Biology subjects

Keats, J.

Publications and source records attributed to Keats, J..

7 recordsLinked to original sources

bioRxiv2026

Complete mitochondrial genomes of Arizona West Nile virus vectors, Culex quinquefasciatus and Culex tarsalis

Here we report a newly developed method utilizing long-range PCR and long-read Pacific Biosciences HiFi sequencing that successfully obtained two full-length and annotated mitochondrial genomes from Culex quinquefasciatus Say, 1823 and Culex tarsalis Coquillett, 1896, both from Maricopa County, Arizona, USA. Given the substantial burden of West Nile virus in Maricopa County over the past decade, and that these vectors are primarily responsible for spillover to human populations in the county, it is critical to better understand their distribution over time and space. This study begins to approach this need by contributing a novel approach that has resulted in the first West Nile virus vector mitochondrial genomes from Arizona. Our circular Cx. quinquefasciatus mitogenome is 15,587 bp in length, making it the first USA-based mitogenome sequenced through the AT-rich control region. The Cx. tarsalis mitochondrial genome is 16,416 bp long, longer than recently published California-based CTarK1 and Texas-based PQ585801 mitogenomes. The increased length of the Cx. tarsalis mitogenome is a result of a 905 bp insertion in the AT-rich control region, not present in the species publicly available mitogenomes. A maximum likelihood-based phylogenetic reconstruction supports the species designation of these newly-sequenced mitogenomes. The newly developed methodology offers a unique approach to study medically-important vector species around the globe, providing a solution to study populations through pooled vector pathogen surveillance programs.

genomics↗

bioRxiv2025

Longitudinal multi-omic profiling uncovers immune escape and predictors of response in multiple myeloma

Multiple myeloma (MM) is an incurable malignancy of clonally expanded plasma cells shaped by complex interactions with the immune microenvironment. To investigate immune factors driving treatment response and resistance, we conducted multi-omics profiling including CD138neg single-cell RNA sequencing of 243 bone marrow samples from 102 patients (631,226 cells) and CD138pos bulk RNA and whole-genome sequencing from 209 samples. Longitudinal analyses revealed that interferon gamma signaling impairs T cell memory after autologous stem cell transplant, while naive B cell abundance and immunoglobulin diversity correlated with improved progression-free survival (HR = 0.48, p = 2.3e-4). At disease progression, MM cells upregulated cancer-testis antigens and immune effector genes, with concurrent B cell depletion, enrichment of myeloid-derived suppressor cell genes in monocytes, and T cell exhaustion. These findings highlight dynamic immune-tumor interactions, identifying naive B cell reconstitution as a biomarker of durable response, and cancer-testis antigens as potential targets for high-risk disease at progression. Statement of SignificanceLongitudinal profiling of multiple myeloma and the immune microenvironment revealed dynamic immune-tumor interactions across the disease course. Dysfunctional CD8 T cells limited memory formation post-transplant, while naive B recovery associated with sustained treatment response. At progression, cancer-testis antigen expression associated with immunosuppression, revealing novel mechanisms of immune escape.

cancer biology↗

bioRxiv2025

Diploid genome assembly of human fibroblast cell lines enables clone specific variant calling, improved read mapping and accurate phasing

Human cell lines are fundamental tools in biomedical research and are widely used in disease modeling, drug development, and many other domains. Here, we present chromosome-level, phased diploid genome assemblies of two popular human cell lines: the BJ foreskin fibroblast line and the IMR-90 fetal lung fibroblast line. Our high-quality assemblies, generated using long-read and Hi-C sequencing data, reveal substantial structural variation, including more than 50,000 insertions, deletions, duplications, and inversions compared to the recent T2T-CHM13v2.0 reference. Our assemblies provide detailed maps of genetic variation, enabling more accurate variant calling and the ability to phase reads when using newly generated or historical sequencing data on these cell lines or their derivatives. All assemblies and associated data have been made available as a resource for the research community. We envision that diploid genome assembly will become a cornerstone approach for personalized medicine in the near future.

genomics↗

bioRxiv2024

Germline and somatic genetic effects on gene expression and outcome in patients with Multiple Myeloma

