200 research outputs found
Low Latency Estimation of Motor Intentions to Assist Reaching Movements along Multiple Sessions in Chronic Stroke Patients: A Feasibility Study
A corrigendum on
Low Latency Estimation of Motor Intentions to Assist Reaching Movements along Multiple
Sessions in Chronic Stroke Patients: A Feasibility Study
by Ibáñez, J., Monge-Pereira, E., Molina-Rueda, F., Serrano, J. I., del Castillo, M. D., Cuesta-Gómez,
A., et al. (2017). Front. Neurosci. 11:126. doi: 10.3389/fnins.2017.00126. In the recently published article, there were incorrect and missing contents in the
Acknowledgments section
Bacterial microevolution and the Pangenome
The comparison of multiple genome sequences sampled from a bacterial population reveals considerable diversity in both the core and the accessory parts of the pangenome. This diversity can be analysed in terms of microevolutionary events that took place since the genomes shared a common ancestor, especially deletion, duplication, and recombination. We review the basic modelling ingredients used implicitly or explicitly when performing such a pangenome analysis. In particular, we describe a basic neutral phylogenetic framework of bacterial pangenome microevolution, which is not incompatible with evaluating the role of natural selection. We survey the different ways in which pangenome data is summarised in order to be included in microevolutionary models, as well as the main methodological approaches that have been proposed to reconstruct pangenome microevolutionary history
VAMOS: a Pathfinder for the HAWC Gamma-Ray Observatory
VAMOS was a prototype detector built in 2011 at an altitude of 4100m a.s.l.
in the state of Puebla, Mexico. The aim of VAMOS was to finalize the design,
construction techniques and data acquisition system of the HAWC observatory.
HAWC is an air-shower array currently under construction at the same site of
VAMOS with the purpose to study the TeV sky. The VAMOS setup included six water
Cherenkov detectors and two different data acquisition systems. It was in
operation between October 2011 and May 2012 with an average live time of 30%.
Besides the scientific verification purposes, the eight months of data were
used to obtain the results presented in this paper: the detector response to
the Forbush decrease of March 2012, and the analysis of possible emission, at
energies above 30 GeV, for long gamma-ray bursts GRB111016B and GRB120328B.Comment: Accepted for pubblication in Astroparticle Physics Journal (20 pages,
10 figures). Corresponding authors: A.Marinelli and D.Zaboro
Reaction rates and transport in neutron stars
Understanding signals from neutron stars requires knowledge about the
transport inside the star. We review the transport properties and the
underlying reaction rates of dense hadronic and quark matter in the crust and
the core of neutron stars and point out open problems and future directions.Comment: 74 pages; commissioned for the book "Physics and Astrophysics of
Neutron Stars", NewCompStar COST Action MP1304; version 3: minor changes,
references updated, overview graphic added in the introduction, improvements
in Sec IV.A.
Haemonchus contortus Acetylcholine Receptors of the DEG-3 Subfamily and Their Role in Sensitivity to Monepantel
Gastro-intestinal nematodes in ruminants, especially Haemonchus contortus, are a global threat to sheep and cattle farming. The emergence of drug resistance, and even multi-drug resistance to the currently available classes of broad spectrum anthelmintics, further stresses the need for new drugs active against gastro-intestinal nematodes. A novel chemical class of synthetic anthelmintics, the Amino-Acetonitrile Derivatives (AADs), was recently discovered and the drug candidate AAD-1566 (monepantel) was chosen for further development. Studies with Caenorhabditis elegans suggested that the AADs act via nicotinic acetylcholine receptors (nAChR) of the nematode-specific DEG-3 subfamily. Here we identify nAChR genes of the DEG-3 subfamily from H. contortus