dataesr/scientific-paragraphs-categorization huggingface dataset:
Gene functional representation We detected a total of 7027 GO categories in our dataset of which a number were significantly over-and under-represented rsob. royalsocietypublishing. org Open Biol 3: 130063 (Fisher's exact test) relative to the full zebra finch Ensembl gene set (figures 2 and 3; electronic supplementary material, table  S1 ). Terms describing cellular components including endoplasmic reticulum ( p ¼ 1. 3 Â 10 26 ), cytoplasm ( p ¼ 8. 3 Â 10 236 ) and cytosol ( p ¼ 8. 4 Â 10 28 ) were significantly enriched. As might be expected of a brain-derived library, categories of neurobiological function were also enriched (axon, p ¼ 0. 0001; dendrite, p ¼ 0. 0048; neuronal cell body, p ¼ 0. 019). A broad group of categories related to RNA processing and translation were also enriched.
0. 8 (112 genes) and the overall top 10% most rapidly evolving genes (530 genes; v. 0. 4075). At v. 0. 8, three GO categories (spindle astral microtubule organization, interkinetic nuclear migration and regulation of microtubule-based process) were significant ( p , 0. 05). GO categories neurogenesis, NADH dehydrogenase activity and cerebral cortex development bordered on statistical significance ( p ¼ 0. 075). Among the top 10%, no GO categories were significant after correction for multiple comparisons. Four genes annotated as having cytokine receptor activity (out of six total such genes in the dataset) were in the top 10% of fastestevolving genes, and this category also bordered on statistical significance ( p ¼ 0. 12). Several functional categories were also moderately under-represented, suggesting stabilizing selection on the genes comprising these categories (protein serine/threonine kinase activity, protein tyrosine kinase activity, protein amino acid phosphorylation and protein kinase activity, 0.
rsob. royalsocietypublishing. org Open Biol 3: 130063 To estimate rates of evolution across the genome as a whole, we generated bootstrap datasets (see Material and methods) from pairwise alignments of each of our ingroup taxa (zebra finch and violet-eared waxbill) with an outgroup, the great tit. In each case, we estimated the average genomic v between to be 0. 13. Therefore, we found no difference in overall molecular rate between the two estrildid finch lineages. We also found a significant correlation between v estimated from zebra finch/chicken orthologues in Ensembl and zebra finch/waxbill orthologues estimated here (R ¼ 0. 35, p , 0. 001; figure  6 ), supporting broadly similar patterns of molecular evolution at these different time scales.
Immune genes were in fact significantly under-represented in our dataset as a whole (figure  2 ). Analyses of complete avian genomes, however, also failed to detect this common signature  [17]. Nam et al. [17]  attributed this to the fact that in their study, evolutionary comparisons of divergent species diluted the signature of adaptive bouts of evolution. Immune genes, however, have been shown to be evolving rapidly on relatively recent time scales in comparisons of turkey and chicken genomes  [9]. Enhancing the waxbill brain transcriptome with genes better represented in other tissue (e. g. spleen and gonads) might help us to test for positive selection in immune-and reproduction-related genes. Our study used 'branch' models to identify genes that show a signature of accelerated evolution across the entire gene.
Acknowledgements. Jim Goodson  provided the waxbill brain tissue sample used in this study. Aakrosh Ratan  provided guidance in the use of DIAL software. Sequencing, assembly and preliminary annotation was performed at the  Roy J. Carver Biotechnology Center at the University of Illinois by Alvaro Hernandez ,  Jyothi Thimapurram  and their staff. Funding statement. This work was funded by  NIH NIGMS   1RC1GM091556  and  East Carolina University.
Immunostained proteins were revealed using a chemoluminescent substrate (Millipore). Densitometric analysis on the immunoblots was quantified by Bio-1D software. The experiments were repeated at least three times, and representative autoradiograms are shown. Analysis of degradation of long-lived proteins. This assay was adapted from Bauvy et al. 52  72 h after siRNA transfection, HeLa cells were incubated for 24 h at 37°C with 0. 2 μCi/ml As mentioned in the Introduction, recent information indicates that the v-ATPase in the lysosomal membrane acts as an amino acid sensor and that it responds to the level of amino acids within the lysosomal lumen. 13 This level is determined by the cytosolic amino acid concentration, the rate of proteolysis within the lysosome (e. g. , by autophagy, which was not considered in these studies) and the rate of amino acid transport out of the lysosomes.
