ALBERT

Description: Low-frequency earthquakes (LFEs), which frequently originate from multiplet-generating sources that are closely linked with tectonic tremor in subduction zones around the world, are difficult to observe and characterize due to their low signal-to-noise ratios. This obstacle can be sidestepped by detecting and then stacking all of the multiplets of a master LFE event, or template, using a matched-filter search; the difficulty however lies in finding an LFE event to use as a template. We implement here an automated beamforming algorithm to detect LFEs within the Mexican subduction zone that can then be used as templates in a matched-filter search. Seismograms recorded on a network of seismic stations are aligned to match the moveout of a potential source at depth and their energies are then summed; any spikes in the summed energy indicate an event originating from that potential source. We apply this method to a 1-d test case and we are able to detect 381 unique, potential LFE templates. We then compare our method to a previously introduced LFE detection scheme based on multiplet correlations for three test cases and find that the two methods are complementary.

Description: A stochastic background of gravitational waves is expected to arise from a superposition of a large number of unresolved gravitational-wave sources of astrophysical and cosmological origin. It should carry unique signatures from the earliest epochs in the evolution of the Universe, inaccessible to standard astrophysical observations. Direct measurements of the amplitude of this background are therefore of fundamental importance for understanding the evolution of the Universe when it was younger than one minute. Here we report limits on the amplitude of the stochastic gravitational-wave background using the data from a two-year science run of the Laser Interferometer Gravitational-wave Observatory (LIGO). Our result constrains the energy density of the stochastic gravitational-wave background normalized by the critical energy density of the Universe, in the frequency band around 100 Hz, to be 〈6.9 x 10(-6) at 95% confidence. The data rule out models of early Universe evolution with relatively large equation-of-state parameter, as well as cosmic (super)string models with relatively small string tension that are favoured in some string theory models. This search for the stochastic background improves on the indirect limits from Big Bang nucleosynthesis and cosmic microwave background at 100 Hz.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉LIGO Scientific Collaboration & Virgo Collaboration -- Abbott, B P -- Abbott, R -- Acernese, F -- Adhikari, R -- Ajith, P -- Allen, B -- Allen, G -- Alshourbagy, M -- Amin, R S -- Anderson, S B -- Anderson, W G -- Antonucci, F -- Aoudia, S -- Arain, M A -- Araya, M -- Armandula, H -- Armor, P -- Arun, K G -- Aso, Y -- Aston, S -- Astone, P -- Aufmuth, P -- Aulbert, C -- Babak, S -- Baker, P -- Ballardin, G -- Ballmer, S -- Barker, C -- Barker, D -- Barone, F -- Barr, B -- Barriga, P -- Barsotti, L -- Barsuglia, M -- Barton, M A -- Bartos, I -- Bassiri, R -- Bastarrika, M -- Bauer, Th S -- Behnke, B -- Beker, M -- Benacquista, M -- Betzwieser, J -- Beyersdorf, P T -- Bigotta, S -- Bilenko, I A -- Billingsley, G -- Birindelli, S -- Biswas, R -- Bizouard, M A -- Black, E -- Blackburn, J K -- Blackburn, L -- Blair, D -- Bland, B -- Boccara, C -- Bodiya, T P -- Bogue, L -- Bondu, F -- Bonelli, L -- Bork, R -- Boschi, V -- Bose, S -- Bosi, L -- Braccini, S -- Bradaschia, C -- Brady, P R -- Braginsky, V B -- Brand, J F J van den -- Brau, J E -- Bridges, D O -- Brillet, A -- Brinkmann, M -- Brisson, V -- Van Den