MDS and MDS/MPN Genomic Subgroups Demonstrate Differential E x Vivo Drug Sensitivity

Background Myelodysplastic syndromes (MDS) and MDS/MPNs are heterogeneous disorders with various combinations of mutations and cytogenetic abnormalities associated with distinct clinical phenotypes, prognosis, and implications for targeted therapies. We previously demonstrated that ex vivo drug sensitivity screening (DSS) identified subgroups of MDS and MDS/MPNs with differing patterns of sensitivity to various drug classes including hypomethylating agents (HMAs), kinase inhibitors, and other small molecules. In this study, we used hierarchical clustering to identify MDS and MDS/MPN genomic subgroups in a large single-center cohort. We then examined associations between these genomic subgroups and ex vivo sensitivity to various drug classes in a cohort of patients with ex vivo DSS. Methods Patients: We identified 294 patients with MDS or MDS/MPNs who had cytogenetics and HemeSTAMP NGS panel (164 genes) performed at Stanford between June 2018 and June 2021. A separate, partially overlapping cohort of 60 patients had ex vivo DSS as described below. Genomic clusters: We used a hierarchical Dirichlet Process (HDP), incorporating mutations and cytogenetics, to identify genomic subgroups. We included pathogenic and likely pathogenic variants with VAF >2% and excluded variants of unknown significance. Ex vivo DSS: Fresh bone marrow aspirates and peripheral blood specimens were RBC-lysed and resuspended in serum-free media with cytokines (Spinner et al, Blood Adv 2020;4(12):2768-78). Samples were plated in 384-well microtiter plates and screened against a collection of up to 74 drugs and 36 drug combinations in triplicate. Specimens were treated for 72 hours and assayed using flow cytometry to assess for blast viability. Statistical analysis: An HDP model was trained on the cohort of 294 patients. To tune the hyperparameters of the model, the log-likelihood of the test data was optimized using cross validation combined with Gaussian Process Bayesian optimization. Inference using the trained model was performed on 60 patients with ex vivo DSS producing a genomic component distribution for each patient. Jensen-Shannon distance was then computed between each pair of patients using their genomic component distributions. Patients were then clustered via agglomerative clustering (average linkage and using a maximum distance cutoff of 0.5) using this distance matrix. Ex vivo sensitivity to drug classes was then compared across clusters using ANOVA on drug sensitivity per drug class averaged over each patient. Results Patient characteristics: Among all 294 patients, the median age was 73 years, 78% had MDS, 16% had CMML, and 6% had other MDS/MPNs. 45% had >5% blasts and 53% had higher risk disease with IPSS-R >3.5. 94% had at least 1 mutation or cytogenetic abnormality with a median of 2 mutations (range 0-7). Among the 60 patients with ex vivo DSS, the median age was 77 years, 82% had MDS, 18% had CMML or other MDS/MPN, 55% had >5% blasts, and 67% had higher risk disease. Genomic subgroups and clusters: An HDP model trained on all 294 patients identified 16 genomic subgroups. Applying these genomic subgroups to the 60 patients with ex vivo DSS, we identified 12 genomic clusters, of which 6 clusters were most common: cluster 0 (enriched for RUNX1/BCOR mutations, N=6), cluster 1 (enriched for TET2/SRSF2/ASXL1, N=13), cluster 3 (enriched for DNMT3A, N=8), cluster 6 (enriched for KRAS/NRAS, N=5), cluster 7 (enriched for STAG2/ASXL1, N=6), and cluster 10 (enriched for TP53/complex cytogenetics, N=5). Associations between genomic clusters and drug sensitivity: Ex vivo drug sensitivity for 60 patients, organized by genomic cluster, is shown in Figure 1A. Ex vivo sensitivity to various drug classes is shown for the most common clusters in Figure 1B. Cluster 10 (enriched for TP53/complex cytogenetics) demonstrated greater ex vivo sensitivity to proteasome inhibitors (p=0.018). In Cluster 6 (enriched for NRAS/KRAS), there was a trend towards greater ex vivo resistance to HMAs and PARP inhibitors (p=0.1 for both comparisons). Conclusions Hierarchical clustering identified distinct genomic subgroups of MDS and MDS/MPNs, which displayed differing ex vivo sensitivity to various drug classes. While the small sample size limits our analysis, these associations between genotype and drug sensitivity phenotype are hypothesis generating and have potential implications for personalized therapy in MDS and MDS/MPNs. Figure 1 Figure 1. Disclosures Spinner: Notable Labs: Honoraria. Schaffert: Notable Labs: Consultancy, Current holder of stock options in a privately-held company, Ended employment in the past 24 months. Santaguida: Notable Labs: Consultancy, Current holder of individual stocks in a privately-held company. Kita: Notable Labs: Current Employment, Current holder of stock options in a privately-held company. Aleshin: Notable Labs: Consultancy. Greenberg: Notable Labs: Research Funding.

