12 results on '"Jones, MC"'
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2. Feedback modulation of cholesterol metabolism by the lipid-responsive non-coding RNA LeXis.
- Author
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Sallam T, Jones MC, Gilliland T, Zhang L, Wu X, Eskin A, Sandhu J, Casero D, Vallim TQ, Hong C, Katz M, Lee R, Whitelegge J, and Tontonoz P
- Subjects
- Animals, Cholesterol biosynthesis, Cholesterol blood, Diet, Western, Dietary Fats pharmacology, Gene Expression Regulation, Heterogeneous-Nuclear Ribonucleoprotein Group C metabolism, Homeostasis drug effects, Ligands, Lipid Metabolism drug effects, Liver drug effects, Liver metabolism, Liver X Receptors, Male, Mice, Mice, Inbred C57BL, Orphan Nuclear Receptors agonists, RNA, Long Noncoding biosynthesis, Signal Transduction, Sterol Regulatory Element Binding Proteins metabolism, Cholesterol metabolism, Homeostasis genetics, Lipid Metabolism genetics, Orphan Nuclear Receptors metabolism, RNA, Long Noncoding genetics
- Abstract
Liver X receptors (LXRs) are transcriptional regulators of cellular and systemic cholesterol homeostasis. Under conditions of excess cholesterol, LXR activation induces the expression of several genes involved in cholesterol efflux, facilitates cholesterol esterification by promoting fatty acid synthesis, and inhibits cholesterol uptake by the low-density lipoprotein receptor. The fact that sterol content is maintained in a narrow range in most cell types and in the organism as a whole suggests that extensive crosstalk between regulatory pathways must exist. However, the molecular mechanisms that integrate LXRs with other lipid metabolic pathways are incompletely understood. Here we show that ligand activation of LXRs in mouse liver not only promotes cholesterol efflux, but also simultaneously inhibits cholesterol biosynthesis. We further identify the long non-coding RNA LeXis as a mediator of this effect. Hepatic LeXis expression is robustly induced in response to a Western diet (high in fat and cholesterol) or to pharmacological LXR activation. Raising or lowering LeXis levels in the liver affects the expression of genes involved in cholesterol biosynthesis and alters the cholesterol levels in the liver and plasma. LeXis interacts with and affects the DNA interactions of RALY, a heterogeneous ribonucleoprotein that acts as a transcriptional cofactor for cholesterol biosynthetic genes in the mouse liver. These findings outline a regulatory role for a non-coding RNA in lipid metabolism and advance our understanding of the mechanisms that coordinate sterol homeostasis.
- Published
- 2016
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3. A shift of thermokarst lakes from carbon sources to sinks during the Holocene epoch.
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Anthony KM, Zimov SA, Grosse G, Jones MC, Anthony PM, Chapin FS 3rd, Finlay JC, Mack MC, Davydov S, Frenzel P, and Frolking S
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- Alaska, Atmosphere chemistry, Canada, Carbon Dioxide analysis, Climate, Freezing, Geologic Sediments chemistry, Greenhouse Effect, History, Ancient, Methane analysis, Siberia, Soil chemistry, Temperature, Carbon Sequestration, Lakes chemistry
- Abstract
Thermokarst lakes formed across vast regions of Siberia and Alaska during the last deglaciation and are thought to be a net source of atmospheric methane and carbon dioxide during the Holocene epoch. However, the same thermokarst lakes can also sequester carbon, and it remains uncertain whether carbon uptake by thermokarst lakes can offset their greenhouse gas emissions. Here we use field observations of Siberian permafrost exposures, radiocarbon dating and spatial analyses to quantify Holocene carbon stocks and fluxes in lake sediments overlying thawed Pleistocene-aged permafrost. We find that carbon accumulation in deep thermokarst-lake sediments since the last deglaciation is about 1.6 times larger than the mass of Pleistocene-aged permafrost carbon released as greenhouse gases when the lakes first formed. Although methane and carbon dioxide emissions following thaw lead to immediate radiative warming, carbon uptake in peat-rich sediments occurs over millennial timescales. We assess thermokarst-lake carbon feedbacks to climate with an atmospheric perturbation model and find that thermokarst basins switched from a net radiative warming to a net cooling climate effect about 5,000 years ago. High rates of Holocene carbon accumulation in 20 lake sediments (47 ± 10 grams of carbon per square metre per year; mean ± standard error) were driven by thermokarst erosion and deposition of terrestrial organic matter, by nutrient release from thawing permafrost that stimulated lake productivity and by slow decomposition in cold, anoxic lake bottoms. When lakes eventually drained, permafrost formation rapidly sequestered sediment carbon. Our estimate of about 160 petagrams of Holocene organic carbon in deep lake basins of Siberia and Alaska increases the circumpolar peat carbon pool estimate for permafrost regions by over 50 per cent (ref. 6). The carbon in perennially frozen drained lake sediments may become vulnerable to mineralization as permafrost disappears, potentially negating the climate stabilization provided by thermokarst lakes during the late Holocene.
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- 2014
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4. Chromosomal rearrangements maintain a polymorphic supergene controlling butterfly mimicry.