51 Our results on the role of GLUD in the regulation of autophagic flux and MTOR signaling are in line with the data of Duran et al. ,  51  and further extend their observations by demonstrating that flux through GLUD1 exerts control over autophagy by limiting the accumulation of ROS. Invitrogen, 11140) and a 50× stock solution of essential AA (Gibco/Invitrogen, 11130) with glutamine (20 mM) and HEPES (50 mM) added and sufficient NaOH to neutralize the pH of this acidic mixture. After the preincubation plus or minus AA, the cells (in 300 μl aliquots) were transferred to tubes containing 1 μl DHE (1. 5 mM, dissolved in DMSO) or, in subsequent experiments, to tubes containing 1 μl MitoSOX (300 μM, dissolved in DMSO). Samples were analyzed without washing on a FACS Calibur (BD BioSciences) and results of 6000 events were expressed as mean fluorescence intensity (MFI) in the red (FL3) channel.
Acknowledgments This paper is dedicated to the memory of  Prof. Joseph M. Tager , the teacher of two of us (A. J. M. , A. J. V. ), who died in February 2011. His studies on glutamate dehydrogenase in the 1960s have been fundamental to our idea that this enzyme might influence signaling in a manner that differs from its traditional function in ammonia metabolism. The authors are grateful to  Dr. S. P. J. Albracht  for sharing his ideas concerning the role of the mitochondrial respiratory chain, and that of Complex I in particular, in the production of ROS. The authors also thank  Dr. M. P. Murphy  ( MRC, Cambridge, UK ) for his kind gift of, and expert advice on, MitoQ and  V. Keizer  for her contribution to the ROS measurements. Work in P. Codogno's laboratory is supported by institutional funding from the  Institut National de la Santé et de la Recherche Médicale (INSERM) , grants from the  Agence Nationale de la Recherche (ANR)  and the  Institut National du Cancer (INCa).
This resulted in the generation of three linkage maps based on SNP markers: one from the parental genotype of the F2 population (1,131 markers in 1,708 centimorgan (cM)), and one for each parent of the G2 population (1,015 and 1,110 markers in 1,447 and 1,425 cM for the female and male parents, respectively). A comparison of segregation patterns in the progeny obtained from the two types of mating (inbreeding and outbreeding) led to the identification of a chromosomal region carrying an embryo viability locus with a semi-lethal allele. Following selfing and segregation, zygote mortality resulted in a deficit of Corsican homozygous genotypes in the F2 population. This dataset was also used to study the extent and distribution of meiotic recombination along the length of the chromosomes and the effect of sex and/or genetic background on recombination.
SNP-assay genotyping statistics We used the maritime pine unigene set to develop a 12 k SNP array for use in genetic linkage mapping. The mean call rate (percentage of valid genotype calls) was 91% and 94% for the G2 and F2 mapping populations, respectively. Samples that performed poorly were identified by plotting the sample call rate against the 10%GeneCall score. In total, four samples from the G2 population and one sample from the F2 population were found to have low call rates and 10% GC scores and were excluded from further analysis. We thus genotyped 83 and 69 offspring for the G2 and F2 populations, respectively. Poorly performing loci are generally excluded on the basis of the GenTrain and Cluster separation scores obtained when Genome studio software is applied to the whole dataset.
In a preliminary study, thresholds of ClusterSep score <0. 6 and GenTrain score <0. 4 were used to exclude loci with a poor performance. However, visual inspection clearly revealed the presence of SNPs that performed well but had low scores. Conversely, some poorly performing loci had scores above these thresholds. We, therefore, decided to inspect all the scatter plots for the 9,279 SNPs by eye. Three people were responsible for this task and any dubious SNP graphs were noted and double-checked. Overall, 2,156 (23. 2%) and 2,276 (24. 5%) of the SNPs were considered to have performed poorly in the G2 and F2 populations, respectively. Surprisingly, a significant number of poorly performing SNPs were not common to the two datasets. Cases of well-defined polymorphic locus in one pedigree that performed poorly in the other pedigree could be classified into four categories [see Additional file 1 for their occurrence]: -Multiple closely located clusters, also referred to as cluster compression (illustrated in Figure  1A ).
4% for the G2 population and 13. 1% for the F2 population. The conversion rates for SNPs resulting in nucleotide replacement were 35% for the G2 population and 18% for the F2 population, whereas those for 1 bp indel mutations were almost zero (1. 8% for G2 and 1% for F2). Indels should, therefore, be avoided when designing an Infinium assay on the basis of 454 reads. Polymorphic SNPs were made available through the National Center for Biotechnology Information (NCBI) dbSNP database  [23]. The accession numbers are listed in Additional file 2.