and investigate their role in AAD sensitivity. Using a novel in vitro selection procedure, mutant H. contortus populations of reduced sensitivity to AAD-1566 were obtained. Sequencing of full-length nAChR coding sequences from AAD-susceptible H. contortus and their AAD-1566-mutant progeny revealed 2 genes to be affected. In the gene monepantel-1 (Hco-mptl-1, formerly named Hc-acr-23H), a panel of mutations was observed exclusively in the AAD-mutant nematodes, including deletions at intron-exon boundaries that result in mis-spliced transcripts and premature stop codons. In the gene Hco-des-2H, the same 135 bp insertion in the 5′ UTR created additional, out of frame start codons in 2 independent H. contortus AAD-mutants. Furthermore, the AAD mutants exhibited altered expression levels of the DEG-3 subfamily nAChR genes Hco-mptl-1, Hco-des-2H and Hco-deg-3H as quantified by real-time PCR. These results indicate that Hco-MPTL-1 and other nAChR subunits of the DEG-3 subfamily constitute a target for AAD action against H. contortus and that loss-of-function mutations in the corresponding genes may reduce the sensitivity to AADs
Alcohol, binge drinking and associated mental health problems in young urban Chileans
OBJECTIVE: To explore the link between alcohol use, binge drinking and mental health problems in a representative sample of adolescent and young adult Chileans. METHODS: Age and sex-adjusted Odds Ratios (OR) for four mental wellbeing measures were estimated with separate conditional logistic regression models for adolescents aged 15-20 years, and young adults aged 21-25 years, using population-based estimates of alcohol use prevalence rates from the Chilean National Health Survey 2010. RESULTS: Sixty five per cent of adolescents and 85% of young adults reported drinking alcohol in the last year and of those 83% per cent of adolescents and 86% of young adults reported binge drinking in the previous month. Adolescents who reported binging alcohol were also more likely, compared to young adults, to report being always or almost always depressed (OR 12.97 [95% CI, 1.86-19.54]) or to feel very anxious in the last month (OR 9.37 [1.77-19.54]). Adolescent females were more likely to report poor life satisfaction in the previous year than adolescent males (OR 8.50 [1.61-15.78]), feel always or almost always depressed (OR 3.41 [1.25-9.58]). Being female was also associated with a self-reported diagnosis of depression for both age groups (adolescents, OR 4.74 [1.49-15.08] and young adults, OR 4.08 [1.65-10.05]). CONCLUSION: Young people in Chile self-report a high prevalence of alcohol use, binge drinking and associated mental health problems. The harms associated with alcohol consumption need to be highlighted through evidence-based prevention programs. Health and education systems need to be strengthened to screen and support young people. Focussing on policy initiatives to limit beverage companies targeting alcohol to young people will also be needed
Comparison of transcriptome-derived simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for genetic fingerprinting, diversity evaluation, and establishment of relationships in eggplants
[EN] Simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers are amongst the most common markers of choice for studies of diversity and relationships in horticultural species. We have used 11 SSR and 35 SNP markers derived from transcriptome sequencing projects to fingerprint 48 accessions of a collection of brinjal (Solanum melongena), gboma (S. macrocarpon) and scarlet (S. aethiopicum) eggplant complexes, which also include their respective wild relatives S. incanum, S. dasyphyllum and S. anguivi. All SSR and SNP markers were polymorphic and 34 and 36 different genetic fingerprints were obtained with SSRs and SNPs, respectively. When combining both markers all accessions but two had different genetic profiles. Although on average SSRs were more informative than SNPs, with a higher number of alleles, genotypes and polymorphic