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Joron M, Frezal L, Jones RT, Chamberlain NL, Lee SF, Haag CR, Whibley A, Becuwe M, Baxter SW, Ferguson L, Wilkinson PA, Salazar C, Davidson C, Clark R, Quail MA, Beasley H, Glithero R, Lloyd C, Sims S, Jones MC, Rogers J, Jiggins CD, and ffrench-Constant RH
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- Alleles, Animals, Butterflies anatomy & histology, Butterflies physiology, Chromosome Walking, Genetic Linkage genetics, Haplotypes genetics, Molecular Mimicry physiology, Molecular Sequence Data, Multigene Family genetics, Phenotype, Pigmentation genetics, Pigmentation physiology, Wings, Animal anatomy & histology, Wings, Animal metabolism, Wings, Animal physiology, Butterflies genetics, Chromosomes, Insect genetics, Gene Rearrangement genetics, Genes, Insect genetics, Molecular Mimicry genetics, Polymorphism, Genetic genetics
- Abstract
Supergenes are tight clusters of loci that facilitate the co-segregation of adaptive variation, providing integrated control of complex adaptive phenotypes. Polymorphic supergenes, in which specific combinations of traits are maintained within a single population, were first described for 'pin' and 'thrum' floral types in Primula and Fagopyrum, but classic examples are also found in insect mimicry and snail morphology. Understanding the evolutionary mechanisms that generate these co-adapted gene sets, as well as the mode of limiting the production of unfit recombinant forms, remains a substantial challenge. Here we show that individual wing-pattern morphs in the polymorphic mimetic butterfly Heliconius numata are associated with different genomic rearrangements at the supergene locus P. These rearrangements tighten the genetic linkage between at least two colour-pattern loci that are known to recombine in closely related species, with complete suppression of recombination being observed in experimental crosses across a 400-kilobase interval containing at least 18 genes. In natural populations, notable patterns of linkage disequilibrium (LD) are observed across the entire P region. The resulting divergent haplotype clades and inversion breakpoints are found in complete association with wing-pattern morphs. Our results indicate that allelic combinations at known wing-patterning loci have become locked together in a polymorphic rearrangement at the P locus, forming a supergene that acts as a simple switch between complex adaptive phenotypes found in sympatry. These findings highlight how genomic rearrangements can have a central role in the coexistence of adaptive phenotypes involving several genes acting in concert, by locally limiting recombination and gene flow.
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- 2011
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5. A second generation human haplotype map of over 3.1 million SNPs.
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Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, Gibbs RA, Belmont JW, Boudreau A, Hardenbol P, Leal SM, Pasternak S, Wheeler DA, Willis TD, Yu F, Yang H, Zeng C, Gao Y, Hu H, Hu W, Li C, Lin W, Liu S, Pan H, Tang X, Wang J, Wang W, Yu J, Zhang B, Zhang Q, Zhao H, Zhao H, Zhou J, Gabriel SB, Barry R, Blumenstiel B, Camargo A, Defelice M, Faggart M, Goyette M, Gupta S, Moore J, Nguyen H, Onofrio RC, Parkin M, Roy J, Stahl E, Winchester E, Ziaugra L, Altshuler D, Shen Y, Yao Z, Huang W, Chu X, He Y, Jin L, Liu Y, Shen Y, Sun W, Wang H, Wang Y, Wang Y, Xiong X, Xu L, Waye MM, Tsui SK, Xue H, Wong JT, Galver LM, Fan JB, Gunderson K, Murray SS, Oliphant AR, Chee MS, Montpetit A, Chagnon F, Ferretti V, Leboeuf M, Olivier JF, Phillips MS, Roumy S, Sallée C, Verner A, Hudson TJ, Kwok PY, Cai D, Koboldt DC, Miller RD, Pawlikowska L, Taillon-Miller P, Xiao M, Tsui LC, Mak W, Song YQ, Tam PK, Nakamura Y, Kawaguchi T, Kitamoto T, Morizono T, Nagashima A, Ohnishi Y, Sekine A, Tanaka T, Tsunoda T, Deloukas P, Bird CP, Delgado M, Dermitzakis ET, Gwilliam R, Hunt S, Morrison J, Powell D, Stranger BE, Whittaker P, Bentley DR, Daly MJ, de Bakker PI, Barrett J, Chretien YR, Maller J, McCarroll S, Patterson N, Pe'er I, Price A, Purcell S, Richter DJ, Sabeti P, Saxena R, Schaffner SF, Sham PC, Varilly P, Altshuler D, Stein LD, Krishnan L, Smith AV, Tello-Ruiz MK, Thorisson GA, Chakravarti A, Chen PE, Cutler DJ, Kashuk CS, Lin S, Abecasis GR, Guan W, Li Y, Munro HM, Qin ZS, Thomas DJ, McVean G, Auton A, Bottolo L, Cardin N, Eyheramendy S, Freeman C, Marchini J, Myers S, Spencer C, Stephens M, Donnelly P, Cardon LR, Clarke G, Evans DM, Morris AP, Weir BS, Tsunoda T, Mullikin JC, Sherry ST, Feolo M, Skol A, Zhang H, Zeng C, Zhao H, Matsuda I, Fukushima Y, Macer DR, Suda E, Rotimi CN, Adebamowo CA, Ajayi I, Aniagwu T, Marshall PA, Nkwodimmah C, Royal CD, Leppert MF, Dixon M, Peiffer A, Qiu R, Kent A, Kato K, Niikawa N, Adewole IF, Knoppers BM, Foster MW, Clayton EW, Watkin J, Gibbs RA, Belmont JW, Muzny D, Nazareth L, Sodergren E, Weinstock GM, Wheeler DA, Yakub I, Gabriel SB, Onofrio RC, Richter DJ, Ziaugra L, Birren BW, Daly MJ, Altshuler D, Wilson RK, Fulton LL, Rogers J, Burton J, Carter NP, Clee CM, Griffiths M, Jones MC, McLay K, Plumb RW, Ross MT, Sims SK, Willey DL, Chen Z, Han H, Kang L, Godbout M, Wallenburg JC, L'Archevêque P, Bellemare G, Saeki K, Wang H, An D, Fu H, Li Q, Wang Z, Wang R, Holden AL, Brooks LD, McEwen JE, Guyer MS, Wang VO, Peterson JL, Shi M, Spiegel J, Sung LM, Zacharia LF, Collins FS, Kennedy K, Jamieson R, and Stewart J
- Subjects
- Female, Homozygote, Humans, Linkage Disequilibrium genetics, Male, Racial Groups genetics, Recombination, Genetic genetics, Selection, Genetic, Haplotypes genetics, Polymorphism, Single Nucleotide genetics
- Abstract
We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.