Broeck, C -- Brooks, A F -- Brown, D A -- Brummit, A -- Brunet, G -- Bullington, A -- Bulten, H J -- Buonanno, A -- Burmeister, O -- Buskulic, D -- Byer, R L -- Cadonati, L -- Cagnoli, G -- Calloni, E -- Camp, J B -- Campagna, E -- Cannizzo, J -- Cannon, K C -- Canuel, B -- Cao, J -- Carbognani, F -- Cardenas, L -- Caride, S -- Castaldi, G -- Caudill, S -- Cavaglia, M -- Cavalier, F -- Cavalieri, R -- Cella, G -- Cepeda, C -- Cesarini, E -- Chalermsongsak, T -- Chalkley, E -- Charlton, P -- Chassande-Mottin, E -- Chatterji, S -- Chelkowski, S -- Chen, Y -- Christensen, N -- Chung, C T Y -- Clark, D -- Clark, J -- Clayton, J H -- Cleva, F -- Coccia, E -- Cokelaer, T -- Colacino, C N -- Colas, J -- Colla, A -- Colombini, M -- Conte, R -- Cook, D -- Corbitt, T R C -- Corda, C -- Cornish, N -- Corsi, A -- Coulon, J-P -- Coward, D -- Coyne, D C -- Creighton, J D E -- Creighton, T D -- Cruise, A M -- Culter, R M -- Cumming, A -- Cunningham, L -- Cuoco, E -- Danilishin, S L -- D'Antonio, S -- Danzmann, K -- Dari, A -- Dattilo, V -- Daudert, B -- Davier, M -- Davies, G -- Daw, E J -- Day, R -- De Rosa, R -- Debra, D -- Degallaix, J -- Del Prete, M -- Dergachev, V -- Desai, S -- Desalvo, R -- Dhurandhar, S -- Di Fiore, L -- Di Lieto, A -- Di Paolo Emilio, M -- Di Virgilio, A -- Diaz, M -- Dietz, A -- Donovan, F -- Dooley, K L -- Doomes, E E -- Drago, M -- Drever, R W P -- Dueck, J -- Duke, I -- Dumas, J-C -- Dwyer, J G -- Echols, C -- Edgar, M -- Effler, A -- Ehrens, P -- Ely, G -- Espinoza, E -- Etzel, T -- Evans, M -- Evans, T -- Fafone, V -- Fairhurst, S -- Faltas, Y -- Fan, Y -- Fazi, D -- Fehrmann, H -- Ferrante, I -- Fidecaro, F -- Finn, L S -- Fiori, I -- Flaminio, R -- Flasch, K -- Foley, S -- Forrest, C -- Fotopoulos, N -- Fournier, J-D -- Franc, J -- Franzen, A -- Frasca, S -- Frasconi, F -- Frede, M -- Frei, M -- Frei, Z -- Freise, A -- Frey, R -- Fricke, T -- Fritschel, P -- Frolov, V V -- Fyffe, M -- Galdi, V -- Gammaitoni, L -- Garofoli, J A -- Garufi, F -- Genin, E -- Gennai, A -- Gholami, I -- Giaime, J A -- Giampanis, S -- Giardina, K D -- Giazotto, A -- Goda, K -- Goetz, E -- Goggin, L M -- Gonzalez, G -- Gorodetsky, M L -- Gobler, S -- Gouaty, R -- Granata, M -- Granata, V -- Grant, A -- Gras, S -- Gray, C -- Gray, M -- Greenhalgh, R J S -- Gretarsson, A M -- Greverie, C -- Grimaldi, F -- Grosso, R -- Grote, H -- Grunewald, S -- Guenther, M -- Guidi, G -- Gustafson, E K -- Gustafson, R -- Hage, B -- Hallam, J M -- Hammer, D -- Hammond, G D -- Hanna, C -- Hanson, J -- Harms, J -- Harry, G M -- Harry, I W -- Harstad, E D -- Haughian, K -- Hayama, K -- Heefner, J -- Heitmann, H -- Hello, P -- Heng, I S -- Heptonstall, A -- Hewitson, M -- Hild, S -- Hirose, E -- Hoak, D -- Hodge, K A -- Holt, K -- Hosken, D J -- Hough, J -- Hoyland, D -- Huet, D -- Hughey, B -- Huttner, S H -- Ingram, D R -- Isogai, T -- Ito, M -- Ivanov, A -- Johnson, B -- Johnson, W W -- Jones, D I -- Jones, G -- Jones, R -- Sancho de la Jordana, L -- Ju, L -- Kalmus, P -- Kalogera, V -- Kandhasamy, S -- Kanner, J -- Kasprzyk, D -- Katsavounidis, E -- Kawabe, K -- Kawamura, S -- Kawazoe, F -- Kells, W -- Keppel, D G -- Khalaidovski, A -- Khalili, F Y -- Khan, R -- Khazanov, E -- King, P -- Kissel, J S -- Klimenko, S -- Kokeyama, K -- Kondrashov, V -- Kopparapu, R -- Koranda, S -- Kozak, D -- Krishnan, B -- Kumar, R -- Kwee, P -- La Penna, P -- Lam, P K -- Landry, M -- Lantz, B -- Laval, M -- Lazzarini, A -- Lei, H -- Lei, M -- Leindecker, N -- Leonor, I -- Leroy, N -- Letendre, N -- Li, C -- Lin, H -- Lindquist, P E -- Littenberg, T B -- Lockerbie, N A -- Lodhia, D -- Longo, M -- Lorenzini, M -- Loriette, V -- Lormand, M -- Losurdo, G -- Lu, P -- Lubinski, M -- Lucianetti, A -- Luck, H -- Machenschalk, B -- Macinnis, M -- Mackowski, J-M -- Mageswaran, M -- Mailand, K -- Majorana, E -- Man, N -- Mandel, I -- Mandic, V -- Mantovani, M -- Marchesoni, F -- Marion, F -- Marka, S -- Marka, Z -- Markosyan, A -- Markowitz, J -- Maros, E -- Marque, J -- Martelli, F -- Martin, I W -- Martin, R M -- Marx, J N -- Mason, K -- Masserot, A -- Matichard, F -- Matone, L -- Matzner, R A -- Mavalvala, N -- McCarthy, R -- McClelland, D E -- McGuire, S C -- McHugh, M -- McIntyre, G -- McKechan, D J A -- McKenzie, K -- Mehmet, M -- Melatos, A -- Melissinos, A C -- Mendell, G -- Menendez, D F -- Menzinger, F -- Mercer, R A -- Meshkov, S -- Messenger, C -- Meyer, M S -- Michel, C -- Milano, L -- Miller, J -- Minelli, J -- Minenkov, Y -- Mino, Y -- Mitrofanov, V P -- Mitselmakher, G -- Mittleman, R -- Miyakawa, O -- Moe, B -- Mohan, M -- Mohanty, S D -- Mohapatra, S R P -- Moreau, J -- Moreno, G -- Morgado, N -- Morgia, A -- Morioka, T -- Mors, K -- Mosca, S -- Mossavi, K -- Mours, B -- Mowlowry, C -- Mueller, G -- Muhammad, D -- Muhlen, H Zur -- Mukherjee, S -- Mukhopadhyay, H -- Mullavey, A -- Muller-Ebhardt, H -- Munch, J -- Murray, P G -- Myers, E -- Myers, J -- Nash, T -- Nelson, J -- Neri, I -- Newton, G -- Nishizawa, A -- Nocera, F -- Numata, K -- Ochsner, E -- O'Dell, J -- Ogin, G H -- O'Reilly, B -- O'Shaughnessy, R -- Ottaway, D J -- Ottens, R S -- Overmier, H -- Owen, B J -- Pagliaroli, G -- Palomba, C -- Pan, Y -- Pankow, C -- Paoletti, F -- Papa, M A -- Parameshwaraiah, V -- Pardi, S -- Pasqualetti, A -- Passaquieti, R -- Passuello, D -- Patel, P -- Pedraza, M -- Penn, S -- Perreca, A -- Persichetti, G -- Pichot, M -- Piergiovanni, F -- Pierro, V -- Pinard, L -- Pinto, I M -- Pitkin, M -- Pletsch, H J -- Plissi, M V -- Poggiani, R -- Postiglione, F -- Principe, M -- Prix, R -- Prodi, G A -- Prokhorov, L -- Punken, O -- Punturo, M -- Puppo, P -- Putten, S van der -- Quetschke, V -- Raab, F J -- Rabaste, O -- Rabeling, D S -- Radkins, H -- Raffai, P -- Raics, Z -- Rainer, N -- Rakhmanov, M -- Rapagnani, P -- Raymond, V -- Re, V -- Reed, C M -- Reed, T -- Regimbau, T -- Rehbein, H -- Reid, S -- Reitze, D H -- Ricci, F -- Riesen, R -- Riles, K -- Rivera, B -- Roberts, P -- Robertson, N A -- Robinet, F -- Robinson, C -- Robinson, E L -- Rocchi, A -- Roddy, S -- Rolland, L -- Rollins, J -- Romano, J D -- Romano, R -- Romie, J H -- Rover, C -- Rowan, S -- Rudiger, A -- Ruggi, P -- Russell, P -- Ryan, K -- Sakata, S -- Salemi, F -- Sandberg, V -- Sannibale, V -- Santamaria, L -- Saraf, S -- Sarin, P -- Sassolas, B -- Sathyaprakash, B S -- Sato, S -- Satterthwaite, M -- Saulson, P R -- Savage, R -- Savov, P -- Scanlan, M -- Schilling, R -- Schnabel, R -- Schofield, R -- Schulz, B -- Schutz, B F -- Schwinberg, P -- Scott, J -- Scott, S M -- Searle, A C -- Sears, B -- Seifert, F -- Sellers, D -- Sengupta, A S -- Sentenac, D -- Sergeev, A -- Shapiro, B -- Shawhan, P -- Shoemaker, D H -- Sibley, A -- Siemens, X -- Sigg, D -- Sinha, S -- Sintes, A M -- Slagmolen, B J J -- Slutsky, J -- van der Sluys, M V -- Smith, J R -- Smith, M R -- Smith, N D -- Somiya, K -- Sorazu, B -- Stein, A -- Stein, L C -- Steplewski, S -- Stochino, A -- Stone, R -- Strain, K A -- Strigin, S -- Stroeer, A -- Sturani, R -- Stuver, A L -- Summerscales, T Z -- Sun, K-X -- Sung, M -- Sutton, P J -- Swinkels, B L -- Szokoly, G P -- Talukder, D -- Tang, L -- Tanner, D B -- Tarabrin, S P -- Taylor, J R -- Taylor, R -- Terenzi, R -- Thacker, J -- Thorne, K A -- Thorne, K S -- Thuring, A -- Tokmakov, K V -- Toncelli, A -- Tonelli, M -- Torres, C -- Torrie, C -- Tournefier, E -- Travasso, F -- Traylor, G -- Trias, M -- Trummer, J -- Ugolini, D -- Ulmen, J -- Urbanek, K -- Vahlbruch, H -- Vajente, G -- Vallisneri, M -- Vass, S -- Vaulin, R -- Vavoulidis, M -- Vecchio, A -- Vedovato, G -- van Veggel, A A -- Veitch, J -- Veitch, P -- Veltkamp, C -- Verkindt, D -- Vetrano, F -- Vicere, A -- Villar, A -- Vinet, J-Y -- Vocca, H -- Vorvick, C -- Vyachanin, S P -- Waldman, S J -- Wallace, L -- Ward, H -- Ward, R L -- Was, M -- Weidner, A -- Weinert, M -- Weinstein, A J -- Weiss, R -- Wen, L -- Wen, S -- Wette, K -- Whelan, J T -- Whitcomb, S E -- Whiting, B F -- Wilkinson, C -- Willems, P A -- Williams, H R -- Williams, L -- Willke, B -- Wilmut, I -- Winkelmann, L -- Winkler, W -- Wipf, C C -- Wiseman, A G -- Woan, G -- Wooley, R -- Worden, J -- Wu, W -- Yakushin, I -- Yamamoto, H -- Yan, Z -- Yoshida, S -- Yvert, M -- Zanolin, M -- Zhang, J -- Zhang, L -- Zhao, C -- Zotov, N -- Zucker, M E -- Zweizig, J -- England -- Nature. 2009 Aug 20;460(7258):990-4. doi: 10.1038/nature08278.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Lists of participants and their affiliations appear at the end of the paper.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/19693079" target="_blank"〉PubMed〈/a〉

Description: Despite decades of research, the roles of climate and humans in driving the dramatic extinctions of large-bodied mammals during the Late Quaternary period remain contentious. Here we use ancient DNA, species distribution models and the human fossil record to elucidate how climate and humans shaped the demographic history of woolly rhinoceros, woolly mammoth, wild horse, reindeer, bison and musk ox. We show that climate has been a major driver of population change over the past 50,000 years. However, each species responds differently to the effects of climatic shifts, habitat redistribution and human encroachment. Although climate change alone can explain the extinction of some species, such as Eurasian musk ox and woolly rhinoceros, a combination of climatic and anthropogenic effects appears to be responsible for the extinction of others, including Eurasian steppe bison and wild horse. We find no genetic signature or any distinctive range dynamics distinguishing extinct from surviving species, emphasizing the challenges associated with predicting future responses of extant mammals to climate and human-mediated habitat change.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4070744/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4070744/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Lorenzen, Eline D -- Nogues-Bravo, David -- Orlando, Ludovic -- Weinstock, Jaco -- Binladen, Jonas -- Marske, Katharine A -- Ugan, Andrew -- Borregaard, Michael K -- Gilbert, M Thomas P -- Nielsen, Rasmus -- Ho, Simon Y W -- Goebel, Ted -- Graf, Kelly E -- Byers, David -- Stenderup, Jesper T -- Rasmussen, Morten -- Campos, Paula F -- Leonard, Jennifer A -- Koepfli, Klaus-Peter -- Froese, Duane -- Zazula, Grant -- Stafford, Thomas W Jr -- Aaris-Sorensen, Kim -- Batra, Persaram -- Haywood, Alan M -- Singarayer, Joy S -- Valdes, Paul J -- Boeskorov, Gennady -- Burns, James A -- Davydov, Sergey P -- Haile, James -- Jenkins, Dennis L -- Kosintsev, Pavel -- Kuznetsova, Tatyana -- Lai, Xulong -- Martin, Larry D -- McDonald, H Gregory -- Mol, Dick -- Meldgaard, Morten -- Munch, Kasper -- Stephan, Elisabeth -- Sablin, Mikhail -- Sommer, Robert S -- Sipko, Taras -- Scott, Eric -- Suchard, Marc A -- Tikhonov, Alexei -- Willerslev, Rane -- Wayne, Robert K -- Cooper, Alan -- Hofreiter, Michael -- Sher, Andrei -- Shapiro, Beth -- Rahbek, Carsten -- Willerslev, Eske -- R01 HG003229/HG/NHGRI NIH HHS/ -- England -- Nature. 2011 Nov 2;479(7373):359-64. doi: 10.1038/nature10574.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Centre for GeoGenetics, University of Copenhagen, Oster Voldgade 5-7, DK-1350 Copenhagen K, Denmark.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22048313" target="_blank"〉PubMed〈/a〉

