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1.
Am J Med Genet B Neuropsychiatr Genet ; 171(4): 534-45, 2016 06.
Article in English | MEDLINE | ID: mdl-26990047

ABSTRACT

Recent studies show that human-specific LINE1s (L1HS) play a key role in the development of the central nervous system (CNS) and its disorders, and that their transpositions within the human genome are more common than previously thought. Many polymorphic L1HS, that is, present or absent across individuals, are not annotated in the current release of the genome and are customarily termed "non-reference L1s." We developed an analytical workflow to identify L1 polymorphic insertions with next-generation sequencing (NGS) using data from a family in which SZ segregates. Our workflow exploits two independent algorithms to detect non-reference L1 insertions, performs local de novo alignment of the regions harboring predicted L1 insertions and resolves the L1 subfamily designation from the de novo assembled sequence. We found 110 non-reference L1 polymorphic loci exhibiting Mendelian inheritance, the vast majority of which are already reported in dbRIP and/or euL1db, thus, confirming their status as non-reference L1 polymorphic insertions. Four previously undetected L1 polymorphic loci were confirmed by PCR amplification and direct sequencing of the insert. A large fraction of our non-reference L1s is located within the open reading frame of protein-coding genes that belong to pathways already implicated in the pathogenesis of schizophrenia. The finding of these polymorphic variants among SZ offsprings is intriguing and suggestive of putative pathogenic role. Our data show the utility of NGS to uncover L1 polymorphic insertions, a neglected type of genetic variants with the potential to influence the risk to develop schizophrenia like SNVs and CNVs. © 2016 Wiley Periodicals, Inc.


Subject(s)
Long Interspersed Nucleotide Elements , Schizophrenia/genetics , Adult , Female , Genetic Predisposition to Disease , Genomics , High-Throughput Nucleotide Sequencing , Humans , Male , Middle Aged , Mutagenesis, Insertional , Open Reading Frames , Pedigree , Polymorphism, Genetic , Risk Factors , Sequence Analysis, DNA
2.
Mol Cell Biol ; 27(23): 8352-63, 2007 Dec.
Article in English | MEDLINE | ID: mdl-17893322

ABSTRACT

Wnt regulation of gene expression requires binding of LEF/T-cell factor (LEF/TCF) transcription factors to Wnt response elements (WREs) and recruitment of the activator beta-catenin. There are significant differences in the abilities of LEF/TCF family members to regulate Wnt target genes. For example, alternatively spliced isoforms of TCF-1 and TCF-4 with a C-terminal "E" tail are uniquely potent in their activation of LEF1 and CDX1. Here we report that the mechanism responsible for this unique activity is an auxiliary 30-amino-acid DNA interaction motif referred to here as the "cysteine clamp" (or C-clamp). The C-clamp contains invariant cysteine, aromatic, and basic residues, and surface plasmon resonance (SPR) studies with recombinant C-clamp protein showed that it binds double-stranded DNA but not single-stranded DNA or RNA (equilibrium dissociation constant = 16 nM). CASTing (Cyclic Amplification and Selection of Targets) experiments were used to test whether this motif influences WRE recognition. Full-length LEF-1, TCF-1E, and TCF-1E with a mutated C-clamp all bind nearly identical WREs (TYYCTTTGATSTT), showing that the C-clamp does not alter WRE specificity. However, a GC element downstream of the WRE (RCCG) is enriched in wild-type TCF-1E binding sites but not in mutant TCF-1E binding sites. We conclude that the C-clamp is a sequence-specific DNA binding motif. C-clamp mutations destroy the ability of beta-catenin to regulate the LEF1 promoter, and they severely impair the ability of TCF-1 to regulate growth in colon cancer cells. Thus, E-tail isoforms of TCFs utilize two DNA binding activities to access a subset of Wnt targets important for cell growth.


Subject(s)
DNA/metabolism , TCF Transcription Factors/chemistry , TCF Transcription Factors/metabolism , Wnt Proteins/metabolism , Amino Acid Motifs , Amino Acid Sequence , Animals , Base Sequence , COS Cells , Cell Line, Tumor , Cell Proliferation , Chlorocebus aethiops , Colonic Neoplasms/pathology , Conserved Sequence , Cysteine/metabolism , Humans , Lymphoid Enhancer-Binding Factor 1/metabolism , Molecular Sequence Data , Protein Binding , Protein Structure, Tertiary , Response Elements/genetics , Structure-Activity Relationship , Transcriptional Activation/genetics
3.
Brief Bioinform ; 3(3): 296-302, 2002 Sep.
Article in English | MEDLINE | ID: mdl-12230038

ABSTRACT

Bioinformatics research is often difficult to do with commercial software. The Open Source BioPerl, BioPython and Biojava projects provide toolkits with multiple functionality that make it easier to create customised pipelines or analysis. This review briefly compares the quirks of the underlying languages and the functionality, documentation, utility and relative advantages of the Bio counterparts, particularly from the point of view of the beginning biologist programmer.


Subject(s)
Computational Biology , Programming Languages , Software , Computer Systems , Humans , Internet , User-Computer Interface
4.
BMC Bioinformatics ; 3: 8, 2002.
Article in English | MEDLINE | ID: mdl-11882250

ABSTRACT

BACKGROUND: Pattern matching is the core of bioinformatics; it is used in database searching, restriction enzyme mapping, and finding open reading frames. It is done repeatedly over increasingly long sequences, thus codes must be efficient and insensitive to sequence length. Such patterns of interest include simple motifs with IUPAC degeneracies, regular expressions, patterns allowing mismatches, and probability matrices. RESULTS: I describe a small application which allows searching for all the above pattern types individually, which further allows these atomic motifs to be assembled into logical rules for more sophisticated analysis. CONCLUSION: tacg is small, portable, faster and more capable than most alternatives, relatively easy to modify, and freely available in source code.


Subject(s)
Computational Biology/methods , DNA/genetics , Algorithms , Base Composition/genetics , DNA/chemistry , Fuzzy Logic , Software
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