- Published
- 2007
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6. Genome-wide detection and characterization of positive selection in human populations.
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Sabeti PC, Varilly P, Fry B, Lohmueller J, Hostetter E, Cotsapas C, Xie X, Byrne EH, McCarroll SA, Gaudet R, Schaffner SF, Lander ES, Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, Gibbs RA, Belmont JW, Boudreau A, Hardenbol P, Leal SM, Pasternak S, Wheeler DA, Willis TD, Yu F, Yang H, Zeng C, Gao Y, Hu H, Hu W, Li C, Lin W, Liu S, Pan H, Tang X, Wang J, Wang W, Yu J, Zhang B, Zhang Q, Zhao H, Zhao H, Zhou J, Gabriel SB, Barry R, Blumenstiel B, Camargo A, Defelice M, Faggart M, Goyette M, Gupta S, Moore J, Nguyen H, Onofrio RC, Parkin M, Roy J, Stahl E, Winchester E, Ziaugra L, Altshuler D, Shen Y, Yao Z, Huang W, Chu X, He Y, Jin L, Liu Y, Shen Y, Sun W, Wang H, Wang Y, Wang Y, Xiong X, Xu L, Waye MM, Tsui SK, Xue H, Wong JT, Galver LM, Fan JB, Gunderson K, Murray SS, Oliphant AR, Chee MS, Montpetit A, Chagnon F, Ferretti V, Leboeuf M, Olivier JF, Phillips MS, Roumy S, Sallée C, Verner A, Hudson TJ, Kwok PY, Cai D, Koboldt DC, Miller RD, Pawlikowska L, Taillon-Miller P, Xiao M, Tsui LC, Mak W, Song YQ, Tam PK, Nakamura Y, Kawaguchi T, Kitamoto T, Morizono T, Nagashima A, Ohnishi Y, Sekine A, Tanaka T, Tsunoda T, Deloukas P, Bird CP, Delgado M, Dermitzakis ET, Gwilliam R, Hunt S, Morrison J, Powell D, Stranger BE, Whittaker P, Bentley DR, Daly MJ, de Bakker PI, Barrett J, Chretien YR, Maller J, McCarroll S, Patterson N, Pe'er I, Price A, Purcell S, Richter DJ, Sabeti P, Saxena R, Schaffner SF, Sham PC, Varilly P, Altshuler D, Stein LD, Krishnan L, Smith AV, Tello-Ruiz MK, Thorisson GA, Chakravarti A, Chen PE, Cutler DJ, Kashuk CS, Lin S, Abecasis GR, Guan W, Li Y, Munro HM, Qin ZS, Thomas DJ, McVean G, Auton A, Bottolo L, Cardin N, Eyheramendy S, Freeman C, Marchini J, Myers S, Spencer C, Stephens M, Donnelly P, Cardon LR, Clarke G, Evans DM, Morris AP, Weir BS, Tsunoda T, Johnson TA, Mullikin JC, Sherry ST, Feolo M, Skol A, Zhang H, Zeng C, Zhao H, Matsuda I, Fukushima Y, Macer DR, Suda E, Rotimi CN, Adebamowo CA, Ajayi I, Aniagwu T, Marshall PA, Nkwodimmah C, Royal CD, Leppert MF, Dixon M, Peiffer A, Qiu R, Kent A, Kato K, Niikawa N, Adewole IF, Knoppers BM, Foster MW, Clayton EW, Watkin J, Gibbs RA, Belmont JW, Muzny D, Nazareth L, Sodergren E, Weinstock GM, Wheeler DA, Yakub I, Gabriel SB, Onofrio RC, Richter DJ, Ziaugra L, Birren BW, Daly MJ, Altshuler D, Wilson RK, Fulton LL, Rogers J, Burton J, Carter NP, Clee CM, Griffiths M, Jones MC, McLay K, Plumb RW, Ross MT, Sims SK, Willey DL, Chen Z, Han H, Kang L, Godbout M, Wallenburg JC, L'Archevêque P, Bellemare G, Saeki K, Wang H, An D, Fu H, Li Q, Wang Z, Wang R, Holden AL, Brooks LD, McEwen JE, Guyer MS, Wang VO, Peterson JL, Shi M, Spiegel J, Sung LM, Zacharia LF, Collins FS, Kennedy K, Jamieson R, and Stewart J
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- Antiporters genetics, Edar Receptor chemistry, Edar Receptor genetics, Gene Frequency, Genetics, Population, Geography, Haplotypes genetics, Humans, Models, Molecular, Polymorphism, Single Nucleotide genetics, Protein Structure, Tertiary, Genome, Human genetics, Selection, Genetic
- Abstract
With the advent of dense maps of human genetic variation, it is now possible to detect positive natural selection across the human genome. Here we report an analysis of over 3 million polymorphisms from the International HapMap Project Phase 2 (HapMap2). We used 'long-range haplotype' methods, which were developed to identify alleles segregating in a population that have undergone recent selection, and we also developed new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population. The analysis reveals more than 300 strong candidate regions. Focusing on the strongest 22 regions, we develop a heuristic for scrutinizing these regions to identify candidate targets of selection. In a complementary analysis, we identify 26 non-synonymous, coding, single nucleotide polymorphisms showing regional evidence of positive selection. Examination of these candidates highlights three cases in which two genes in a common biological process have apparently undergone positive selection in the same population:LARGE and DMD, both related to infection by the Lassa virus, in West Africa;SLC24A5 and SLC45A2, both involved in skin pigmentation, in Europe; and EDAR and EDA2R, both involved in development of hair follicles, in Asia.