Description: The earliest anatomically modern humans in Europe are thought to have appeared around 43,000-42,000 calendar years before present (43-42 kyr cal BP), by association with Aurignacian sites and lithic assemblages assumed to have been made by modern humans rather than by Neanderthals. However, the actual physical evidence for modern humans is extremely rare, and direct dates reach no farther back than about 41-39 kyr cal BP, leaving a gap. Here we show, using stratigraphic, chronological and archaeological data, that a fragment of human maxilla from the Kent's Cavern site, UK, dates to the earlier period. The maxilla (KC4), which was excavated in 1927, was initially diagnosed as Upper Palaeolithic modern human. In 1989, it was directly radiocarbon dated by accelerator mass spectrometry to 36.4-34.7 kyr cal BP. Using a Bayesian analysis of new ultrafiltered bone collagen dates in an ordered stratigraphic sequence at the site, we show that this date is a considerable underestimate. Instead, KC4 dates to 44.2-41.5 kyr cal BP. This makes it older than any other equivalently dated modern human specimen and directly contemporary with the latest European Neanderthals, thus making its taxonomic attribution crucial. We also show that in 13 dental traits KC4 possesses modern human rather than Neanderthal characteristics; three other traits show Neanderthal affinities and a further seven are ambiguous. KC4 therefore represents the oldest known anatomically modern human fossil in northwestern Europe, fills a key gap between the earliest dated Aurignacian remains and the earliest human skeletal remains, and demonstrates the wide and rapid dispersal of early modern humans across Europe more than 40 kyr ago.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Higham, Tom -- Compton, Tim -- Stringer, Chris -- Jacobi, Roger -- Shapiro, Beth -- Trinkaus, Erik -- Chandler, Barry -- Groning, Flora -- Collins, Chris -- Hillson, Simon -- O'Higgins, Paul -- FitzGerald, Charles -- Fagan, Michael -- England -- Nature. 2011 Nov 2;479(7374):521-4. doi: 10.1038/nature10484.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Oxford Radiocarbon Accelerator Unit, Research Laboratory for Archaeology and the History of Art, University of Oxford, Oxford OX1 3QY, UK. thomas.higham@rlaha.ox.ac.uk〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22048314" target="_blank"〉PubMed〈/a〉

Description: The rich fossil record of equids has made them a model for evolutionary processes. Here we present a 1.12-times coverage draft genome from a horse bone recovered from permafrost dated to approximately 560-780 thousand years before present (kyr BP). Our data represent the oldest full genome sequence determined so far by almost an order of magnitude. For comparison, we sequenced the genome of a Late Pleistocene horse (43 kyr BP), and modern genomes of five domestic horse breeds (Equus ferus caballus), a Przewalski's horse (E. f. przewalskii) and a donkey (E. asinus). Our analyses suggest that the Equus lineage giving rise to all contemporary horses, zebras and donkeys originated 4.0-4.5 million years before present (Myr BP), twice the conventionally accepted time to the most recent common ancestor of the genus Equus. We also find that horse population size fluctuated multiple times over the past 2 Myr, particularly during periods of severe climatic changes. We estimate that the Przewalski's and domestic horse populations diverged 38-72 kyr BP, and find no evidence of