygous from heterozygous CNVs, have remained challenging. Here we present CopySeq, a novel computational approach with an underlying statistical framework that analyzes the depth-of-coverage of high-throughput DNA sequencing reads, and can incorporate paired-end and breakpoint junction analysis based CNV-analysis approaches, to infer locus copy-number genotypes. We benchmarked CopySeq by genotyping 500 chromosome 1 CNV regions in 150 personal genomes sequenced at low-coverage. The assessed copy-number genotypes were highly concordant with our performed qPCR experiments (Pearson correlation coefficient 0.94), and with the published results of two microarray platforms (95–99% concordance). We further demonstrated the utility of CopySeq for analyzing gene regions enriched for segmental duplications by comprehensively inferring copy-number genotypes in the CNV-enriched >800 olfactory receptor (OR) human gene and pseudogene loci. CopySeq revealed that OR loci display an extensive range of locus copy-numbers across individuals, with zero to two copies in some OR loci, and two to nine copies in others. Among genetic variants affecting OR loci we identified deleterious variants including CNVs and SNPs affecting ∼15% and ∼20% of the human OR gene repertoire, respectively, implying that genetic variants with a possible impact on smell perception are widespread. Finally, we found that for several OR loci the reference genome appears to represent a minor-frequency variant, implying a necessary revision of the OR repertoire for future functional studies. CopySeq can ascertain genomic structural variation in specific gene families as well as at a genome-wide scale, where it may enable the quantitative evaluation of CNVs in genome-wide association studies involving high-throughput sequencing

The Baker's Yeast Diploid Genome Is Remarkably Stable in Vegetative Growth and Meiosis

Accurate estimates of mutation rates provide critical information to analyze genome evolution and organism fitness. We used whole-genome DNA sequencing, pulse-field gel electrophoresis, and comparative genome hybridization to determine mutation rates in diploid vegetative and meiotic mutation accumulation lines of Saccharomyces cerevisiae. The vegetative lines underwent only mitotic divisions while the meiotic lines underwent a meiotic cycle every ∼20 vegetative divisions. Similar base substitution rates were estimated for both lines. Given our experimental design, these measures indicated that the meiotic mutation rate is within the range of being equal to zero to being 55-fold higher than the vegetative rate. Mutations detected in vegetative lines were all heterozygous while those in meiotic lines were homozygous. A quantitative analysis of intra-tetrad mating events in the meiotic lines showed that inter-spore mating is primarily responsible for rapidly fixing mutations to homozygosity as well as for removing mutations. We did not observe 1–2 nt insertion/deletion (in-del) mutations in any of the sequenced lines and only one structural variant in a non-telomeric location was found. However, a large number of structural variations in subtelomeric sequences were seen in both vegetative and meiotic lines that did not affect viability. Our results indicate that the diploid yeast nuclear genome is remarkably stable during the vegetative and meiotic cell cycles and support the hypothesis that peripheral regions of chromosomes are more dynamic than gene-rich central sections where structural rearrangements could be deleterious. This work also provides an improved estimate for the mutational load carried by diploid organisms

Relating CNVs to transcriptome data at fine resolution: Assessment of the effect of variant size, type, and overlap with functional regions

Copy-number variants (CNVs) form an abundant class of genetic variation with a presumed widespread impact on individual traits. While recent advances, such as the population-scale sequencing of human genomes, facilitated the fine-scale mapping of CNVs, the phenotypic impact of most of these CNVs remains unclear. By relating copy-number genotypes to transcriptome sequencing data, we have evaluated the impact of CNVs, mapped at fine scale, on gene expression. Based on data from 129 individuals with ancestry from two populations, we identified CNVs associated with the expression of 110 genes, with 13% of the associations involving complex, multiallelic CNVs. Categorization of CNVs according to variant type, size, and gene overlap enabled us to examine the impact of different CNV classes on expression variation. While many small (<4 kb) CNVs were associated with expression variation, overall we observed an enrichment of large duplications and deletions, including large intergenic CNVs, relative to the entire set of expression-associated CNVs. Furthermore, the copy number of genes intersecting with CNVs typically correlated positively with the genes' expression, and also was more strongly correlated with expression than nearby single nucleotide polymorphisms, suggesting a frequent causal role of CNVs in expression quantitative trait loci (eQTLs). We also elucidated unexpected cases of negative correlations between copy number and expression by assessing the CNVs' effects on the structure and regulation of genes. Finally, we examined dosage compensation of transcript levels. Our results suggest that association studies can gain in resolution and power by including fine-scale CNV information, such as those obtained from population-scale sequencing

DELLY: structural variant discovery by integrated paired‐end and split‐read analysis. Bioinformatics 28:i333‐i339.