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- 2007
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7. The DNA sequence and biological annotation of human chromosome 1.
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Gregory SG, Barlow KF, McLay KE, Kaul R, Swarbreck D, Dunham A, Scott CE, Howe KL, Woodfine K, Spencer CC, Jones MC, Gillson C, Searle S, Zhou Y, Kokocinski F, McDonald L, Evans R, Phillips K, Atkinson A, Cooper R, Jones C, Hall RE, Andrews TD, Lloyd C, Ainscough R, Almeida JP, Ambrose KD, Anderson F, Andrew RW, Ashwell RI, Aubin K, Babbage AK, Bagguley CL, Bailey J, Beasley H, Bethel G, Bird CP, Bray-Allen S, Brown JY, Brown AJ, Buckley D, Burton J, Bye J, Carder C, Chapman JC, Clark SY, Clarke G, Clee C, Cobley V, Collier RE, Corby N, Coville GJ, Davies J, Deadman R, Dunn M, Earthrowl M, Ellington AG, Errington H, Frankish A, Frankland J, French L, Garner P, Garnett J, Gay L, Ghori MR, Gibson R, Gilby LM, Gillett W, Glithero RJ, Grafham DV, Griffiths C, Griffiths-Jones S, Grocock R, Hammond S, Harrison ES, Hart E, Haugen E, Heath PD, Holmes S, Holt K, Howden PJ, Hunt AR, Hunt SE, Hunter G, Isherwood J, James R, Johnson C, Johnson D, Joy A, Kay M, Kershaw JK, Kibukawa M, Kimberley AM, King A, Knights AJ, Lad H, Laird G, Lawlor S, Leongamornlert DA, Lloyd DM, Loveland J, Lovell J, Lush MJ, Lyne R, Martin S, Mashreghi-Mohammadi M, Matthews L, Matthews NS, McLaren S, Milne S, Mistry S, Moore MJ, Nickerson T, O'Dell CN, Oliver K, Palmeiri A, Palmer SA, Parker A, Patel D, Pearce AV, Peck AI, Pelan S, Phelps K, Phillimore BJ, Plumb R, Rajan J, Raymond C, Rouse G, Saenphimmachak C, Sehra HK, Sheridan E, Shownkeen R, Sims S, Skuce CD, Smith M, Steward C, Subramanian S, Sycamore N, Tracey A, Tromans A, Van Helmond Z, Wall M, Wallis JM, White S, Whitehead SL, Wilkinson JE, Willey DL, Williams H, Wilming L, Wray PW, Wu Z, Coulson A, Vaudin M, Sulston JE, Durbin R, Hubbard T, Wooster R, Dunham I, Carter NP, McVean G, Ross MT, Harrow J, Olson MV, Beck S, Rogers J, Bentley DR, Banerjee R, Bryant SP, Burford DC, Burrill WD, Clegg SM, Dhami P, Dovey O, Faulkner LM, Gribble SM, Langford CF, Pandian RD, Porter KM, and Prigmore E
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- Base Sequence, DNA Replication Timing, Disease, Gene Duplication, Genes genetics, Genetic Variation genetics, Genomics, Humans, Molecular Sequence Data, Open Reading Frames genetics, Pseudogenes genetics, Recombination, Genetic genetics, Selection, Genetic, Sequence Analysis, DNA, Chromosomes, Human, Pair 1 genetics
- Abstract
The reference sequence for each human chromosome provides the framework for understanding genome function, variation and evolution. Here we report the finished sequence and biological annotation of human chromosome 1. Chromosome 1 is gene-dense, with 3,141 genes and 991 pseudogenes, and many coding sequences overlap. Rearrangements and mutations of chromosome 1 are prevalent in cancer and many other diseases. Patterns of sequence variation reveal signals of recent selection in specific genes that may contribute to human fitness, and also in regions where no function is evident. Fine-scale recombination occurs in hotspots of varying intensity along the sequence, and is enriched near genes. These and other studies of human biology and disease encoded within chromosome 1 are made possible with the highly accurate annotated sequence, as part of the completed set of chromosome sequences that comprise the reference human genome.