recent admixture between the domestic horse breeds and the Przewalski's horse investigated. This supports the contention that Przewalski's horses represent the last surviving wild horse population. We find similar levels of genetic variation among Przewalski's and domestic populations, indicating that the former are genetically viable and worthy of conservation efforts. We also find evidence for continuous selection on the immune system and olfaction throughout horse evolution. Finally, we identify 29 genomic regions among horse breeds that deviate from neutrality and show low levels of genetic variation compared to the Przewalski's horse. Such regions could correspond to loci selected early during domestication.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Orlando, Ludovic -- Ginolhac, Aurelien -- Zhang, Guojie -- Froese, Duane -- Albrechtsen, Anders -- Stiller, Mathias -- Schubert, Mikkel -- Cappellini, Enrico -- Petersen, Bent -- Moltke, Ida -- Johnson, Philip L F -- Fumagalli, Matteo -- Vilstrup, Julia T -- Raghavan, Maanasa -- Korneliussen, Thorfinn -- Malaspinas, Anna-Sapfo -- Vogt, Josef -- Szklarczyk, Damian -- Kelstrup, Christian D -- Vinther, Jakob -- Dolocan, Andrei -- Stenderup, Jesper -- Velazquez, Amhed M V -- Cahill, James -- Rasmussen, Morten -- Wang, Xiaoli -- Min, Jiumeng -- Zazula, Grant D -- Seguin-Orlando, Andaine -- Mortensen, Cecilie -- Magnussen, Kim -- Thompson, John F -- Weinstock, Jacobo -- Gregersen, Kristian -- Roed, Knut H -- Eisenmann, Vera -- Rubin, Carl J -- Miller, Donald C -- Antczak, Douglas F -- Bertelsen, Mads F -- Brunak, Soren -- Al-Rasheid, Khaled A S -- Ryder, Oliver -- Andersson, Leif -- Mundy, John -- Krogh, Anders -- Gilbert, M Thomas P -- Kjaer, Kurt -- Sicheritz-Ponten, Thomas -- Jensen, Lars Juhl -- Olsen, Jesper V -- Hofreiter, Michael -- Nielsen, Rasmus -- Shapiro, Beth -- Wang, Jun -- Willerslev, Eske -- RC2 HG005598/HG/NHGRI NIH HHS/ -- England -- Nature. 2013 Jul 4;499(7456):74-8. doi: 10.1038/nature12323. Epub 2013 Jun 26.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Oster Voldgade 5-7, 1350 Copenhagen K, Denmark. Lorlando@snm.ku.dk〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/23803765" target="_blank"〉PubMed〈/a〉

Description: Recent advances in paleogenomic technologies have enabled an increasingly detailed understanding of the evolutionary relationships of now-extinct mammalian taxa. However, a number of enigmatic Quaternary species have never been characterized with molecular data, often because available fossils are rare or are found in environments that are not optimal for DNA preservation. Here, we analyze paleogenomic data extracted from bones attributed to the late Pleistocene western camel, Camelops cf. hesternus, a species that was distributed across central and western North America until its extinction approximately 13,000 years ago. Despite a modal sequence length of only around 35 base pairs, we reconstructed high-coverage complete mitochondrial genomes and low-coverage partial nuclear genomes for each specimen. We find that Camelops is sister to African and Asian bactrian and dromedary camels, to the exclusion of South American camelids (llamas, guanacos, alpacas, and vicuñas). These results contradict previous morphology-based phylogenetic models for Camelops , which suggest instead a closer relationship between Camelops and the South American camelids. The molecular data imply a Late Miocene divergence of the Camelops clade from lineages that separately gave rise to the extant camels of Eurasia. Our results demonstrate the increasing capacity of modern paleogenomic methods to resolve evolutionary relationships among distantly related lineages.