information content (PIC), and expected heterozygosity (He) values, SNPs have proved highly informative in our materials. Low observed heterozygosity (Ho) and high fixation index (f) values confirm the high degree of homozygosity of eggplants. Genetic identities within groups of each complex were higher than with groups of other complexes, although differences in the ranks of genetic identity values among groups were observed between SSR and SNP markers. For low and intermediate values of pair-wise SNP genetic distances, a moderate correlation between SSR and SNP genetic distances was observed (r(2) = 0.592), but for high SNP genetic distances the correlation was low (r(2) = 0.080). The differences among markers resulted in different phenogram topologies, with a different eggplant complex being basal (gboma eggplant for SSRs and brinjal eggplant for SNPs) to the two others. Overall the results reveal that both types of markers are complementary for eggplant fingerprinting and that interpretation of relationships among groups may be greatly affected by the type of marker used.This work has been funded by European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No 677379 (G2P-SOL project: Linking genetic resources, genomes and phenotypes of Solanaceous crops) and by Spanish Ministerio de Economia y Competitividad and Fondo Europeo de Desarrollo Regional (Grant AGL2015-64755-R from MINECO/FEDER). Pietro Gramazio is grateful to Universitat Politecnica de Valencia for a pre-doctoral contract (Programa FPI de la UPV-Subprograma 1/2013 call). Mariola Plazas is grateful to Spanish Ministerio de Economia, Industria y Competitividad for a post-doctoral grant within the Juan de la Cierva-Formacion programme (FJCI-2015-24835).Gramazio, P.; Prohens Tomás, J.; Borras, D.; Plazas Ávila, MDLO.; Herraiz García, FJ.; Vilanova Navarro, S. (2017). Comparison of transcriptome-derived simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for genetic fingerprinting, diversity evaluation, and establishment of relationships in eggplants. Euphytica. 213(264):1-18. https://doi.org/10.1007/s10681-017-2057-3S118213264Acquadro A, Barchi L, Gramazio P et al (2017) Coding SNPs analysis highlights genetic relationships and evolution pattern in eggplant complexes. PLoS ONE 12:e0180774. https://doi.org/10.1371/journal.pone.0180774Adeniji O, Kusolwa P, Reuben S (2013) Morphological descriptors and micro satellite diversity among scarlet eggplant groups. Afr Crop Sci J 21(1):37–49Aguoru C, Omoigui L, Olasan J (2015) Molecular characterization of Solanum species (Solanum aethiopicum complex; Solanum macrocarpon and Solanum anguivi) using multiplex RAPD primers. J Plant Stud 4:27–34. https://doi.org/10.5539/jps.v4n1p27Arumuganathan K, Earle E (1991) Nuclear DNA content of some important plant species. Plant Mol Biol Rep 9(3):208–218Ashrafi H, Hill T, Stoffel K et al (2012) De novo assembly of the pepper transcriptome (Capsicum annuum): a benchmark for in silico discovery of SNPs, SSRs and candidate genes. BMC Genom 13:1–15. https://doi.org/10.1186/1471-2164-13-571Augustinos AA, Petropoulos C, Karasoulou V et al (2016) Assessing diversity among traditional Greek and foreign eggplant cultivars using molecular markers and morphometrical descriptors. Span J Agric Res 14:e0710. https://doi.org/10.5424/sjar/2016144-9020Avise JC (2012) Molecular markers, natural history and evolution. Springer Science & Business Media, Berlin. https://doi.org/10.1007/978-1-4615-2381-9Blanca J, Cañizares J, Roig C et al (2011) Transcriptome characterization and high throughput SSRs and SNPs discovery in Cucurbita pepo (Cucurbitaceae). BMC Genom 12:104. https://doi.org/10.1186/1471-2164-12-104Botstein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet 32(3):314–331Bukenya Z, Carasco J (1994) Biosystematic study of Solanum macrocarpon—S. dasyphyllum complex in Uganda and relations with Solanum linnaeanum. East Afr Agric For J 59(3):187–204Castillo A, Budak H, Varshney RK et al (2008) Transferability and polymorphism