- Published
- 2006
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8. The DNA sequence of the human X chromosome.
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Ross MT, Grafham DV, Coffey AJ, Scherer S, McLay K, Muzny D, Platzer M, Howell GR, Burrows C, Bird CP, Frankish A, Lovell FL, Howe KL, Ashurst JL, Fulton RS, Sudbrak R, Wen G, Jones MC, Hurles ME, Andrews TD, Scott CE, Searle S, Ramser J, Whittaker A, Deadman R, Carter NP, Hunt SE, Chen R, Cree A, Gunaratne P, Havlak P, Hodgson A, Metzker ML, Richards S, Scott G, Steffen D, Sodergren E, Wheeler DA, Worley KC, Ainscough R, Ambrose KD, Ansari-Lari MA, Aradhya S, Ashwell RI, Babbage AK, Bagguley CL, Ballabio A, Banerjee R, Barker GE, Barlow KF, Barrett IP, Bates KN, Beare DM, Beasley H, Beasley O, Beck A, Bethel G, Blechschmidt K, Brady N, Bray-Allen S, Bridgeman AM, Brown AJ, Brown MJ, Bonnin D, Bruford EA, Buhay C, Burch P, Burford D, Burgess J, Burrill W, Burton J, Bye JM, Carder C, Carrel L, Chako J, Chapman JC, Chavez D, Chen E, Chen G, Chen Y, Chen Z, Chinault C, Ciccodicola A, Clark SY, Clarke G, Clee CM, Clegg S, Clerc-Blankenburg K, Clifford K, Cobley V, Cole CG, Conquer JS, Corby N, Connor RE, David R, Davies J, Davis C, Davis J, Delgado O, Deshazo D, Dhami P, Ding Y, Dinh H, Dodsworth S, Draper H, Dugan-Rocha S, Dunham A, Dunn M, Durbin KJ, Dutta I, Eades T, Ellwood M, Emery-Cohen A, Errington H, Evans KL, Faulkner L, Francis F, Frankland J, Fraser AE, Galgoczy P, Gilbert J, Gill R, Glöckner G, Gregory SG, Gribble S, Griffiths C, Grocock R, Gu Y, Gwilliam R, Hamilton C, Hart EA, Hawes A, Heath PD, Heitmann K, Hennig S, Hernandez J, Hinzmann B, Ho S, Hoffs M, Howden PJ, Huckle EJ, Hume J, Hunt PJ, Hunt AR, Isherwood J, Jacob L, Johnson D, Jones S, de Jong PJ, Joseph SS, Keenan S, Kelly S, Kershaw JK, Khan Z, Kioschis P, Klages S, Knights AJ, Kosiura A, Kovar-Smith C, Laird GK, Langford C, Lawlor S, Leversha M, Lewis L, Liu W, Lloyd C, Lloyd DM, Loulseged H, Loveland JE, Lovell JD, Lozado R, Lu J, Lyne R, Ma J, Maheshwari M, Matthews LH, McDowall J, McLaren S, McMurray A, Meidl P, Meitinger T, Milne S, Miner G, Mistry SL, Morgan M, Morris S, Müller I, Mullikin JC, Nguyen N, Nordsiek G, Nyakatura G, O'Dell CN, Okwuonu G, Palmer S, Pandian R, Parker D, Parrish J, Pasternak S, Patel D, Pearce AV, Pearson DM, Pelan SE, Perez L, Porter KM, Ramsey Y, Reichwald K, Rhodes S, Ridler KA, Schlessinger D, Schueler MG, Sehra HK, Shaw-Smith C, Shen H, Sheridan EM, Shownkeen R, Skuce CD, Smith ML, Sotheran EC, Steingruber HE, Steward CA, Storey R, Swann RM, Swarbreck D, Tabor PE, Taudien S, Taylor T, Teague B, Thomas K, Thorpe A, Timms K, Tracey A, Trevanion S, Tromans AC, d'Urso M, Verduzco D, Villasana D, Waldron L, Wall M, Wang Q, Warren J, Warry GL, Wei X, West A, Whitehead SL, Whiteley MN, Wilkinson JE, Willey DL, Williams G, Williams L, Williamson A, Williamson H, Wilming L, Woodmansey RL, Wray PW, Yen J, Zhang J, Zhou J, Zoghbi H, Zorilla S, Buck D, Reinhardt R, Poustka A, Rosenthal A, Lehrach H, Meindl A, Minx PJ, Hillier LW, Willard HF, Wilson RK, Waterston RH, Rice CM, Vaudin M, Coulson A, Nelson DL, Weinstock G, Sulston JE, Durbin R, Hubbard T, Gibbs RA, Beck S, Rogers J, and Bentley DR
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- Animals, Antigens, Neoplasm genetics, Centromere genetics, Chromosomes, Human, Y genetics, Contig Mapping, Crossing Over, Genetic genetics, Dosage Compensation, Genetic, Female, Genetic Linkage genetics, Genetics, Medical, Humans, Male, Polymorphism, Single Nucleotide genetics, RNA genetics, Repetitive Sequences, Nucleic Acid genetics, Sequence Homology, Nucleic Acid, Testis metabolism, Chromosomes, Human, X genetics, Evolution, Molecular, Genomics, Sequence Analysis, DNA
- Abstract
The human X chromosome has a unique biology that was shaped by its evolution as the sex chromosome shared by males and females. We have determined 99.3% of the euchromatic sequence of the X chromosome. Our analysis illustrates the autosomal origin of the mammalian sex chromosomes, the stepwise process that led to the progressive loss of recombination between X and Y, and the extent of subsequent degradation of the Y chromosome. LINE1 repeat elements cover one-third of the X chromosome, with a distribution that is consistent with their proposed role as way stations in the process of X-chromosome inactivation. We found 1,098 genes in the sequence, of which 99 encode proteins expressed in testis and in various tumour types. A disproportionately high number of mendelian diseases are documented for the X chromosome. Of this number, 168 have been explained by mutations in 113 X-linked genes, which in many cases were characterized with the aid of the DNA sequence.
