المؤلفون: Lauren M. Sanders, Rahul Chandra, Navid Zebarjadi, Holly C. Beale, A. Geoffrey Lyle, Analiz Rodriguez, Ellen Towle Kephart, Jacob Pfeil, Allison Cheney, Katrina Learned, Rob Currie, Leonid Gitlin, David Vengerov, David Haussler, Sofie R. Salama, Olena M. Vaske

المصدر: Communications Biology, Vol 5, Iss 1, Pp 1-11 (2022)

مصطلحات موضوعية: Biology (General), QH301-705.5

الوصف: Using a support vector machine learning approach and multi-omics data, dysregulation of key cancer driver pathways is revealed in cancer cell lines compared to primary tumors.

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2399-3642Test

الوصول الحر: https://doaj.org/article/ae37f4fd1afe478ab8fe248e3f11b99fTest

المؤلفون: Megan R. Reed, A. Geoffrey Lyle, Annick De Loose, Leena Maddukuri, Katrina Learned, Holly C. Beale, Ellen T. Kephart, Allison Cheney, Anouk van den Bout, Madison P. Lee, Kelsey N. Hundley, Ashley M. Smith, Teresa M. DesRochers, Cecile Rose T. Vibat, Murat Gokden, Sofie Salama, Christopher P. Wardell, Robert L. Eoff, Olena M. Vaske, Analiz Rodriguez

المصدر: Cells, Vol 10, Iss 12, p 3400 (2021)

مصطلحات موضوعية: Li Fraumeni, glioblastoma, precision medicine, organoid, transcriptomics, Cytology, QH573-671

الوصف: Li Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome caused by germline mutations in TP53. TP53 is the most common mutated gene in human cancer, occurring in 30–50% of glioblastomas (GBM). Here, we highlight a precision medicine platform to identify potential targets for a GBM patient with LFS. We used a comparative transcriptomics approach to identify genes that are uniquely overexpressed in the LFS GBM patient relative to a cancer compendium of 12,747 tumor RNA sequencing data sets, including 200 GBMs. STAT1 and STAT2 were identified as being significantly overexpressed in the LFS patient, indicating ruxolitinib, a Janus kinase 1 and 2 inhibitors, as a potential therapy. The LFS patient had the highest level of STAT1 and STAT2 expression in an institutional high-grade glioma cohort of 45 patients, further supporting the cancer compendium results. To empirically validate the comparative transcriptomics pipeline, we used a combination of adherent and organoid cell culture techniques, including ex vivo patient-derived organoids (PDOs) from four patient-derived cell lines, including the LFS patient. STAT1 and STAT2 expression levels in the four patient-derived cells correlated with levels identified in the respective parent tumors. In both adherent and organoid cultures, cells from the LFS patient were among the most sensitive to ruxolitinib compared to patient-derived cells with lower STAT1 and STAT2 expression levels. A spheroid-based drug screening assay (3D-PREDICT) was performed and used to identify further therapeutic targets. Two targeted therapies were selected for the patient of interest and resulted in radiographic disease stability. This manuscript supports the use of comparative transcriptomics to identify personalized therapeutic targets in a functional precision medicine platform for malignant brain tumors.

وصف الملف: electronic resource

العلاقة: https://www.mdpi.com/2073-4409/10/12/3400Test; https://doaj.org/toc/2073-4409Test

الوصول الحر: https://doaj.org/article/9dc85f09d7834fddbaa84d2a1a8e9843Test

المؤلفون: Jacob Pfeil, Lauren M Sanders, Ioannis Anastopoulos, A Geoffrey Lyle, Alana S Weinstein, Yuanqing Xue, Andrew Blair, Holly C Beale, Alex Lee, Stanley G Leung, Phuong T Dinh, Avanthi Tayi Shah, Marcus R Breese, W Patrick Devine, Isabel Bjork, Sofie R Salama, E Alejandro Sweet-Cordero, David Haussler, Olena Morozova Vaske

المصدر: PLoS Computational Biology, Vol 16, Iss 4, p e1007753 (2020)

