Extending Grazing and Reducing Stored Feed Needs

Why extend the grazing season? For most livestock producers, extending the grazing season for their animals, or otherwise filling gaps in pasture forage availability to reduce stored feed needs, should be a high priority objective

The Human Gene Mutation Database: 2008 update

The Human Gene Mutation Database (HGMD®) is a comprehensive core collection of germline mutations in nuclear genes that underlie or are associated with human inherited disease. Here, we summarize the history of the database and its current resources. By December 2008, the database contained over 85,000 different lesions detected in 3,253 different genes, with new entries currently accumulating at a rate exceeding 9,000 per annum. Although originally established for the scientific study of mutational mechanisms in human genes, HGMD has since acquired a much broader utility for researchers, physicians, clinicians and genetic counselors as well as for companies specializing in biopharmaceuticals, bioinformatics and personalized genomics. HGMD was first made publicly available in April 1996, and a collaboration was initiated in 2006 between HGMD and BIOBASE GmbH. This cooperative agreement covers the exclusive worldwide marketing of the most up-to-date (subscription) version of HGMD, HGMD Professional, to academic, clinical and commercial users

The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies

The Human Gene Mutation Database (HGMD®) constitutes a comprehensive collection of published germline mutations in nuclear genes that underlie, or are closely associated with human inherited disease. At the time of writing (March 2017), the database contained in excess of 203,000 different gene lesions identified in over 8000 genes manually curated from over 2600 journals. With new mutation entries currently accumulating at a rate exceeding 17,000 per annum, HGMD represents de facto the central unified gene/disease-oriented repository of heritable mutations causing human genetic disease used worldwide by researchers, clinicians, diagnostic laboratories and genetic counsellors, and is an essential tool for the annotation of next-generation sequencing data. The public version of HGMD (http://www.hgmd.org) is freely available to registered users from academic institutions and non-profit organisations whilst the subscription version (HGMD Professional) is available to academic, clinical and commercial users under license via QIAGEN Inc

The Human Gene Mutation Database (HGMD®): optimizing its use in a clinical diagnostic or research setting

The Human Gene Mutation Database (HGMD®) constitutes a comprehensive collection of published germline mutations in nuclear genes that are thought to underlie, or are closely associated with human inherited disease. At the time of writing (June 2020), the database contains in excess of 289,000 different gene lesions identified in over 11,100 genes manually curated from 72,987 articles published in over 3100 peer-reviewed journals. There are primarily two main groups of users who utilise HGMD on a regular basis; research scientists and clinical diagnosticians. This review aims to highlight how to make the most out of HGMD data in each setting

Reversal of graft-versus-host disease with infusion of autologous bone marrow

Graft-versus-host disease (GVHD) remains a major complication of bone marrow transplantation. This report describes reversal of GVHD by infusion of stored recipient bone marrow following combined liver-bone marrow allotransplantation. Graft-versus-host disease developed at the end of the first postoperative week. The skin involvement progressively spread to approximately 80% of the body surface and was not affected by modification of the immunosuppressive treatment. On the 42nd and 43rd postoperative day 1.23 × 108 and 1.6 × 108 autologous bone marrow cells per kg of recipient body weight were infused. The skin rush began to dramatically improve and resolved within 2 wk from the autologous marrow infusion. Autologous bone marrow storage previous to allogeneic bone marrow transplantation for tolerance induction could constitute a safety net in case of occurrence of GVHD. © 1994

MHC-I genotype and tumor mutational burden predict response to immunotherapy.

BackgroundImmune checkpoint blockade (ICB) with antibodies inhibiting cytotoxic T lymphocyte-associated protein-4 (CTLA-4) and programmed cell death protein-1 (PD-1) (or its ligand (PD-L1)) can stimulate immune responses against cancer and have revolutionized the treatment of tumors. The influence of host germline genetics and its interaction with tumor neoantigens remains poorly defined. We sought to determine the interaction between tumor mutational burden (TMB) and the ability of a patient's major histocompatibility complex class I (MHC-I) to efficiently present mutated driver neoantigens in predicting response ICB.MethodsComprehensive genomic profiling was performed on 83 patients with diverse cancers treated with ICB to determine TMB and human leukocyte antigen-I (HLA-I) genotype. The ability of a patient's MHC-I to efficiently present mutated driver neoantigens (defined by the Patient Harmonic-mean Best Rank (PHBR) score (with lower PHBR indicating more efficient presentation)) was calculated for each patient.ResultsThe median progression-free survival (PFS) for PHBR score < 0.5 vs. ≥ 0.5 was 5.1 vs. 4.4 months (P = 0.04). Using a TMB cutoff of 10 mutations/mb, the stable disease > 6 months/partial response/complete response rate, median PFS, and median overall survival (OS) of TMB high/PHBR high vs. TMB high/PHBR low were 43% vs. 78% (P = 0.049), 5.8 vs. 26.8 months (P = 0.03), and 17.2 months vs. not reached (P = 0.23), respectively. These findings were confirmed in an independent validation cohort of 32 patients.ConclusionsPoor presentation of driver mutation neoantigens by MHC-I may explain why some tumors (even with a high TMB) do not respond to ICB

MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing

We have developed a novel machine-learning approach, MutPred Splice, for the identification of coding region substitutions that disrupt pre-mRNA splicing. Applying MutPred Splice to human disease-causing exonic mutations suggests that 16% of mutations causing inherited disease and 10 to 14% of somatic mutations in cancer may disrupt pre-mRNA splicing. For inherited disease, the main mechanism responsible for the splicing defect is splice site loss, whereas for cancer the predominant mechanism of splicing disruption is predicted to be exon skipping via loss of exonic splicing enhancers or gain of exonic splicing silencer elements. MutPred Splice is available at http://mutdb.org/mutpredsplice

Distinct sequence features underlie microdeletions and gross deletions in the human genome

Microdeletions and gross deletions are important causes (~20%) of human inherited disease and their genomic locations are strongly influenced by the local DNA sequence environment. This notwithstanding, no study has systematically examined their underlying generative mechanisms. Here, we obtained 42,098 pathogenic microdeletions and gross deletions from the Human Gene Mutation Database (HGMD) that together form a continuum of germline deletions ranging in size from 1bp to 28,394,429bp. We analyzed the DNA sequence within 1-kb of the breakpoint junctions and found that the frequencies of non-B DNA-forming repeats, GC-content, and the presence of seven of 78 specific sequence motifs in the vicinity of pathogenic deletions correlated with deletion length for deletions of length ≤30 bp. Further, we found that the presence of DR, GQ and STR repeats is important for the formation of longer deletions (>30 bp) but not for the formation of shorter deletions (≤30 bp) whilst significantly (Chi-square test P-value30 bp). We provide evidence to support a functional distinction between microdeletions and gross deletions. Finally, we propose that a deletion length cut-off of 25-30bp may serve as an objective means to functionally distinguish microdeletions from gross deletions