- Published
- 2005
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9. DNA sequence and analysis of human chromosome 9.
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Humphray SJ, Oliver K, Hunt AR, Plumb RW, Loveland JE, Howe KL, Andrews TD, Searle S, Hunt SE, Scott CE, Jones MC, Ainscough R, Almeida JP, Ambrose KD, Ashwell RI, Babbage AK, Babbage S, Bagguley CL, Bailey J, Banerjee R, Barker DJ, Barlow KF, Bates K, Beasley H, Beasley O, Bird CP, Bray-Allen S, Brown AJ, Brown JY, Burford D, Burrill W, Burton J, Carder C, Carter NP, Chapman JC, Chen Y, Clarke G, Clark SY, Clee CM, Clegg S, Collier RE, Corby N, Crosier M, Cummings AT, Davies J, Dhami P, Dunn M, Dutta I, Dyer LW, Earthrowl ME, Faulkner L, Fleming CJ, Frankish A, Frankland JA, French L, Fricker DG, Garner P, Garnett J, Ghori J, Gilbert JG, Glison C, Grafham DV, Gribble S, Griffiths C, Griffiths-Jones S, Grocock R, Guy J, Hall RE, Hammond S, Harley JL, Harrison ES, Hart EA, Heath PD, Henderson CD, Hopkins BL, Howard PJ, Howden PJ, Huckle E, Johnson C, Johnson D, Joy AA, Kay M, Keenan S, Kershaw JK, Kimberley AM, King A, Knights A, Laird GK, Langford C, Lawlor S, Leongamornlert DA, Leversha M, Lloyd C, Lloyd DM, Lovell J, Martin S, Mashreghi-Mohammadi M, Matthews L, McLaren S, McLay KE, McMurray A, Milne S, Nickerson T, Nisbett J, Nordsiek G, Pearce AV, Peck AI, Porter KM, Pandian R, Pelan S, Phillimore B, Povey S, Ramsey Y, Rand V, Scharfe M, Sehra HK, Shownkeen R, Sims SK, Skuce CD, Smith M, Steward CA, Swarbreck D, Sycamore N, Tester J, Thorpe A, Tracey A, Tromans A, Thomas DW, Wall M, Wallis JM, West AP, Whitehead SL, Willey DL, Williams SA, Wilming L, Wray PW, Young L, Ashurst JL, Coulson A, Blöcker H, Durbin R, Sulston JE, Hubbard T, Jackson MJ, Bentley DR, Beck S, Rogers J, and Dunham I
- Subjects
- Base Composition, Euchromatin genetics, Evolution, Molecular, Female, Gene Duplication, Genes, Duplicate genetics, Genetic Variation genetics, Genetics, Medical, Genomics, Heterochromatin genetics, Humans, Male, Neoplasms genetics, Neurodegenerative Diseases genetics, Pseudogenes genetics, Sequence Analysis, DNA, Sex Determination Processes, Chromosomes, Human, Pair 9 genetics, Genes, Physical Chromosome Mapping
- Abstract
Chromosome 9 is highly structurally polymorphic. It contains the largest autosomal block of heterochromatin, which is heteromorphic in 6-8% of humans, whereas pericentric inversions occur in more than 1% of the population. The finished euchromatic sequence of chromosome 9 comprises 109,044,351 base pairs and represents >99.6% of the region. Analysis of the sequence reveals many intra- and interchromosomal duplications, including segmental duplications adjacent to both the centromere and the large heterochromatic block. We have annotated 1,149 genes, including genes implicated in male-to-female sex reversal, cancer and neurodegenerative disease, and 426 pseudogenes. The chromosome contains the largest interferon gene cluster in the human genome. There is also a region of exceptionally high gene and G + C content including genes paralogous to those in the major histocompatibility complex. We have also detected recently duplicated genes that exhibit different rates of sequence divergence, presumably reflecting natural selection.
- Published
- 2004
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10. The DNA sequence and comparative analysis of human chromosome 10.