of barley EST-SSR markers used for phylogenetic analysis in Hordeum chilense. BMC Plant Biol 8:97. https://doi.org/10.1186/1471-2229-8-97Choudhary S, Sethy NK, Shokeen B, Bhatia S (2009) Development of chickpea EST-SSR markers and analysis of allelic variation across related species. Theor Appl Genet 118:591–608. https://doi.org/10.1007/s00122-008-0923-zCoates BS, Sumerford DV, Miller NJ et al (2009) Comparative performance of single nucleotide polymorphism and microsatellite markers for population genetic analysis. J Hered 100:556–564. https://doi.org/10.1093/jhered/esp028D’Agostino N, Golas T, van de Geest H et al (2013) Genomic analysis of the native European Solanum species, S. dulcamara. BMC Genom 14:356. https://doi.org/10.1186/1471-2164-14-356Daunay MC, Hazra P (2012) Eggplant. In: Peter KV, Hazra P (eds) Handbook of Vegetables. Studium Press, Houston, pp 257–322Davey J, Hohenlohe P, Etter P et al (2011) Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nat Rev Genet 12:499–510. https://doi.org/10.1038/nrg3012De Barba M, Miquel C, Lobréaux S et al (2016) High-throughput microsatellite genotyping in ecology: improved accuracy, efficiency, standardization and success with low-quantity and degraded DNA. Mol Ecol Resour 17(3):492–507. https://doi.org/10.1111/1755-0998.12594Doyle J, Doyle J (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem Bull 19:11–15Ellegren H (2004) Microsatellites: simple sequences with complex evolution. Nat Rev Genet 5:435–445. https://doi.org/10.1038/nrg1348Felsenstein, J (2007). PHYLIP (Phylogeny Inference Package) Version 3.67. Department of Genome Sciences, University of Washington, Seattle, WA, USAFernandez-Silva I, Whitney J, Wainwright B (2013) Microsatellites for next-generation ecologists: a post-sequencing bioinformatics pipeline. PLoS ONE 8(2):e55990Filippi CV, Aguirre N, Rivas JG et al (2015) Population structure and genetic diversity characterization of a sunflower association mapping population using SSR and SNP markers. BMC Plant Biol 15:52. https://doi.org/10.1186/s12870-014-0360-xFischer MC, Rellstab C, Leuzinger M et al (2017) Estimating genomic diversity and population differentiation—an empirical comparison of microsatellite and SNP variation in Arabidopsis halleri. BMC Genom 18:69. https://doi.org/10.1186/s12864-016-3459-7Furini A, Wunder J (2004) Analysis of eggplant (Solanum melongena)-related germplasm: morphological and AFLP data contribute to phylogenetic interpretations and germplasm utilization. Theor Appl Genet 108:197–208. https://doi.org/10.1007/s00122-003-1439-1Gadaleta A, Giancaspro A, Zacheo S et al (2011) Comparison of genomic and EST-derived SSR markers in phylogenetic analysis of wheat. Plant Genet Resour 9:243–246. https://doi.org/10.1017/S147926211100030XGe H, Liu Y, Jiang M et al (2013) Analysis of genetic diversity and structure of eggplant populations (Solanum melongena L.) in China using simple sequence repeat markers. Sci Hortic 162:71–75. https://doi.org/10.1016/j.scienta.2013.08.004Gonzaga ZJ (2015) Evaluation of SSR and SNP Markers for Molecular Breeding in Rice. Plant Breed Biotechnol 3:139–152. https://doi.org/10.9787/PBB.2015.3.2.139Goodwin S, McPherson J, McCombie W (2016) Coming of age: ten years of next-generation sequencing technologies. Nat Rev Genet 17(6):333–351Gramazio P, Blanca J, Ziarsolo P et al (2016) Transcriptome analysis and molecular marker discovery in Solanum incanum and S. aethiopicum, two close relatives of the common eggplant (Solanum melongena) with interest for breeding. BMC Genom 17:300. https://doi.org/10.1186/s12864-016-2631-4Grover A, Sharma PC (2014) Development and use of molecular markers: past and present. Crit Rev Biotechnol 8551:1–13. https://doi.org/10.3109/07388551.2014.959891Hamblin MT, Warburton ML, Buckler ES (2007) Empirical comparison of simple sequence repeats and single nucleotide polymorphisms in assessment of maize diversity and relatedness. PLoS ONE 2:e1367. https://doi.org/10.1371/journal.pone.0001367Hess JE, Matala AP (2011) Comparison of SNPs and microsatellites for fine-scale application of genetic stock identification of Chinook salmon in the Columbia River Basin Comparison of SNPs and microsatellites for fine-scale application of genetic stock identification of Chinook salmon in the Columbia River Basin. Mol Ecol Resour. https://doi.org/10.1111/j.1755-0998.2010.02958.xHighton R (1993) The relationship between the number of loci and the statistical support for the topology of UPGMA trees obtained from genetic distance data. Mol Phylogenet Evol 2:337–343Hirakawa H, Shirasawa K, Miyatake K, Nunome, T et al (2014) Draft genome sequence of eggplant (Solanum melongena L.): the representative solanum species indigenous to the old world. DNA Res 21:649–660. https://doi.org/10.1093/dnares/dsu027Hong CP, Piao ZY, Kang TW et al (2007) Genomic distribution of simple sequence repeats in Brassica rapa. Mol Cells 23:349–356.Hu J, Wang L, Li J (2011) Comparison of genomic SSR and EST-SSR markers for estimating genetic diversity in cucumber. Biol Plant 55:577–580. https://doi.org/10.1007/s10535-011-0129-0Isshiki S, Iwata N, Khan MMR (2008) ISSR variations in eggplant (Solanum melongena L.) and related Solanum species. Sci Hortic 117:186–190. https://doi.org/10.1016/j.scienta.2008.04.003Jones ES, Sullivan H, Bhattramakki D, Smith JSC (2007) A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (Zea mays L.). Theor Appl Genet 115:361–371. https://doi.org/10.1007/s00122-007-0570-9Kalia RK, Rai MK, Kalia S et al (2011) Microsatellite markers: an overview of the recent progress in plants. Euphytica 177:309–334Kashi Y, King DG (2006) Simple sequence repeats as advantageous mutators in evolution. Trends Genet 22:253–259. https://doi.org/10.1016/j.tig.2006.03.005Kaushik P, Prohens J, Vilanova S et al (2016) Phenotyping of eggplant wild relatives and interspecific hybrids with conventional and phenomics descriptors provides insight for their potential utilization in breeding. Front Plant Sci 7:677Kim C, Guo H, Kong W et al (2016) Application of genotyping by sequencing technology to a variety of crop breeding programs. Plant Sci 242:14–22Knapp S, Vorontsova MS, Prohens J (2013) Wild relatives of the eggplant (Solanum melongena L.: Solanaceae): new understanding of species names in a complex group. PLoS ONE 8:e57039Kruglyak S, Durrett RT, Schug MD, Aquadro CF (1998) Equilibrium distributions of microsatellite repeat length resulting from a balance between slippage events and point mutations. Proc Natl Acad Sci USA 95:10774–10778. https://doi.org/10.1073/pnas.95.18.10774Lester RN, Daunay MC (2003) Diversity of African vegetable Solanum species and its implications for a better understanding of plant domestication. Schriften zu Genetischen Ressourcen 22:137–152Lester RN, Niakan L (1986) Origin and domestication of the scarlet eggplant, Solanum aethiopicum, from S. anguivi in Africa. In: D’Arcy WG (ed) Solanaceae: biology and systematics. Columbia University Press, New York, pp 433–456Lester RN, Jaeger PML, Bleijendaal-Spierings BHM et al (1990) African eggplants-a review of collecting in West Africa. Plant Genet Resour Newsl 81:17–26Levin R, Myers N, Bohs L (2006) Phylogenetic relationships among the ‘spiny solanums’ (Solanum subgenus Leptostemonum, Solanaceae). Am J Bot 93(1):157–169Li WH, Gojobori T, Nei M (1981) Pseudogenes as a paradigm of neutral evolution. Nature 292:237–239Li YC, Korol AB, Fahima T et al (2002) Microsatellites: genomic distribution, putative functions and mutational mechanisms: a review. Mol Ecol 11:2453–2465Liu K, Muse S (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21:2128–2129Mantel N (1967) The detection of disease clustering and a generalized regression approach. Cancer Res 27:209–220. https://doi.org/10.1038/214637b0Martínez-Arias R, Calafell F, Mateu E et al (2001) Sequence variability of a human pseudogene. Genome Res 11:1071–1085. https://doi.org/10.1101/gr.167701Meyer RS, Karol KG, Little DP et al (2012) Phylogeographic relationships among Asian eggplants and new