مصطلحات موضوعية: Biology (General), QH301-705.5

الوصف: Precision oncology has primarily relied on coding mutations as biomarkers of response to therapies. While transcriptome analysis can provide valuable information, incorporation into workflows has been difficult. For example, the relative rather than absolute gene expression level needs to be considered, requiring differential expression analysis across samples. However, expression programs related to the cell-of-origin and tumor microenvironment effects confound the search for cancer-specific expression changes. To address these challenges, we developed an unsupervised clustering approach for discovering differential pathway expression within cancer cohorts using gene expression measurements. The hydra approach uses a Dirichlet process mixture model to automatically detect multimodally distributed genes and expression signatures without the need for matched normal tissue. We demonstrate that the hydra approach is more sensitive than widely-used gene set enrichment approaches for detecting multimodal expression signatures. Application of the hydra analysis framework to small blue round cell tumors (including rhabdomyosarcoma, synovial sarcoma, neuroblastoma, Ewing sarcoma, and osteosarcoma) identified expression signatures associated with changes in the tumor microenvironment. The hydra approach also identified an association between ATRX deletions and elevated immune marker expression in high-risk neuroblastoma. Notably, hydra analysis of all small blue round cell tumors revealed similar subtypes, characterized by changes to infiltrating immune and stromal expression signatures.

العلاقة: https://doi.org/10.1371/journal.pcbi.1007753Test; https://doaj.org/toc/1553-734XTest; https://doaj.org/toc/1553-7358Test; https://doaj.org/article/6b18e66d017444afb3146ec81d8a8f6fTest

الإتاحة: https://doi.org/10.1371/journal.pcbi.1007753Test
https://doaj.org/article/6b18e66d017444afb3146ec81d8a8f6fTest

المؤلفون: Pattra Chun-on, Angela M. Hinchie, Holly C. Beale, Agustin A Gil Silva, Elizabeth Rush, Cindy Sander, Carla J. Connelly, Brittani K.N. Seynnaeve, John M. Kirkwood, Olena M. Vaske, Carol W. Greider, Jonathan K. Alder

المصدر: Science (New York, N.Y.). 378(6620)

مصطلحات موضوعية: Transcriptional Activation, Multidisciplinary, Skin Neoplasms, Telomere-Binding Proteins, Telomere Homeostasis, Telomere, Shelterin Complex, Gene Expression Regulation, Neoplastic, Cell Line, Tumor, Mutation, Humans, Promoter Regions, Genetic, Melanoma, Telomerase

الوصف: Overcoming replicative senescence is an essential step during oncogenesis, and the reactivation of TERT through promoter mutations is a common mechanism. TERT promoter mutations are acquired in about 75% of melanomas but are not sufficient to maintain telomeres, suggesting that additional mutations are required. We identified a cluster of variants in the promoter of ACD encoding the shelterin component TPP1. ACD promoter variants are present in about 5% of cutaneous melanoma and co-occur with TERT promoter mutations. The two most common somatic variants create or modify binding sites for E-twenty-six (ETS) transcription factors, similar to mutations in the TERT promoter. The variants increase the expression of TPP1 and function together with TERT to synergistically lengthen telomeres. Our findings suggest that TPP1 promoter variants collaborate with TERT activation to enhance telomere maintenance and immortalization in melanoma.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::74f3a42bccab9b89e2b0637b2a386a7dTest
https://pubmed.ncbi.nlm.nih.gov/36356143Test

المؤلفون: Benedict Paten, Jordan M. Eizenga, John Vivian, Holly C. Beale, Olena Morozova-Vaske

المصدر: JCO Clin Cancer Inform

مصطلحات موضوعية: 0301 basic medicine, Regulation of gene expression, Gene Expression Profiling, Bayes Theorem, Sample (statistics), General Medicine, Computational biology, Biology, Prognosis, Gene Expression Regulation, Neoplastic, Gene expression profiling, 03 medical and health sciences, Bayes' theorem, 030104 developmental biology, 0302 clinical medicine, Neoplasms, 030220 oncology & carcinogenesis, Original Reports, Outlier, Gene expression, Biomarkers, Tumor, Humans, Bayesian framework, Gene, Algorithms