ABSTRACT Motivation: The discovery of genomic structural variants (SVs) at high sensitivity and specificity is an essential requirement for characterizing naturally occurring variation and for understanding pathological somatic rearrangements in personal genome sequencing data. Of particular interest are integrated methods that accurately identify simple and complex rearrangements in heterogeneous sequencing datasets at single-nucleotide resolution, as an optimal basis for investigating the formation mechanisms and functional consequences of SVs. Results: We have developed an SV discovery method, called DELLY, that integrates short insert paired-ends, long-range matepairs and split-read alignments to accurately delineate genomic rearrangements at single-nucleotide resolution. DELLY is suitable for detecting copy-number variable deletion and tandem duplication events as well as balanced rearrangements such as inversions or reciprocal translocations. DELLY, thus, enables to ascertain the full spectrum of genomic rearrangements, including complex events. On simulated data, DELLY compares favorably to other SV prediction methods across a wide range of sequencing parameters. On real data, DELLY reliably uncovers SVs from the 1000 Genomes Project and cancer genomes, and validation experiments of randomly selected deletion loci show a high specificity

A common microdeletion affecting a hippocampus- and amygdala-specific isoform of tryptophan hydroxylase 2 is not associated with affective disorders

OBJECTIVES: Copy number variants (CNVs) have been shown to affect susceptibility for neuropsychiatric disorders. To date, studies implicating the serotonergic system in complex conditions have just focused on single nucleotide polymorphisms (SNPs). We therefore sought to identify novel common genetic copy number polymorphisms affecting genes of the serotonergic system, and to assess their putative role in bipolar affective disorder (BPAD) and major depressive disorder (MDD). METHODS: A selection of 41 genes of the serotonergic system encoding receptors, the serotonin transporter, metabolic enzymes and chaperones were investigated using a paired-end mapping (PEM) approach on next-generation sequencing data from the pilot project of the 1000 Genomes Project. For association testing, 593 patients with MDD, 1,145 patients with BPAD, and 1,738 healthy controls were included in the study. RESULTS: PEM led to the identification of a microdeletion in the gene encoding tryptophan hydroxylase 2 (TPH2), affecting an amygdala- and hippocampus-specific isoform. It was not associated with BPAD or MDD using a case-control association approach. CONCLUSIONS: We did not find evidence for a role of the TPH2 microdeletion in the pathoetiology of affective disorders. Further studies examining its putative role in behavioral traits regulated by the limbic system are warranted

Synthetic lethality between the cohesin subunits STAG1 and STAG2 in diverse cancer contexts

Recent genome analyses have identified recurrent mutations in the cohesin complex in a wide range of human cancers. Here we demonstrate that the most frequently mutated subunit of the cohesin complex, STAG2, displays a strong synthetic lethal interaction with its paralog STAG1. Mechanistically, STAG1 loss abrogates sister chromatid cohesion in STAG2 mutated but not in wild-type cells leading to mitotic catastrophe, defective cell division and apoptosis. STAG1 inactivation inhibits the proliferation of STAG2 mutated but not wild-type bladder cancer and Ewing sarcoma cell lines. Restoration of STAG2 expression in a mutated bladder cancer model alleviates the dependency on STAG1. Thus, STAG1 and STAG2 support sister chromatid cohesion to redundantly ensure cell survival. STAG1 represents a vulnerability of cancer cells carrying mutations in the major emerging tumor suppressor STAG2 across different cancer contexts. Exploiting synthetic lethal interactions to target recurrent cohesin mutations in cancer, e.g. by inhibiting STAG1, holds the promise for the development of selective therapeutics.Research in the laboratory of J-MP is funded by the Austrian Science Fund (SFB-F34 and Wittgenstein award Z196-B20) and the Austrian Research Promotion Agency (Headquarter grants FFG-834223 and FFG-852936, Laura Bassi Centre for Optimized Structural Studies grant FFG-840283). Research in the laboratory of JZ was funded by a Starting Grant of the European Research Council (ERC no. 336860) and SFB grant F4710 of the Austrian Science Fund (FWF). Research on Ewing sarcoma in the laboratory of HK was funded by the Austrian Science Fund ERA-Net grant I 1225-B19. Work in the lab of FXR was funded by a grant from Fundación Científica de la Asociación Española Contra el Cáncer, Madrid, Spain. Research in the laboratory of TW is supported by National Institute of Health grant R01CA169345 and an Innovation Grant from Alex’s Lemonade Stand