perspectives on eggplant domestication. Mol Phylogenet Evol 63:685–701. https://doi.org/10.1016/j.ympev.2012.02.006Muñoz-Falcón J, Prohens J, Vilanova S, Nuez F (2009) Diversity in commercial varieties and landraces of black eggplants and implications for broadening the breeders’ gene pool. Ann Appl Biol 154(3):453–465Nandha PS, Singh J (2014) Comparative assessment of genetic diversity between wild and cultivated barley using gSSR and EST-SSR markers. Plant Breed 133:28–35. https://doi.org/10.1111/pbr.12118Nei M (1972) Genetic distance between populations. Am Nat 106:283–292. https://doi.org/10.1086/282771Nunome T, Negoro S, Kono I et al (2009) Development of SSR markers derived from SSR-enriched genomic library of eggplant (Solanum melongena L.). Theor Appl Genet 119:1143–1153. https://doi.org/10.1007/s00122-009-1116-0Page R (2001) TreeView. Glasgow University, GlasgowPeakall P, Smouse R (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research an update. Bioinformatics 28:2537–2539Pessarakli M, Dris R (2004) Pollination and breeding of eggplants. J Food Agric Environ 2:218–219Plazas M, Andújar I, Vilanova S et al (2014) Conventional and phenomics characterization provides insight into the diversity and relationships of hypervariable scarlet (Solanum aethiopicum L.) and gboma (S. macrocarpon L.) eggplant complexes. Front. Plant Sci 5:318Ranil R, Niran H, Plazas M et al (2015) Improving seed germination of the eggplant rootstock Solanum torvum by testing multiple factors using an orthogonal array design. Sci Hortic 193:174–181. https://doi.org/10.1016/j.scienta.2015.07.030Sakata Y, Lester RN (1997) Chloroplast DNA diversity in brinjal eggplant (Solanum melongena L.) and related species. Euphytica 97:295–301. https://doi.org/10.1023/A:1003000612441Sakata Y, Nishio T, Matthews PJ (1991) Chloroplast DNA analysis of eggplant (Solanum melongena) and related species for their taxonomic affinity. Euphytica 55:21–26Särkinen T, Bohs L, Olmstead RG, Knapp S (2013) A phylogenetic framework for evolutionary study of the nightshades (Solanaceae): a dated 1000-tip tree. BMC Evol Biol 13:214. https://doi.org/10.1186/1471-2148-13-214Scheben A, Batley J, Edwards D (2017) Genotyping-by-sequencing approaches to characterize crop genomes: choosing the right tool for the right application. Plant Biotechnol J 15:149–161Sneath P, Sokal R (1973) Numerical taxonomy. The principles and practice of numerical classification. W H Freeman Limited, San FranciscoStàgel A, Portis E, Toppino L et al (2008) Gene-based microsatellite development for mapping and phylogeny studies in eggplant. BMC Genom 9:357. https://doi.org/10.1186/1471-2164-9-357Sunseri F, Polignano GB, Alba V et al (2010) Genetic diversity and characterization of African eggplant germplasm collection. Afr J Plant Sci 4:231–241Syfert MM, Castañeda-Álvarez NP, Khoury CK et al (2016) Crop wild relatives of the brinjal eggplant (Solanum melongena): poorly represented in genebanks and many species at risk of extinction. Am J Bot 103:635–651. https://doi.org/10.3732/ajb.1500539Thiel T, Michalek W, Varshney R, Graner A (2003) Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.). Theor Appl Genet 106:411–422. https://doi.org/10.1007/s00122-002-1031-0Thomson MJ, Alfred J, Dangl J et al (2014) High-throughput SNP genotyping to accelerate crop improvement. Plant Breed Biotechnol 2:195–212. https://doi.org/10.9787/PBB.2014.2.3.195Thorvaldsdóttir H, Robinson JT, Mesirov JP (2013) Integrative genomics viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 14:178–192. https://doi.org/10.1093/bib/bbs017Tumbilen Y, Frary A, Daunay MC, Doganlar S (2011) Application of EST-SSRs to examine genetic diversity in eggplant and its close relatives. Turk J Biol 35:125–136. https://doi.org/10.3906/biy-0906-57van Inghelandt D, Melchinger AE, Lebreton C, Stich B (2010) Population structure and genetic diversity in a commercial maize breeding program assessed with SSR and SNP markers. Theor Appl Genet 120:1289–1299. https://doi.org/10.1007/s00122-009-1256-2Van