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Deloukas P, Earthrowl ME, Grafham DV, Rubenfield M, French L, Steward CA, Sims SK, Jones MC, Searle S, Scott C, Howe K, Hunt SE, Andrews TD, Gilbert JG, Swarbreck D, Ashurst JL, Taylor A, Battles J, Bird CP, Ainscough R, Almeida JP, Ashwell RI, Ambrose KD, Babbage AK, Bagguley CL, Bailey J, Banerjee R, Bates K, Beasley H, Bray-Allen S, Brown AJ, Brown JY, Burford DC, Burrill W, Burton J, Cahill P, Camire D, Carter NP, Chapman JC, Clark SY, Clarke G, Clee CM, Clegg S, Corby N, Coulson A, Dhami P, Dutta I, Dunn M, Faulkner L, Frankish A, Frankland JA, Garner P, Garnett J, Gribble S, Griffiths C, Grocock R, Gustafson E, Hammond S, Harley JL, Hart E, Heath PD, Ho TP, Hopkins B, Horne J, Howden PJ, Huckle E, Hynds C, Johnson C, Johnson D, Kana A, Kay M, Kimberley AM, Kershaw JK, Kokkinaki M, Laird GK, Lawlor S, Lee HM, Leongamornlert DA, Laird G, Lloyd C, Lloyd DM, Loveland J, Lovell J, McLaren S, McLay KE, McMurray A, Mashreghi-Mohammadi M, Matthews L, Milne S, Nickerson T, Nguyen M, Overton-Larty E, Palmer SA, Pearce AV, Peck AI, Pelan S, Phillimore B, Porter K, Rice CM, Rogosin A, Ross MT, Sarafidou T, Sehra HK, Shownkeen R, Skuce CD, Smith M, Standring L, Sycamore N, Tester J, Thorpe A, Torcasso W, Tracey A, Tromans A, Tsolas J, Wall M, Walsh J, Wang H, Weinstock K, West AP, Willey DL, Whitehead SL, Wilming L, Wray PW, Young L, Chen Y, Lovering RC, Moschonas NK, Siebert R, Fechtel K, Bentley D, Durbin R, Hubbard T, Doucette-Stamm L, Beck S, Smith DR, and Rogers J
- Subjects
- Animals, Base Composition, Contig Mapping, CpG Islands genetics, Evolution, Molecular, Exons genetics, Gene Duplication, Genetic Variation genetics, Genetics, Medical, Genomics, Humans, Pan troglodytes genetics, Proteins genetics, Pseudogenes genetics, Sequence Analysis, DNA, Chromosomes, Human, Pair 10 genetics, Genes, Physical Chromosome Mapping
- Abstract
The finished sequence of human chromosome 10 comprises a total of 131,666,441 base pairs. It represents 99.4% of the euchromatic DNA and includes one megabase of heterochromatic sequence within the pericentromeric region of the short and long arm of the chromosome. Sequence annotation revealed 1,357 genes, of which 816 are protein coding, and 430 are pseudogenes. We observed widespread occurrence of overlapping coding genes (either strand) and identified 67 antisense transcripts. Our analysis suggests that both inter- and intrachromosomal segmental duplications have impacted on the gene count on chromosome 10. Multispecies comparative analysis indicated that we can readily annotate the protein-coding genes with current resources. We estimate that over 95% of all coding exons were identified in this study. Assessment of single base changes between the human chromosome 10 and chimpanzee sequence revealed nonsense mutations in only 21 coding genes with respect to the human sequence.
- Published
- 2004
- Full Text
- View/download PDF
11. The DNA sequence and analysis of human chromosome 13.
- Author
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Dunham A, Matthews LH, Burton J, Ashurst JL, Howe KL, Ashcroft KJ, Beare DM, Burford DC, Hunt SE, Griffiths-Jones S, Jones MC, Keenan SJ, Oliver K, Scott CE, Ainscough R, Almeida JP, Ambrose KD, Andrews DT, Ashwell RI, Babbage AK, Bagguley CL, Bailey J, Bannerjee R, Barlow KF, Bates K, Beasley H, Bird CP, Bray-Allen S, Brown AJ, Brown JY, Burrill W, Carder C, Carter NP, Chapman JC, Clamp ME, Clark SY, Clarke G, Clee CM, Clegg SC, Cobley V, Collins JE, Corby N, Coville GJ, Deloukas P, Dhami P, Dunham I, Dunn M, Earthrowl ME, Ellington AG, Faulkner L, Frankish AG, Frankland J, French L, Garner P, Garnett J, Gilbert JG, Gilson CJ, Ghori J, Grafham DV, Gribble SM, Griffiths C, Hall RE, Hammond S, Harley JL, Hart EA, Heath PD, Howden PJ, Huckle EJ, Hunt PJ, Hunt AR, Johnson C, Johnson D, Kay M, Kimberley AM, King A, Laird GK, Langford CJ, Lawlor S, Leongamornlert DA, Lloyd DM, Lloyd C, Loveland JE, Lovell J, Martin S, Mashreghi-Mohammadi M, McLaren SJ, McMurray A, Milne S, Moore MJ, Nickerson T, Palmer SA, Pearce AV, Peck AI, Pelan S, Phillimore B, Porter KM, Rice CM, Searle S, Sehra HK, Shownkeen R, Skuce CD, Smith M, Steward CA, Sycamore N, Tester J, Thomas DW, Tracey A, Tromans A, Tubby B, Wall M, Wallis JM, West AP, Whitehead SL, Willey DL, Wilming L, Wray PW, Wright MW, Young L, Coulson A, Durbin R, Hubbard T, Sulston JE, Beck S, Bentley DR, Rogers J, and Ross MT
- Subjects
- Chromosome Mapping, Genetics, Medical, Humans, Pseudogenes genetics, RNA, Untranslated genetics, Sequence Analysis, DNA, Chromosomes, Human, Pair 13 genetics, Genes genetics, Physical Chromosome Mapping
- Abstract
Chromosome 13 is the largest acrocentric human chromosome. It carries genes involved in cancer including the breast cancer type 2 (BRCA2) and retinoblastoma (RB1) genes, is frequently rearranged in B-cell chronic lymphocytic leukaemia, and contains the DAOA locus associated with bipolar disorder and schizophrenia. We describe completion and analysis of 95.5 megabases (Mb) of sequence from chromosome 13, which contains 633 genes and 296 pseudogenes. We estimate that more than 95.4% of the protein-coding genes of this chromosome have been identified, on the basis of comparison with other vertebrate genome sequences. Additionally, 105 putative non-coding RNA genes were found. Chromosome 13 has one of the lowest gene densities (6.5 genes per Mb) among human chromosomes, and contains a central region of 38 Mb where the gene density drops to only 3.1 genes per Mb.