الوصف: PURPOSE Many antineoplastics are designed to target upregulated genes, but quantifying upregulation in a single patient sample requires an appropriate set of samples for comparison. In cancer, the most natural comparison set is unaffected samples from the matching tissue, but there are often too few available unaffected samples to overcome high intersample variance. Moreover, some cancer samples have misidentified tissues of origin or even composite-tissue phenotypes. Even if an appropriate comparison set can be identified, most differential expression tools are not designed to accommodate comparisons to a single patient sample. METHODS We propose a Bayesian statistical framework for gene expression outlier detection in single samples. Our method uses all available data to produce a consensus background distribution for each gene of interest without requiring the researcher to manually select a comparison set. The consensus distribution can then be used to quantify over- and underexpression. RESULTS We demonstrate this method on both simulated and real gene expression data. We show that it can robustly quantify overexpression, even when the set of comparison samples lacks ideally matched tissue samples. Furthermore, our results show that the method can identify appropriate comparison sets from samples of mixed lineage and rediscover numerous known gene-cancer expression patterns. CONCLUSION This exploratory method is suitable for identifying expression outliers from comparative RNA sequencing (RNA-seq) analysis for individual samples, and Treehouse, a pediatric precision medicine group that leverages RNA-seq to identify potential therapeutic leads for patients, plans to explore this method for processing its pediatric cohort.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7f067d6fbb55e8f80ca62f3beba890dTest
https://doi.org/10.1200/cci.19.00095Test

المؤلفون: Gina D. Mawla, A. Geoffrey Lyle, Ellen T. Kephart, Katrina Learned, Holly C. Beale, Joshua E. Goldford, Olena M. Vaske

المصدر: Cancer Research. 82:LB059-LB059

مصطلحات موضوعية: Cancer Research, Oncology

الوصف: Pediatric high-grade glioma (pHGG) is a highly malignant and poorly understood cancer driven by diverse genetic and epigenetic mechanisms. Here, we use comparative RNA sequencing, outlier analysis, and spectral clustering approaches to analyze transcriptomic data of 1,543 pediatric brain tumor specimens from the UCSC Treehouse Childhood Cancer Initiative (Treehouse) and Open Pediatric Brain Tumor Atlas (OpenPBTA) to identify subpopulations of pHGG patients with characteristic gene expression profiles. We find that approximately half (45%) of pHGG tumors from OpenPBTA exist in three subgroups defined by high outlier-level expression either of: mitochondrially-encoded 12S and 16S rRNAs; genes enriched in the HSF1-mediated heat shock response and activation pathways; or six C/D box snoRNA (SNORD) genes originating from the paternally-expressed SNORD116 locus involved in Prader-Willi syndrome, a complex neurodevelopmental disorder. Interestingly, the same set of HSF1-dependent pathway genes is also significantly upregulated in a subset (~11%) of pHGG tumors from Treehouse, validating this finding in two independent compendia with different transcript isolation strategies (Treehouse, polyA selection; OpenPBTA, ribodepletion). Our work identifies distinct classes of tumors with outlier-level expression of genes with previously unknown roles in pHGG and provides a framework for subtyping tumors by comparative transcriptomics that is adaptable to any cancer type. We are currently investigating the molecular roles of HSF1-response genes and the imprinted SNORD116 gene cluster in pHGG. Our ongoing research into the biomolecular signatures and mechanisms of the three major tumor classes of pHGG as defined in our study will contribute to a greater understanding of pHGG disease manifestation and progression, and will inform strategies of tailored therapeutic interventions for children with this devastating disease. Citation Format: Gina D. Mawla, A. Geoffrey Lyle, Ellen T. Kephart, Katrina Learned, Holly C. Beale, Joshua E. Goldford, Olena M. Vaske. Subtype classification of pediatric high-grade glioma tumors by comparative transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB059.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::56cc8a84daec9ca0c5e52932b040e2bdTest
https://doi.org/10.1158/1538-7445.am2022-lb059Test

المؤلفون: A. Geoffrey Lyle, Jacquelyn M. Roger, Matthew A. Cattle, Katrina Learned, Robert Currie, Sofie R. Salama, Holly C. Beale, Lauren Sanders, John Vivian, Olena M. Vaske, Du Linh Lam, Ellen Kephart, Drew K A Thompson, Isabel Bjork, Jacob Pfeil, David Haussler, Liam T. McKay