Multiple Myeloma (MM) is a hematological malignancy associated with poor prognosis and relapses. MM has a strong inherited component, and while the mutational and transcriptomic landscapes of MM have been characterized extensively, the molecular consequences of germline genetic variation in MM have not been previously explored. Here, we have leveraged matched genotype and expression data from 607 patients to map the germline and somatic regulatory variation in MM. We find that non-coding variation shapes the transcriptional landscape of MM, contributing to overall survival. These regulatory variants alter the binding of transcription factors with known importance in MM, such as IRF4, providing insights into the underlying mechanisms. These data contribute to the increasing understanding of the genetic, molecular, and cellular forces shaping MM risk and outcomes.

genomics↗

bioRxiv2020

Patient Similarity Network of Newly Diagnosed Multiple Myeloma Identifies Patient Sub-groups with Distinct Genetic Features and Clinical Implications

The remarkable genetic heterogeneity of Multiple Myeloma (MM) poses a significant challenge for proper prognostication and clinical management of patients. Accurate dissection of the genetic and molecular landscape of the disease and the robust identification of homogeneous classes of patients are essential steps to reliable risk stratification and the development of novel precision medicine strategies. Here we introduce MM-PSN, the first multi-omics Patient Similarity Network of newly diagnosed MM. MM-PSN has enabled the identification of three broad patient groups and twelve distinct sub-groups defined by five data types generated from genomic and transcriptomic patient profiling of 655 patients. The MM-PSN classification uncovered novel associations between distinct MM hallmarks with significant prognostic implications and allowed further refinement of risk stratification. Our analysis revealed that gain of 1q is the most important single lesion conferring high risk of relapse, and its association with an MMSET translocation is the most significant determinant of poor outcome. We developed a classifier and validated these results in an independent dataset of 559 pts. Our findings suggest that gain of 1q should be incorporated in routine staging systems and risk assessment tools. The MM-PSN classifier is available as a free resource to allow for an easy implementation in most clinical settings.

cancer biology↗

bioRxiv2019

Revealing the impact of recurrent and rare structural variants in multiple myeloma

The landscape of structural variants (SVs) in multiple myeloma remains poorly understood. Here, we performed comprehensive classification and analysis of SVs in multiple myeloma, interrogating a large cohort of 762 patients with whole genome and RNA sequencing. We identified 100 SV hotspots involving 31 new candidate driver genes, including drug targets BCMA (TNFRSF17) and SLAMF7. Complex SVs, including chromothripsis and templated insertions, were present in 61 % of patients and frequently resulted in the simultaneous acquisition of multiple drivers. After accounting for all recurrent events, 63 % of SVs remained unexplained. Intriguingly, these rare SVs were associated with up to 7-fold enrichment for outlier gene expression, indicating that many rare driver SVs remain unrecognized and are likely important in the biology of individual tumors.

genomics↗

bioRxiv2019

Microhomology-mediated end joining drives complex rearrangements and over expression of MYC and PVT1 in multiple myeloma

MYC is a widely acting transcription factor and its deregulation is a crucial event in many human cancers. MYC is important biologically and clinically in multiple myeloma, but the mechanisms underlying its dysregulation are poorly understood. We show that MYC rearrangements are present in 36.0% of newly diagnosed myeloma patients, as detected in the largest set of next generation sequencing data to date (n=1267). Rearrangements were complex and associated with increased expression of MYC and PVT1, but not other genes at 8q24. The highest effect on gene expression was detected in cases where the MYC locus is juxtaposed next to super-enhancers associated with genes such as IGH, IGK, IGL, TXNDC5/BMP6, FAM46C and FOXO3. We identified three hotspots of recombination at 8q24, one of which is enriched for IGH-MYC translocations. Breakpoint analysis indicates primary myeloma rearrangements involving the IGH locus occur through non-homologous end joining, whereas secondary MYC rearrangements occur through microhomology-mediated end joining. This mechanism is different to lymphomas, where non-homologous end joining generates MYC rearrangements. Rearrangements resulted in over-expression of key genes and ChIP-seq identified that HK2, a member of the glucose metabolism pathway, is directly over-expressed through binding of MYC at its promoter.

cancer biology↗