Browsing by Subject "RNA, Untranslated"

Now showing 1 - 4 of 4
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    Alpha satellite DNA biology: finding function in the recesses of the genome.
    (Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology, 2018-09) McNulty, Shannon M; Sullivan, Beth A
    Repetitive DNA, formerly referred to by the misnomer "junk DNA," comprises a majority of the human genome. One class of this DNA, alpha satellite, comprises up to 10% of the genome. Alpha satellite is enriched at all human centromere regions and is competent for de novo centromere assembly. Because of the highly repetitive nature of alpha satellite, it has been difficult to achieve genome assemblies at centromeres using traditional next-generation sequencing approaches, and thus, centromeres represent gaps in the current human genome assembly. Moreover, alpha satellite DNA is transcribed into repetitive noncoding RNA and contributes to a large portion of the transcriptome. Recent efforts to characterize these transcripts and their function have uncovered pivotal roles for satellite RNA in genome stability, including silencing "selfish" DNA elements and recruiting centromere and kinetochore proteins. This review will describe the genomic and epigenetic features of alpha satellite DNA, discuss recent findings of noncoding transcripts produced from distinct alpha satellite arrays, and address current progress in the functional understanding of this oft-neglected repetitive sequence. We will discuss unique challenges of studying human satellite DNAs and RNAs and point toward new technologies that will continue to advance our understanding of this largely untapped portion of the genome.
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    Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs.
    (Nature, 2002-12-05) Okazaki, Y; Furuno, M; Kasukawa, T; Adachi, J; Bono, H; Kondo, S; Nikaido, I; Osato, N; Osato, N; Saito, R; Suzuki, H; Yamanaka, I; Kiyosawa, H; Yagi, K; Tomaru, Y; Hasegawa, Y; Nogami, A; Schönbach, C; Gojobori, T; Baldarelli, R; Hill, DP; Bult, C; Hume, DA; Hume, DA; Quackenbush, J; Schriml, LM; Kanapin, A; Matsuda, H; Batalov, S; Beisel, KW; Blake, JA; Bradt, D; Brusic, V; Chothia, C; Corbani, LE; Cousins, S; Dalla, E; Dragani, TA; Fletcher, CF; Forrest, A; Frazer, KS; Gaasterland, T; Gariboldi, M; Gissi, C; Godzik, A; Gough, J; Grimmond, S; Gustincich, S; Hirokawa, N; Jackson, IJ; Jarvis, ED; Kanai, A; Kawaji, H; Kawasawa, Y; Kedzierski, RM; King, BL; Konagaya, A; Kurochkin, IV; Lee, Y; Lenhard, B; Lyons, PA; Maglott, DR; Maltais, L; Marchionni, L; McKenzie, L; Miki, H; Nagashima, T; Numata, K; Okido, T; Pavan, WJ; Pertea, G; Pesole, G; Petrovsky, N; Pillai, R; Pontius, JU; Qi, D; Ramachandran, S; Ravasi, T; Reed, JC; Reed, DJ; Reid, J; Ring, BZ; Ringwald, M; Sandelin, A; Schneider, C; Semple, CAM; Setou, M; Shimada, K; Sultana, R; Takenaka, Y; Taylor, MS; Teasdale, RD; Tomita, M; Verardo, R; Wagner, L; Wahlestedt, C; Wang, Y; Watanabe, Y; Wells, C; Wilming, LG; Wynshaw-Boris, A; Yanagisawa, M; Yang, I; Yang, L; Yuan, Z; Zavolan, M; Zhu, Y; Zimmer, A; Carninci, P; Hayatsu, N; Hirozane-Kishikawa, T; Konno, H; Nakamura, M; Sakazume, N; Sato, K; Shiraki, T; Waki, K; Kawai, J; Aizawa, K; Arakawa, T; Fukuda, S; Hara, A; Hashizume, W; Imotani, K; Ishii, Y; Itoh, M; Kagawa, I; Miyazaki, A; Sakai, K; Sasaki, D; Shibata, K; Shinagawa, A; Yasunishi, A; Yoshino, M; Waterston, R; Lander, ES; Rogers, J; Birney, E; Hayashizaki, Y; FANTOM Consortium; RIKEN Genome Exploration Research Group Phase I & II Team
    Only a small proportion of the mouse genome is transcribed into mature messenger RNA transcripts. There is an international collaborative effort to identify all full-length mRNA transcripts from the mouse, and to ensure that each is represented in a physical collection of clones. Here we report the manual annotation of 60,770 full-length mouse complementary DNA sequences. These are clustered into 33,409 'transcriptional units', contributing 90.1% of a newly established mouse transcriptome database. Of these transcriptional units, 4,258 are new protein-coding and 11,665 are new non-coding messages, indicating that non-coding RNA is a major component of the transcriptome. 41% of all transcriptional units showed evidence of alternative splicing. In protein-coding transcripts, 79% of splice variations altered the protein product. Whole-transcriptome analyses resulted in the identification of 2,431 sense-antisense pairs. The present work, completely supported by physical clones, provides the most comprehensive survey of a mammalian transcriptome so far, and is a valuable resource for functional genomics.
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    Depression in pregnancy, infant birth weight and DNA methylation of imprint regulatory elements.
    (Epigenetics : official journal of the DNA Methylation Society, 2012-07) Liu, Y; Murphy, SK; Murtha, AP; Fuemmeler, BF; Schildkraut, J; Huang, Z; Overcash, F; Kurtzberg, J; Jirtle, R; Iversen, ES; Forman, MR; Hoyo, C
    Depressed mood in pregnancy has been linked to low birth weight (LBW, 4,500 g) infants had 5.9% higher methylation at the PLAGL1 DMR compared with normal birth weight infants. Our findings confirm that severe maternal depressed mood in pregnancy is associated with LBW, and that MEG3 and IGF2 plasticity may play important roles.
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    Quantitative genetics of CTCF binding reveal local sequence effects and different modes of X-chromosome association.
    (PLoS Genet, 2014-11) Ding, Zhihao; Ni, Yunyun; Timmer, Sander W; Lee, Bum-Kyu; Battenhouse, Anna; Louzada, Sandra; Yang, Fengtang; Dunham, Ian; Crawford, Gregory E; Lieb, Jason D; Durbin, Richard; Iyer, Vishwanath R; Birney, Ewan
    Associating genetic variation with quantitative measures of gene regulation offers a way to bridge the gap between genotype and complex phenotypes. In order to identify quantitative trait loci (QTLs) that influence the binding of a transcription factor in humans, we measured binding of the multifunctional transcription and chromatin factor CTCF in 51 HapMap cell lines. We identified thousands of QTLs in which genotype differences were associated with differences in CTCF binding strength, hundreds of them confirmed by directly observable allele-specific binding bias. The majority of QTLs were either within 1 kb of the CTCF binding motif, or in linkage disequilibrium with a variant within 1 kb of the motif. On the X chromosome we observed three classes of binding sites: a minority class bound only to the active copy of the X chromosome, the majority class bound to both the active and inactive X, and a small set of female-specific CTCF sites associated with two non-coding RNA genes. In sum, our data reveal extensive genetic effects on CTCF binding, both direct and indirect, and identify a diversity of patterns of CTCF binding on the X chromosome.