G2 mapping population The following numbers of test-cross SNP markers/contigs were available from the 12 k SNP assay in the G2 pedigree [see Additional file 6]: 760 SNPs in 543 contigs (G2F) and 900 SNPs in 615 contigs (G2M), from which a total of 442 and 500 loci (that is, contigs) were mapped as framework markers (map 1, that is, the most reliable map established by JoinMap software, see methods section) in the female and male maps, respectively. Including the markers already available (SNPs, simple sequence repeats (SSRs) and EST-Ps), we eventually mapped a total of 550 and 619 markers on the G2F and G2M maps, respectively, 25 of these loci being common to both maps (indicated by dashed green lines in Figure  2  and Additional file 3). Accessory test-cross (56 and 82 loci for G2F and G2M, respectively) or intercross (409 loci) markers were localized to their most probable framework marker location (indicated in blue in Figure  2  and Additional file 3).
Given the low information content assigned to pairs of markers segregating in 1:1 and 1:2:1 ratios  [24] , only markers showing multiple parallel linkages were retained. Overall, 1,015 and LG2_G2M Figure  2  Example of linkage group (LG2) obtained from segregation data for the G2 and F2 mapping populations. Markers common to the G2 female (G2F), G2 male (G2M) and F2 maps are linked by green dashed lines. Framework markers (segregating in a 1:1 ratio) are indicated in black, whereas accessory markers (segregating in a 1:2:1 ratio) are indicated in blue followed, in brackets, by the distance (in cM) to the nearest framework marker and the corresponding LOD score. Markers displaying segregation distortion in the initial dataset are indicated with an asterisk (*). The whole map is available in Additional file 3.
Unigene set In a recent review, McKay et al. [5]  summarized the transcriptomic resources currently available for the five best-studied coniferous genera. For maritime pine, the first unigene set was derived from 30 k Sanger ESTs and contained 4,483 contigs and 9,247 singletons  [25]  gene model is available. We will not discuss the content of version#3 further here, because the three datasets were merged together (as they used essentially different sequence reads: Sanger, 454, Illumina) to obtain a large annotated catalog of full-length cDNAs. In the absence of a sequence genome for a conifer, such a catalog will serve as a reference for guiding the assembly of further short-read sequences. This approach is considered the most cost-effective method for both: i) gene expression profiling  [28]  to determine the molecular mechanisms involved in tree growth and adaptation (for example,  [29] ); and ii) polymorphism detection  [30, 31]  for applications in evolutionary ecology (for example,  [12] ), conservation and breeding (for example,  [13] ).
They observed no significant SD for loci in the dataset resulting from selfing, suggesting that gametic selection, leading to gamete abortion or lower gamete fitness, can be ruled out as a possible cause of SD in this study. Genomic regions containing lethal or sublethal alleles have already been detected in several conifers, through linkage mapping approaches (reviewed in Williams  [21] ). The number of such lethal or sublethal equivalents is generally high in populations, as revealed by the typical high level of inbreeding depression in these outcrossing species (reviewed by Williams and Savolainen  [42] ), but their severity varies in the population, with some genotypes (like that selected in this study) bearing mutations that are, a priori, less deleterious than others. The nature of the underlying loci remains unclear.
Bioinformatic analysis Development of genomic resources Sanger ESTs were available from the sequencing of 12 suppressive subtractive hybridization (SSH) and/or conventional cDNA libraries  [25]. In this study, pyrosequencing (454 titanium, Roche, Branford, CT, USA) was also conducted for 15 additional cDNA libraries. A description of the libraries generated is provided in Additional file 14. It should be noted that (i) maritime pine libraries were derived from several genotypes and correspond to different tissues (differentiating xylem, roots, bud, needles and somatic embryo) or different experimental treatments (that is, drought-stressed plant), and (ii) that most of the sequences (97%) were obtained by the pyrosequencing approach. In addition, 2,358 Sanger ESTs (libraries 26235, 26097 and 12219 in Additional file 14) were recovered from the NCBI dbEST and Genbank databases.