- Published
- 2004
- Full Text
- View/download PDF
12. The DNA sequence and analysis of human chromosome 6.
- Author
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Mungall AJ, Palmer SA, Sims SK, Edwards CA, Ashurst JL, Wilming L, Jones MC, Horton R, Hunt SE, Scott CE, Gilbert JG, Clamp ME, Bethel G, Milne S, Ainscough R, Almeida JP, Ambrose KD, Andrews TD, Ashwell RI, Babbage AK, Bagguley CL, Bailey J, Banerjee R, Barker DJ, Barlow KF, Bates K, Beare DM, Beasley H, Beasley O, Bird CP, Blakey S, Bray-Allen S, Brook J, Brown AJ, Brown JY, Burford DC, Burrill W, Burton J, Carder C, Carter NP, Chapman JC, Clark SY, Clark G, Clee CM, Clegg S, Cobley V, Collier RE, Collins JE, Colman LK, Corby NR, Coville GJ, Culley KM, Dhami P, Davies J, Dunn M, Earthrowl ME, Ellington AE, Evans KA, Faulkner L, Francis MD, Frankish A, Frankland J, French L, Garner P, Garnett J, Ghori MJ, Gilby LM, Gillson CJ, Glithero RJ, Grafham DV, Grant M, Gribble S, Griffiths C, Griffiths M, Hall R, Halls KS, Hammond S, Harley JL, Hart EA, Heath PD, Heathcott R, Holmes SJ, Howden PJ, Howe KL, Howell GR, Huckle E, Humphray SJ, Humphries MD, Hunt AR, Johnson CM, Joy AA, Kay M, Keenan SJ, Kimberley AM, King A, Laird GK, Langford C, Lawlor S, Leongamornlert DA, Leversha M, Lloyd CR, Lloyd DM, Loveland JE, Lovell J, Martin S, Mashreghi-Mohammadi M, Maslen GL, Matthews L, McCann OT, McLaren SJ, McLay K, McMurray A, Moore MJ, Mullikin JC, Niblett D, Nickerson T, Novik KL, Oliver K, Overton-Larty EK, Parker A, Patel R, Pearce AV, Peck AI, Phillimore B, Phillips S, Plumb RW, Porter KM, Ramsey Y, Ranby SA, Rice CM, Ross MT, Searle SM, Sehra HK, Sheridan E, Skuce CD, Smith S, Smith M, Spraggon L, Squares SL, Steward CA, Sycamore N, Tamlyn-Hall G, Tester J, Theaker AJ, Thomas DW, Thorpe A, Tracey A, Tromans A, Tubby B, Wall M, Wallis JM, West AP, White SS, Whitehead SL, Whittaker H, Wild A, Willey DJ, Wilmer TE, Wood JM, Wray PW, Wyatt JC, Young L, Younger RM, Bentley DR, Coulson A, Durbin R, Hubbard T, Sulston JE, Dunham I, Rogers J, and Beck S
- Subjects
- Animals, Exons genetics, Genetic Diseases, Inborn genetics, HLA-B Antigens genetics, Humans, Pseudogenes genetics, RNA, Transfer genetics, Sequence Analysis, DNA, Chromosomes, Human, Pair 6 genetics, Genes genetics, Physical Chromosome Mapping
- Abstract
Chromosome 6 is a metacentric chromosome that constitutes about 6% of the human genome. The finished sequence comprises 166,880,988 base pairs, representing the largest chromosome sequenced so far. The entire sequence has been subjected to high-quality manual annotation, resulting in the evidence-supported identification of 1,557 genes and 633 pseudogenes. Here we report that at least 96% of the protein-coding genes have been identified, as assessed by multi-species comparative sequence analysis, and provide evidence for the presence of further, otherwise unsupported exons/genes. Among these are genes directly implicated in cancer, schizophrenia, autoimmunity and many other diseases. Chromosome 6 harbours the largest transfer RNA gene cluster in the genome; we show that this cluster co-localizes with a region of high transcriptional activity. Within the essential immune loci of the major histocompatibility complex, we find HLA-B to be the most polymorphic gene on chromosome 6 and in the human genome.
- Published
- 2003
- Full Text
- View/download PDF
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