Evolution and genomic organization of the insect sHSP gene cluster and coordinate regulation in phenotypic plasticity

Background Conserved syntenic gene complexes are rare in Arthropods and likely only retained due to functional constraint. Numerous sHSPs have been identified in the genomes of insects, some of which are located clustered in close proximity. Previous phylogenetic analyses of these clustered sHSP have been limited to a small number of holometabolous insect species and have not determined the pattern of evolution of the clustered sHSP genes (sHSP-C) in insect or Arthropod lineages. Results Using eight genomes from representative insect orders and three non-insect arthropod genomes we have identified that a syntenic cluster of sHSPs (sHSP-C) is a hallmark of most Arthropod genomes. Using 11 genomes from Hymenopteran species our phylogenetic analyses have refined the evolution of the sHSP-C in Hymenoptera and found that the sHSP-C is order-specific with evidence of birth-and-death evolution in the hymenopteran lineage. Finally we have shown that the honeybee sHSP-C is co-ordinately expressed and is marked by genomic features, including H3K27me3 histone marks consistent with coordinate regulation, during honeybee ovary activation. Conclusions The syntenic sHSP-C is present in most insect genomes, and its conserved coordinate expression and regulation implies that it is an integral genomic component of environmental response in arthropods.

Legal Challenges in Precision Medicine: What Duties Arising From Genetic and Genomic Testing Does a Physician Owe to Patients?

Precision medicine is increasingly incorporated into clinical practice via three primary data conduits: environmental, lifestyle, and genetic data. In this manuscript we take a closer look at the genetic tier of precision medicine. The volume and variety of data provides a more robust picture of health for individual patients and patient populations. However, this increased data may also have an adverse effect by muddling our understanding without the proper pedagogical tools. Patient genomic data can be challenging to work with. Physicians may encounter genetic results which are not fully understood. Genetic tests may also lead to the quandary of linking patients with diseases or disorders where there are no known treatments. Thus, physicians face a unique challenge of establishing the proper scope of their duty to patients when dealing with genomic data. Some of those scope of practice boundaries have been established as a result of litigation, while others remain an open question. In this paper, we map out some of the legal challenges facing the genomic component of precision medicine, both established and some questions requiring additional guidance. If physicians begin to perceive genomic data as falling short in overall benefit to their patients, it may detrimentally impact precision medicine as a whole. Helping to develop guidance for physicians working with patient genomic data can help avoid this fate of faltering confidence.

Genomic Tackling of Human Satellite DNA: Breaking Barriers through Time

(Peri)centromeric repetitive sequences and, more specifically, satellite DNA (satDNA) sequences, constitute a major human genomic component. SatDNA sequences can vary on a large number of features, including nucleotide composition, complexity, and abundance. Several satDNA families have been identified and characterized in the human genome through time, albeit at different speeds. Human satDNA families present a high degree of sub-variability, leading to the definition of various subfamilies with different organization and clustered localization. Evolution of satDNA analysis has enabled the progressive characterization of satDNA features. Despite recent advances in the sequencing of centromeric arrays, comprehensive genomic studies to assess their variability are still required to provide accurate and proportional representation of satDNA (peri)centromeric/acrocentric short arm sequences. Approaches combining multiple techniques have been successfully applied and seem to be the path to follow for generating integrated knowledge in the promising field of human satDNA biology.