المصدر: GigaScience, vol 10, iss 3
GigaScience

مصطلحات موضوعية: depth, AcademicSubjects/SCI02254, unmapped, Health Informatics, Computational biology, exonic, Biology, Deep sequencing, Whole Exome Sequencing, 03 medical and health sciences, 0302 clinical medicine, Neoplasms, Exome Sequencing, Technical Note, Genetics, Humans, RNA-Seq, Child, 030304 developmental biology, Cancer, 0303 health sciences, Sequence Analysis, RNA, Gene Expression Profiling, Human Genome, Reproducibility of Results, High-Throughput Nucleotide Sequencing, sequencing, Pediatric cancer, Computer Science Applications, duplicate, quality, AcademicSubjects/SCI00960, RNA, Sequence Analysis, 030217 neurology & neurosurgery, Biotechnology

الوصف: Background The reproducibility of gene expression measured by RNA sequencing (RNA-Seq) is dependent on the sequencing depth. While unmapped or non-exonic reads do not contribute to gene expression quantification, duplicate reads contribute to the quantification but are not informative for reproducibility. We show that mapped, exonic, non-duplicate (MEND) reads are a useful measure of reproducibility of RNA-Seq datasets used for gene expression analysis. Findings In bulk RNA-Seq datasets from 2,179 tumors in 48 cohorts, the fraction of reads that contribute to the reproducibility of gene expression analysis varies greatly. Unmapped reads constitute 1–77% of all reads (median [IQR], 3% [3–6%]); duplicate reads constitute 3–100% of mapped reads (median [IQR], 27% [13–43%]); and non-exonic reads constitute 4–97% of mapped, non-duplicate reads (median [IQR], 25% [16–37%]). MEND reads constitute 0–79% of total reads (median [IQR], 50% [30–61%]). Conclusions Because not all reads in an RNA-Seq dataset are informative for reproducibility of gene expression measurements and the fraction of reads that are informative varies, we propose reporting a dataset's sequencing depth in MEND reads, which definitively inform the reproducibility of gene expression, rather than total, mapped, or exonic reads. We provide a Docker image containing (i) the existing required tools (RSeQC, sambamba, and samblaster) and (ii) a custom script to calculate MEND reads from RNA-Seq data files. We recommend that all RNA-Seq gene expression experiments, sensitivity studies, and depth recommendations use MEND units for sequencing depth.

وصف الملف: application/pdf

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0c41d1a09b6a7b588df765f9b7c0686Test
https://escholarship.org/uc/item/2fq331n9Test

المؤلفون: Christopher P. Wardell, Robert L. Eoff, Annick De Loose, Sofie R. Salama, Anouk van den Bout, Teresa M. DesRochers, A. Geoffrey Lyle, Murat Gokden, Madison P Lee, Kelsey Hundley, Analiz Rodriguez, Allison Cheney, Katrina Learned, Leena Maddukuri, Olena M. Vaske, Megan R. Reed, Holly C. Beale, Cecile Rose T. Vibat, Ashley M. Smith, Ellen Kephart

المصدر: Cells, Vol 10, Iss 3400, p 3400 (2021)
Cells
Cells; Volume 10; Issue 12; Pages: 3400

مصطلحات موضوعية: Adult, Male, Ruxolitinib, Adolescent, QH301-705.5, precision medicine, organoid, Li Fraumeni, glioblastoma, transcriptomics, Article, Li-Fraumeni Syndrome, Transcriptome, Young Adult, Germline mutation, Glioma, Nitriles, medicine, Humans, RNA-Seq, Biology (General), Child, Germ-Line Mutation, Janus kinase 1, business.industry, Cancer, STAT2 Transcription Factor, Janus Kinase 1, General Medicine, Janus Kinase 2, Precision medicine, medicine.disease, Gene Expression Regulation, Neoplastic, Organoids, Pyrimidines, STAT1 Transcription Factor, Li–Fraumeni syndrome, Cancer research, Pyrazoles, Female, business, medicine.drug