Description: In recent years, ancient DNA has increasingly been used for estimating molecular timescales, particularly in studies of substitution rates and demographic histories. Molecular clocks can be calibrated using temporal information from ancient DNA sequences. This information comes from the ages of the ancient samples, which can be estimated by radiocarbon dating the source material or by dating the layers in which the material was deposited. Both methods involve sources of uncertainty. The performance of Bayesian phylogenetic inference depends on the information content of the data set, which includes variation in the DNA sequences and the structure of the sample ages. Various sources of estimation error can reduce our ability to estimate rates and timescales accurately and precisely. We investigated the impact of sample-dating uncertainties on the estimation of evolutionary timescale parameters using the software BEAST. Our analyses involved 11 published data sets and focused on estimates of substitution rate and root age. We show that, provided that samples have been accurately dated and have a broad temporal span, it might be unnecessary to account for sample-dating uncertainty in Bayesian phylogenetic analyses of ancient DNA. We also investigated the sample size and temporal span of the ancient DNA sequences needed to estimate phylogenetic timescales reliably. Our results show that the range of sample ages plays a crucial role in determining the quality of the results but that accurate and precise phylogenetic estimates of timescales can be made even with only a few ancient sequences. These findings have important practical consequences for studies of molecular rates, timescales, and population dynamics.

Description: Effective population size is fundamental in population genetics and characterizes genetic diversity. To infer past population dynamics from molecular sequence data, coalescent-based models have been developed for Bayesian nonparametric estimation of effective population size over time. Among the most successful is a Gaussian Markov random field (GMRF) model for a single gene locus. Here, we present a generalization of the GMRF model that allows for the analysis of multilocus sequence data. Using simulated data, we demonstrate the improved performance of our method to recover true population trajectories and the time to the most recent common ancestor (TMRCA). We analyze a multilocus alignment of HIV-1 CRF02_AG gene sequences sampled from Cameroon. Our results are consistent with HIV prevalence data and uncover some aspects of the population history that go undetected in Bayesian parametric estimation. Finally, we recover an older and more reconcilable TMRCA for a classic ancient DNA data set.

Description: Motivation: We introduce Pycellerator, a Python library for reading Cellerator arrow notation from standard text files, conversion to differential equations, generating stand-alone Python solvers, and optionally running and plotting the solutions. All of the original Cellerator arrows, which represent reactions ranging from mass action, Michales–Menten–Henri (MMH) and Gene-Regulation (GRN) to Monod–Wyman–Changeaux (MWC), user defined reactions and enzymatic expansions (KMech), were previously represented with the Mathematica extended character set. These are now typed as reaction-like commands in ASCII text files that are read by Pycellerator, which includes a Python command line interface (CLI), a Python application programming interface (API) and an iPython notebook interface. Results: Cellerator reaction arrows are now input in text files. The arrows are parsed by Pycellerator and translated into differential equations in Python, and Python code is automatically generated to solve the system. Time courses are produced by executing the auto-generated Python code. Users have full freedom to modify the solver and utilize the complete set of standard Python tools. The new libraries are completely independent of the old Cellerator software and do not require Mathematica. Availability and implementation: All software is available (GPL) from the github repository at https://github.com/biomathman/pycellerator/releases . Details, including installation instructions and a glossary of acronyms and terms, are given in the Supplementary information . Contact: bruce.e.shapiro@csun.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Remarkably little is known about the population-level processes leading up to the extinction of the neandertal. To examine this, we use mitochondrial DNA sequences from 13 neandertal individuals, including a novel sequence from northern Spain, to examine neandertal demographic history. Our analyses indicate that recent western European neandertals (〈48 kyr) constitute a tightly defined group with low mitochondrial genetic variation in comparison with both eastern and older (〉48 kyr) European neandertals. Using control region sequences, Bayesian demographic simulations provide higher support for a model of population fragmentation followed by separate demographic trajectories in subpopulations over a null model of a single stable population. The most parsimonious explanation for these results is that of a population turnover in western Europe during early Marine Isotope Stage 3, predating the arrival of anatomically modern humans in the region.