Mutation frequencies<unk>  has established the mutation frequency for<unk>  human<unk> s. The mutation frequency in the<unk><unk>  between generations for humans (parent to child) is about 70 new mutations per generation. An even lower level of variation was found comparing<unk>  in blood cells for a pair of monozygotic (identical twins) 100-year-old centenarians. Only 8 somatic differences were found, though somatic variation occurring in less than 20% of blood cells would be undetected. In the specifically protein coding regions of the human<unk> , it is estimated that there are about 0.35 mutations that would change the protein sequence between parent/child generations (less than one mutated protein per generation). In cancer, mutation frequencies are much higher, due to<unk>  instability. This frequency can further depend on patient age, exposure to DNA damaging agents (such as UV-irradiation or components of tobacco smoke) and the activity/inactivity of DNA repair mechanisms. Furthermore, mutation frequency can vary between cancer types: in germline cells, mutation rates occur at approximately 0.023 mutations per megabase, but this number is much higher in breast cancer (1.18-1.66 somatic mutations per Mb), in lung cancer (17.7) or in melanomas (≈33). Since the haploid human<unk>  consists of approximately 3,200 megabases, this translates into about 74 mutations (mostly in noncoding regions) in germline DNA per generation, but 3,776-5,312 somatic mutations per haploid<unk>  in breast cancer, 56,640 in lung cancer and 105,600 in melanomas. The distribution of somatic mutations across the human<unk>  is very uneven, such that the gene-rich, early-replicating regions receive fewer mutations than gene-poor, late-replicating heterochromatin, likely due to differential DNA repair activity. In particular, the histone modification H3K9me3 is associated with high, and H3K36me3 with low mutation frequencies.<unk> -wide association studies In research,<unk>  can be used in a<unk> -Wide Association Study (GWAS) – a project aiming to determine the genetic variant or variants associated with a disease or some other phenotype. Diagnostic use In 2009, Illumina released its first<unk><unk>  sequencers that were approved for clinical as opposed to research-only use and doctors at academic medical centers began quietly using them to try to diagnose what was wrong with people whom standard approaches had failed to help. In 2009, a team from Stanford led by Euan Ashley performed clinical interpretation of a full human<unk> , that of bioengineer Stephen Quake. In 2010, Ashley’s team reported<unk><unk>  molecular autopsy and in 2011, extended the interpretation framework to a fully sequenced family, the West family, who were the first family to be sequenced on the Illumina platform. The price to sequence a<unk>  at that time was US$19,500, which was billed to the patient but usually paid for out of a research grant; one person at that time had applied for reimbursement from their insurance company. For example, one child had needed around 100 surgeries by the time he was three years old, and his doctor turned to<unk>  to determine the problem; it took a team of around 30 people that included 12 bioinformatics experts, three<unk>  technicians, five physicians, two genetic counsellors and two ethicists to identify a rare mutation in the XIAP that was causing widespread problems. Due to recent cost reductions (see above)<unk>  has become a realistic application in DNA diagnostics. In 2013, the 3Gb-TEST consortium obtained funding from the European Union to prepare the health care system for these innovations in DNA diagnostics. Quality assessment schemes, Health technology assessment and guidelines have to be in place. The 3Gb-TEST consortium has identified the analysis and interpretation of sequence data as the most complicated step in the diagnostic process. At the Consortium meeting in Athens in September 2014, the Consortium coined the word genotranslation for this crucial step. This step leads to a so-called<unk> port. Guidelines are needed to determine the required content of these reports.<unk> s2People (G2P), an initiative of Brigham and Women's Hospital and Harvard Medical School was created in 2011 to examine the integration of<unk> c<unk>  into clinical care of adults and children. G2P's director, Robert C. Green, had previously led the REVEAL study — Risk EValuation and Education for Alzheimer's Disease – a series of clinical trials exploring patient reactions to the knowledge of their genetic risk for Alzheimer's. Green and a team of researchers launched the BabySeq Project in 2013 to study the ethical and medical consequences of<unk>  an infant's DNA. A second phase, BabySeq2, was funded by NIH in 2021 and is an implementation study that expands this project, planning to enroll 500 infants from diverse families and track the effects of their<unk> c<unk>  on their pediatric care. In 2018, researchers at Rady Children's Institute for<unk> c Medicine in San Diego, CA determined that rapid<unk>  (rWGS) can diagnose genetic disorders in time to change acute medical or surgical management (clinical utility) and improve outcomes in acutely ill infants. The researchers reported a retrospective cohort study of acutely ill inpatient infants in a regional children's hospital from July 2016-March 2017. Forty-two families received rWGS for etiologic diagnosis of genetic disorders. The diagnostic sensitivity of rWGS was 43% (eighteen of 42 infants) and 10% (four of 42 infants) for standard genetic tests (P = .0005). The rate of clinical utility of rWGS (31%, thirteen of 42 infants) was significantly greater than for standard genetic tests (2%, one of 42; P = .0015). Eleven (26%) infants with diagnostic rWGS avoided morbidity, one had a 43% reduction in likelihood of mortality, and one started palliative care. In six of the eleven infants, the changes in management reduced inpatient cost by $800,000-$2,000,000. These findings replicate a prior study of the clinical utility of rWGS in acutely ill inpatient infants, and demonstrate improved outcomes and net healthcare savings. rWGS merits consideration as a first tier test in this setting. Rare variant association study<unk>  studies enable the assessment of associations between complex traits and both coding and noncoding rare variants (minor allele frequency (MAF) < 1%) across the<unk> . Single-variant analyses typically have low power to identify associations with rare variants, and variant set tests have been proposed to jointly test the effects of given sets of multiple rare variants. SNP annotations help to prioritize rare functional variants, and incorporating these annotations can effectively boost the power of genetic association of rare variants analysis of<unk>  studies.
Whole genome sequencing
Microscopic Observation Drug Susceptibility assay
Virtual colony count
Clinical metagenomic sequencing
Functional molecular infection epidemiology
Broth microdilution
Molecular genetics
Yeast expression platform