الوصف: Li Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome caused by germline mutations in TP53. TP53 is the most common mutated gene in human cancer, occurring in 30–50% of glioblastomas (GBM). Here, we highlight a precision medicine platform to identify potential targets for a GBM patient with LFS. We used a comparative transcriptomics approach to identify genes that are uniquely overexpressed in the LFS GBM patient relative to a cancer compendium of 12,747 tumor RNA sequencing data sets, including 200 GBMs. STAT1 and STAT2 were identified as being significantly overexpressed in the LFS patient, indicating ruxolitinib, a Janus kinase 1 and 2 inhibitors, as a potential therapy. The LFS patient had the highest level of STAT1 and STAT2 expression in an institutional high-grade glioma cohort of 45 patients, further supporting the cancer compendium results. To empirically validate the comparative transcriptomics pipeline, we used a combination of adherent and organoid cell culture techniques, including ex vivo patient-derived organoids (PDOs) from four patient-derived cell lines, including the LFS patient. STAT1 and STAT2 expression levels in the four patient-derived cells correlated with levels identified in the respective parent tumors. In both adherent and organoid cultures, cells from the LFS patient were among the most sensitive to ruxolitinib compared to patient-derived cells with lower STAT1 and STAT2 expression levels. A spheroid-based drug screening assay (3D-PREDICT) was performed and used to identify further therapeutic targets. Two targeted therapies were selected for the patient of interest and resulted in radiographic disease stability. This manuscript supports the use of comparative transcriptomics to identify personalized therapeutic targets in a functional precision medicine platform for malignant brain tumors.

وصف الملف: application/pdf

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f35e9765ca24ba4181d07b0b2ccd621Test
https://doi.org/10.3390/cells10123400Test

المؤلفون: Phuong T. Dinh, Holly C. Beale, Isabel Bjork, Alana S. Weinstein, Stanley G. Leung, E. Alejandro Sweet-Cordero, David Haussler, Ioannis N. Anastopoulos, Jacob Pfeil, Avanthi Tayi Shah, W. Patrick Devine, Yuanqing Xue, Lauren Sanders, Alex G. Lee, Sofie R. Salama, Olena M. Vaske, Marcus R. Breese, A. Geoffrey Lyle, Andrew Blair

المساهمون: Markowetz, Florian, Pfeil, Jacob [0000-0002-8773-8520], Anastopoulos, Ioannis [0000-0002-6279-0648], Lyle, A Geoffrey [0000-0002-3435-526X], Weinstein, Alana S [0000-0002-1563-9072], Xue, Yuanqing [0000-0003-1892-6787], Beale, Holly C [0000-0003-4091-538X], Dinh, Phuong T [0000-0002-0273-1603], Devine, W Patrick [0000-0003-4634-8830], Salama, Sofie R [0000-0001-6999-7193], Sweet-Cordero, E Alejandro [0000-0002-9787-9351], Vaske, Olena Morozova [0000-0002-1677-417X], Apollo - University of Cambridge Repository

المصدر: PLoS computational biology, vol 16, iss 4
PLoS Computational Biology
PLoS Computational Biology, Vol 16, Iss 4, p e1007753 (2020)

مصطلحات موضوعية: 0301 basic medicine, Hydra, Gene Expression, Pathology and Laboratory Medicine, Pediatrics, Mathematical Sciences, Transcriptome, Neuroblastoma, 0302 clinical medicine, Animal Cells, Models, Neoplasms, Gene expression, Medicine and Health Sciences, Tumor Microenvironment, Blastomas, Cluster Analysis, Biology (General), Precision Medicine, Child, Immune Response, Cancer, Regulation of gene expression, Pediatric, Osteosarcoma, Tumor, Ecology, Sarcomas, Eukaryota, Animal Models, Statistical, Biological Sciences, Synovial sarcoma, Gene Expression Regulation, Neoplastic, Computational Theory and Mathematics, Experimental Organism Systems, Oncology, Modeling and Simulation, Lernaean Hydra, Cellular Types, Research Article, Biotechnology, Pediatric Research Initiative, QH301-705.5, Pediatric Cancer, Bioinformatics, Immune Cells, Ewing Sarcoma, Immunology, Computational biology, Biology, Research and Analysis Methods, 03 medical and health sciences, Cellular and Molecular Neuroscience, Cnidaria, Signs and Symptoms, Rare Diseases, Diagnostic Medicine, Information and Computing Sciences, medicine, Biomarkers, Tumor, Genetics, Animals, Humans, Molecular Biology, Ecology, Evolution, Behavior and Systematics, ATRX, Inflammation, Tumor microenvironment, Neoplastic, Models, Statistical, Gene Expression Profiling, Organisms, Neurosciences, Biology and Life Sciences, Cancers and Neoplasms, Computational Biology, Cell Biology, medicine.disease, Pediatric cancer, Invertebrates, 030104 developmental biology, Orphan Drug, Good Health and Well Being, Gene Expression Regulation, Animal Studies, 030217 neurology & neurosurgery, Biomarkers