­­Evolution and genomic organization of the sHSP gene cluster in Arthropods

Background Conserved syntenic gene complexes are rare in Arthropods and likely only retained due to functional constraint. Numerous sHSPs have been identified in the genomes of insects, some of which are located clustered in close proximity. Previous phylogenetic analyses of these clustered sHSP have been limited to a small number of holometabolous insect species and have not determined the pattern of evolution of the clustered sHSP genes (sHSP-C) in insect or Arthropod lineages. Results Using eight genomes from representative insect orders and three non-insect arthropod genomes we have identified that a syntenic cluster of sHSPs (sHSP-C) is a hallmark of most Arthropod genomes. Using 11 genomes from Hymenopteran species our phylogenetic analyses have refined the evolution of the sHSP-C in Hymenoptera and found that the sHSP-C is order-specific with evidence of birth-and-death evolution in the hymenopteran lineage. Finally we have shown that the honeybee sHSP-C is co-ordinately expressed and is marked by genomic features, including H3K27me3 histone marks consistent with coordinate regulation, during honeybee ovary activation. Conclusions The syntenic sHSP-C is present in most insect genomes, and its conserved coordinate expression and regulation implies that it is an integral genomic component of environmental response in arthropods.

Independent Genomic Sources of Brain Structure and Function

IntroductionThe last decade has seen a surge in well powered genome-wide association studies (GWASs) of complex behavioural traits, disorders, and more recently, of brain structural and functional neuroimaging features. However, the extreme polygenicity of these complex traits makes it difficult to translate the GWAS signal into mechanistic biological insights. We postulate that the covariance of SNP-effects across many brain features, as be captured by latent genomic components of SNP effect sizes. These may partly reflect the concerted multi-locus genomic effects through known molecular pathways and protein-protein interactions. Here, we test the feasibility of a new data-driven method to derive such latent components of genome-wide effects on more than thousand neuroimaging derived traits, and investigate their utility in interpreting the complex biological processes that shape the GWAS signal.MethodsWe downloaded the GWAS summary statistics of 3,143 brain imaging-derived phenotypes (IDPs) from the UK Biobank, provided by the Oxford Brain Imaging Genetics (BIG) Server (Elliott et al. 2018). Probabilistic independent component analysis (ICA) was used to extract two hundred independent genomic components from the matrix of SNP-effect sizes. We qualitatively describe the distribution of the latent component’s loadings in the neuroimaging and the genomic dimensions. Gene-wide statistics were calculated for each genomic component. We tested the genomic component’s enrichment for molecular pathways using MSigDB, and for single-cell RNA-sequencing of adult and foetal brain cells.Results200 components explained 80% of the variance in SNP-effects sizes. Each MRI modality and data processing method projected the imaging data into a clearly distinct cluster in the genomic component embedded space. Among the 200 genomic components, 157 were clearly driven by a single locus, while 39 were highly polygenic. Together, these 39 components were significantly enriched for 2,274 MSigDB gene sets (fully corrected for multiple testing across gene-sets and components). Several components were sensitive to molecular pathways, single cell expression profiles, and brain traits in patterns consistent with knowledge across these biological levels. To illustrate this, we highlight a component that implicated axonal regeneration pathways, which was specifically enriched for gene expression in oligodendrocyte precursors, microglia and astrocytes, and loaded highly on white matter neuroimaging traits. We highlight a second component that implicated synaptic function and neuron projection organization pathways that was specifically enriched for neuronal cell transcriptomes.ConclusionWe propose genomic ICA as a new method to identify latent genetic factors influencing brain structure and function by multimodal MRI. The derived latent genomic dimensions are highly sensitive to known molecular pathways and cell-specific gene expression profiles. Genomic ICA may help to disentangle the many different biological routes by which the genome defines the inter-individual variation of the brain. Future research is aimed at using this method to profile individual subjects’ genomic data along the new latent dimensions and evaluating the utility of these dimensions in stratifying heterogeneous patient populations.

