@article {769,
	title = {Delineation of a Human Mendelian Disorder of the DNA Demethylation Machinery: TET3 Deficiency.},
	journal = {Am J Hum Genet},
	volume = {106},
	year = {2020},
	month = {2020 02 06},
	pages = {234-245},
	abstract = {<p>Germline pathogenic variants in chromatin-modifying enzymes are a common cause of pediatric developmental disorders. These enzymes catalyze reactions that regulate epigenetic inheritance via histone post-translational modifications and DNA methylation. Cytosine methylation (5-methylcytosine [5mC]) of DNA is the quintessential epigenetic mark, yet no human Mendelian disorder of DNA demethylation has yet been delineated. Here, we describe in detail a Mendelian disorder caused by the disruption of DNA demethylation. TET3 is a methylcytosine dioxygenase that initiates DNA demethylation during early zygote formation, embryogenesis, and neuronal differentiation and is intolerant to haploinsufficiency in mice and humans. We identify and characterize 11 cases of human TET3 deficiency in eight families with the common phenotypic features of intellectual disability and/or global developmental delay; hypotonia; autistic traits; movement disorders; growth abnormalities; and facial dysmorphism. Mono-allelic frameshift and nonsense variants in TET3 occur throughout the coding region. Mono-allelic and bi-allelic missense variants localize to conserved residues; all but one such variant occur within the catalytic domain, and most display hypomorphic function in an assay of catalytic activity. TET3 deficiency and other Mendelian disorders of the epigenetic machinery show substantial phenotypic overlap, including features of intellectual disability and abnormal growth, underscoring shared disease mechanisms.</p>},
	keywords = {Adult, Amino Acid Sequence, Autistic Disorder, Child, Child, Preschool, Developmental Disabilities, Dioxygenases, DNA Demethylation, Embryonic Development, Female, Gene Expression Regulation, Developmental, Growth Disorders, Humans, Infant, Male, Middle Aged, Movement Disorders, Pedigree, Protein Conformation, Sequence Homology, Young Adult},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2019.12.007},
	author = {Beck, David B and Petracovici, Ana and He, Chongsheng and Moore, Hannah W and Louie, Raymond J and Ansar, Muhammad and Douzgou, Sofia and Sithambaram, Sivagamy and Cottrell, Trudie and Santos-Cortez, Regie Lyn P and Prijoles, Eloise J and Bend, Renee and Keren, Boris and Mignot, Cyril and Nougues, Marie-Christine and {\~O}unap, Katrin and Reimand, Tiia and Pajusalu, Sander and Zahid, Muhammad and Saqib, Muhammad Arif Nadeem and Buratti, Julien and Seaby, Eleanor G and McWalter, Kirsty and Telegrafi, Aida and Baldridge, Dustin and Shinawi, Marwan and Leal, Suzanne M and Schaefer, G Bradley and Stevenson, Roger E and Banka, Siddharth and Bonasio, Roberto and Fahrner, Jill A}
}
@article {277,
	title = {DIAMUND: direct comparison of genomes to detect mutations.},
	journal = {Hum Mutat},
	volume = {35},
	year = {2014},
	month = {2014 Mar},
	pages = {283-8},
	abstract = {<p>DNA sequencing has become a powerful method to discover the genetic basis of disease. Standard, widely used protocols for analysis usually begin by comparing each individual to the human reference genome. When applied to a set of related individuals, this approach reveals millions of differences, most of which are shared among the individuals and unrelated to the disease being investigated. We have developed a novel algorithm for variant detection, one that compares DNA sequences directly to one another, without aligning them to the reference genome. When used to find de novo mutations in exome sequences from family trios, or to compare normal and diseased samples from the same individual, the new method, direct alignment for mutation discovery (DIAMUND), produces a dramatically smaller list of candidate mutations than previous methods, without losing sensitivity to detect the true cause of a genetic disease. We demonstrate our results on several example cases, including two family trios in which it correctly found the disease-causing variant while excluding thousands of harmless variants that standard methods had identified. </p>},
	keywords = {Algorithms, Computational Biology, Exome, Genetic Loci, Genetic Variation, Genome, Human, Humans, Mutation, Sequence Alignment, Sequence Analysis, DNA, Software},
	issn = {1098-1004},
	doi = {10.1002/humu.22503},
	author = {Salzberg, Steven L and Pertea, Mihaela and Fahrner, Jill A and Sobreira, Nara}
}