الوصف: Precision oncology has primarily relied on coding mutations as biomarkers of response to therapies. While transcriptome analysis can provide valuable information, incorporation into workflows has been difficult. For example, the relative rather than absolute gene expression level needs to be considered, requiring differential expression analysis across samples. However, expression programs related to the cell-of-origin and tumor microenvironment effects confound the search for cancer-specific expression changes. To address these challenges, we developed an unsupervised clustering approach for discovering differential pathway expression within cancer cohorts using gene expression measurements. The hydra approach uses a Dirichlet process mixture model to automatically detect multimodally distributed genes and expression signatures without the need for matched normal tissue. We demonstrate that the hydra approach is more sensitive than widely-used gene set enrichment approaches for detecting multimodal expression signatures. Application of the hydra analysis framework to small blue round cell tumors (including rhabdomyosarcoma, synovial sarcoma, neuroblastoma, Ewing sarcoma, and osteosarcoma) identified expression signatures associated with changes in the tumor microenvironment. The hydra approach also identified an association between ATRX deletions and elevated immune marker expression in high-risk neuroblastoma. Notably, hydra analysis of all small blue round cell tumors revealed similar subtypes, characterized by changes to infiltrating immune and stromal expression signatures.
Author summary Pediatric cancers generally have few somatic mutations. To increase the number of actionable treatment leads, precision pediatric oncology initiatives also analyze tumor gene expression patterns. However, currently available approaches for gene expression data analysis in the clinical setting often use arbitrary thresholds for assessing overexpression and assume gene expression is normally distributed. These methods also rely on reference distributions of related cancer types or normal samples for assessing expression distributions. Often adequate normal samples are not available, and comparing matched cancer cohorts without accounting for subtype expression overestimates the uncertainty in the analysis. We developed a computational framework to automatically detect multimodal expression distributions within well-defined disease populations. Our analysis of small blue round cell tumors (including rhabdomyosarcoma, synovial sarcoma, neuroblastoma, Ewing sarcoma and osteosarcoma) discovered a significant number of multimodally expressed genes. Multimodally expressed genes were associated with proliferative signaling, extracellular matrix organization, and immune signaling pathways across cancer types. Expression signatures correlated with differences in patient outcomes for MYCN non-amplified neuroblastoma, osteosarcoma, and synovial sarcoma. The low mutation rate in pediatric cancers has led some to suggest that pediatric cancers are less immunogenic. However, our analysis suggests that immune infiltration can be identified across small blue round cell tumors. Thus, further research into modulating immune cells for patient benefit may be warranted.

وصف الملف: application/pdf; text/xml; application/zip

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36883de655dc99d8481ddfda8b794f36Test
https://escholarship.org/uc/item/4fp081x6Test

المؤلفون: Jeffrey J Schoenebeck, Sarah A Hutchinson, Alexandra Byers, Holly C Beale, Blake Carrington, Daniel L Faden, Maud Rimbault, Brennan Decker, Jeffrey M Kidd, Raman Sood, Adam R Boyko, John W Fondon, Robert K Wayne, Carlos D Bustamante, Brian Ciruna, Elaine A Ostrander

المصدر: PLoS Genetics, Vol 8, Iss 8, p e1002849 (2012)

مصطلحات موضوعية: Genetics, QH426-470

الوصف: Since the beginnings of domestication, the craniofacial architecture of the domestic dog has morphed and radiated to human whims. By beginning to define the genetic underpinnings of breed skull shapes, we can elucidate mechanisms of morphological diversification while presenting a framework for understanding human cephalic disorders. Using intrabreed association mapping with museum specimen measurements, we show that skull shape is regulated by at least five quantitative trait loci (QTLs). Our detailed analysis using whole-genome sequencing uncovers a missense mutation in BMP3. Validation studies in zebrafish show that Bmp3 function in cranial development is ancient. Our study reveals the causal variant for a canine QTL contributing to a major morphologic trait.

العلاقة: https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22876193/pdf/?tool=EBITest; https://doaj.org/toc/1553-7390Test; https://doaj.org/toc/1553-7404Test; https://doaj.org/article/da65ca9d6a76427a9ce911d89d9ba5caTest

الإتاحة: https://doi.org/10.1371/journal.pgen.1002849Test
https://doaj.org/article/da65ca9d6a76427a9ce911d89d9ba5caTest