Dark Matter of Primate Genomes: Satellite DNA Repeats and Their Evolutionary Dynamics

A substantial portion of the primate genome is composed of non-coding regions, so-called “dark matter”, which includes an abundance of tandemly repeated sequences called satellite DNA. Collectively known as the satellitome, this genomic component offers exciting evolutionary insights into aspects of primate genome biology that raise new questions and challenge existing paradigms. A complete human reference genome was recently reported with telomere-to-telomere human X chromosome assembly that resolved hundreds of dark regions, encompassing a 3.1 Mb centromeric satellite array that had not been identified previously. With the recent exponential increase in the availability of primate genomes, and the development of modern genomic and bioinformatics tools, extensive growth in our knowledge concerning the structure, function, and evolution of satellite elements is expected. The current state of knowledge on this topic is summarized, highlighting various types of primate-specific satellite repeats to compare their proportions across diverse lineages. Inter- and intraspecific variation of satellite repeats in the primate genome are reviewed. The functional significance of these sequences is discussed by describing how the transcriptional activity of satellite repeats can affect gene expression during different cellular processes. Sex-linked satellites are outlined, together with their respective genomic organization. Mechanisms are proposed whereby satellite repeats might have emerged as novel sequences during different evolutionary phases. Finally, the main challenges that hinder the detection of satellite DNA are outlined and an overview of the latest methodologies to address technological limitations is presented.

Supernumerary B Chromosomes and Plant Genome Changes: A Snapshot of Wild Populations of Aegilops speltoides Tausch (Poaceae, Triticeae)

In various eukaryotes, supernumerary B chromosomes (Bs) are an optional genomic component that affect their integrity and functioning. In the present study, the impact of Bs on the current changes in the genome of goatgrass, Aegilops speltoides, was addressed. Individual plants from contrasting populations with and without Bs were explored using fluorescence in situ hybridization. In parallel, abundances of the Ty1-copia, Ty3-gypsy, and LINE retrotransposons (TEs), and the species-specific Spelt1 tandem repeat (TR) in vegetative and generative spike tissues were estimated by real-time quantitative PCR. The results revealed: (i) ectopic associations between Bs and the regular A chromosomes, and (ii) cell-specific rearrangements of Bs in both mitosis and microgametogenesis. Further, the copy numbers of TEs and TR varied significantly between (iii) genotypes and (iv) different spike tissues in the same plant(s). Finally, (v) in plants with and without Bs from different populations, genomic abundances and/or copy number dynamics of TEs and TR were similar. These findings indicate that fluctuations in TE and TR copy numbers are associated with DNA damage and repair processes during cell proliferation and differentiation, and ectopic recombination is one of the mechanisms by which Bs play a role in genome changes.

A Graph Auto-Encoder for Haplotype Assembly and Viral Quasispecies Reconstruction

Reconstructing components of a genomic mixture from data obtained by means of DNA sequencing is a challenging problem encountered in a variety of applications including single individual haplotyping and studies of viral communities. High-throughput DNA sequencing platforms oversample mixture components to provide massive amounts of reads whose relative positions can be determined by mapping the reads to a known reference genome; assembly of the components, however, requires discovery of the reads' origin – an NP-hard problem that the existing methods struggle to solve with the required level of accuracy. In this paper, we present a learning framework based on a graph auto-encoder designed to exploit structural properties of sequencing data. The algorithm is a neural network which essentially trains to ignore sequencing errors and infers the posterior probabilities of the origin of sequencing reads. Mixture components are then reconstructed by finding consensus of the reads determined to originate from the same genomic component. Results on realistic synthetic as well as experimental data demonstrate that the proposed framework reliably assembles haplotypes and reconstructs viral communities, often significantly outperforming state-of-the-art techniques. Source codes, datasets and supplementary document are available at https://github.com/WuLoli/GAEseq.

New method of complex photo-fluorescent microbiotesting

The biotesting procedure is described, which provides for recording changes in the intensities of elastic light scattering, light absorption and intrinsic photofluorescence of the protein component, as well as determination of concentration and structuring coefficients of the genomic component of samples with viable unicellular test organisms, incubated in a liquid nutrient medium in the presence and absence of various external chemical factors. The results of the analysis using this technique of the antibiotic activity of cations of various metals are presented. It is shown that using this technique can be much more rapid, objectively and comprehensively than using standard visual microbiotesting methods, to assess the effect on reproduction rate, metabolic activity and genome structure of test organisms of samples of various products, wastes, etc.