Tassell CP, Smith TPL, Matukumalli LK et al (2008) SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries. Nat Methods 5:247–252. https://doi.org/10.1038/nmeth.1185Varshney R, Graner A, Sorrells M (2005) Genic microsatellite markers in plants: features and applications. Trends Biotechnol 23(1):48–55Varshney RK, Chabane K, Hendre PS et al (2007) Comparative assessment of EST-SSR, EST-SNP and AFLP markers for evaluation of genetic diversity and conservation of genetic resources using wild, cultivated and elite barleys. Plant Sci 173:638–649. https://doi.org/10.1016/j.plantsci.2007.08.010Vilanova S, Manzur JP, Prohens J (2012) Development and characterization of genomic simple sequence repeat markers in eggplant and their application to the study of diversity and relationships in a collection of different cultivar types and origins. Mol Breed 30:647–660. https://doi.org/10.1007/s11032-011-9650-2Vilanova S, Hurtado M, Cardona A (2014) Genetic diversity and relationships in local varieties of eggplant from different cultivar groups as assessed by genomic SSR markers. Not Bot Horti Agrobo Cluj-Napoca 42:59–65Vogel JP, Gu YQ, Twigg P et al (2006) EST sequencing and phylogenetic analysis of the model grass Brachypodium distachyon. Theor Appl Genet 113:186–195. https://doi.org/10.1007/s00122-006-0285-3Vorontsova MS, Stern S, Bohs L, Knapp S (2013) African spiny solanum (subgenus Leptostemonum, Solanaceae): a thorny phylogenetic tangle. Bot J Linn Soc 173:176–193. https://doi.org/10.1111/boj.12053Weese TL, Bohs L (2010) Eggplant origins: out of Africa, into the Orient. Taxon 59:49–56. https://doi.org/10.2307/27757050Wright S (1965) The interpretation of population structure by F-statistics with special regard to systems of mating. Evolution 19:395–420. https://doi.org/10.2307/2406450Xiao M, Zhang Y, Chen X et al (2013) Transcriptome analysis based on next-generation sequencing of non-model plants producing specialized metabolites of biotechnological interest. J Biotechnol 166:122–134. https://doi.org/10.1016/j.jbiotec.2013.04.004Yan J, Yang X, Shah T et al (2010) High-throughput SNP genotyping with the Goldengate assay in maize. Mol Breed 25:441–451. https://doi.org/10.1007/s11032-009-9343-2Yang X, Xu Y, Shah T et al (2011) Comparison of SSRs and SNPs in assessment of genetic relatedness in maize. Genetica 139:1045–1054. https://doi.org/10.1007/s10709-011-9606-9Yu J, Zhang Z, Zhu C et al (2009) Simulation appraisal of the adequacy of number of background markers for relationship estimation in association mapping. Plant Genome 2:63. https://doi.org/10.3835/plantgenome2008.09.0009Zhan L, Paterson I, Fraser B (2016) MEGASAT: automated inference of microsatellite genotypes from sequence data. Ecol Resour, Mol. https://doi.org/10.1111/1755-0998.1256
Milagro limits and HAWC sensitivity for the rate-density of evaporating Primordial Black Holes
postprin
An estimate of the number of tropical tree species
The high species richness of tropical forests has long been recognized, yet there remains substantial uncertainty regarding the actual number of tropical tree species. Using a pantropical tree inventory database from closed canopy forests, consisting of 657,630 trees belonging to 11,371 species, we use a fitted value of Fisher’s alpha and an approximate pantropical stem total to estimate the minimum number of tropical forest tree species to fall between ∼40,000 and ∼53,000, i.e. at the high end of previous estimates. Contrary to common assumption, the Indo-Pacific region was found to be as species-rich as the Neotropics, with both regions having a minimum of ∼19,000–25,000 tree species. Continental Africa is relatively depauperate with a minimum of ∼4,500–6,000 tree species. Very few species are shared among the African, American, and the Indo-Pacific regions. We provide a methodological framework for estimating species richness in trees that may help refine species richness estimates of tree-dependent taxa
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