Assembly procedure and annotation Sanger sequences and 454-reads were assembled with the SIGENAE pipeline [68] based on TGICL software [67], with the same parameters described by Ueno et al. [69]. This software uses the CAP3 assembler  [70] , which takes into account the quality of sequenced nucleotides when calculating the alignment score. The resulting unigene set was called 'PineContig_v2'. This unigene set was annotated by BLAST analysis against the following databases: Repeat sequences were detected with RepeatMasker. Contigs and annotations can be browsed and data mining carried out with BioMart, at  [22].
Detection of nucleotide polymorphism Four subsets of this vast body of data (detailed below) were screened for the development of the 12 k Illumina Infinium SNP array. A flowchart describing the steps involved in the identification of SNPs segregating in the Aquitaine population is shown in Figure  5. In silico SNPs detected in Aquitaine genotypes (set#1). In total, 685,926 sequences from Aquitaine genotypes (454 and Sanger reads) derived from 17 cDNA libraries were extracted from PineContig_v2 [see Additional  file 15]. We focused on this ecotype of maritime pine because our long-term objective is to carry out genomic selection in the breeding program focusing principally on this provenance. Data were cleaned with the SmartKitCleaner and Pyrocleaner tools  [65]. The remaining 584,089 reads were distributed into 42,682 contigs (10,830 singletons, 15,807 contigs with 2 to 4 reads, 6,871 contigs with 5 to 10 reads, 3,927 contigs with 11 to 20 reads, 5,247 contigs with more than 20 reads, Additional file 16).
SNP detection was performed for contigs containing more than 10 reads. A first Perl script ('mask') was used to mask singleton SNPs  [71]. A second Perl script, 'Remove' , was then used to remove the positions containing alignment gaps for all reads. The number of false positives was minimized by establishing a priority list of SNPs in the assay on the basis of MAF, depending on the depth of each SNP. Finally, based on these four different SNP sets, 10,593 SNPs (corresponding to 11,938 bead types, Additional file 17) were available for genotyping after filtering with the ADT of Illumina. All but three of the SNPs had a score above 0. 63.
SNP genotyping assay Genotyping was carried out at Genediffusion (Institut Pasteur, Lille, France) with the Illumina Infinium assay, used according to the manufacturer's instructions (Illumina). In total, 87 and 70 offspring were initially genotyped for the G2 and F2 mapping populations, respectively. The Infinium assay is based on the direct hybridization of genomic targets to array-bound sequences. Single-base extension is followed by fluorescence staining, signal amplification, scanning and analysis with Genome Studio software v. 1. 0. From the initial set of 10,593 SNPs, 1,314 (12. 4%) did not pass Illumina production quality control and were eliminated. The remaining 9,279 SNPs (6,299 SNPs sensu stricto and 2,980 indels distributed in 4,613 different contigs) were individually inspected with Genome Studio software, with a GenCall score cutoff of 0.
A single-base extension reaction is then performed, followed by an ion-exchange cleanup step. Finally, the products are detected in a MassArray mass spectrophotometer and the data are acquired in real time with MassArray RT software. Alleles were automatically assigned by MassArray TyperAnalyser 4. 0. 22 software and associated with a reliability value. Positive (hybrid parent of the F2 mapping population) and negative controls were including in the genotyping process. Visual inspection was carried out for all the SNPs, to detect any incorrect assignments made by the ' Autocluster' option of the MassArray Typer Analyser software. Finally, locus segregation was tested for goodness of fit to expected Mendelian segregation ratios, in Chi 2 tests (P ≤0. 01).
i) Reference databases: UniProtKB/Swiss-Prot Release August 2010, UniProtKB/ TrEMBL Release August 2010, RefSeq Protein of 8 June 2010, Pfam Release 24. 0 of July 2009 and RefSeq RNA of 8 June 2010; and ii) species-specific TIGR databases: Arabidopsis AGI 15. 0, Vitis VvGI 7. 0, Medicago MtGI 10. 0, TIGR Populus PplPGI 5. 0, Oryza OGI 18. 0, Picea SGI 4. 0, Helianthus HaGI 6. 0 and Nicotiana NtGI 6. 0.
Acknowledgments This study was carried out with financial support from the  ANR  ( ERANET SUSTAINPINE  project), the  European Commission , under  FP7  ( FP7-2118-68  NOVELTREE) and  FEDER  ( ABIOGEN  project  No. Presage 32973 ). EC and IL were supported by fellowships from  NOVELTREE  and SUSTAINPINE, respectively. We thank  Camille Lepoittevin  for assistance with SNP detection and  Emily Telfer  for advice concerning an earlier version of this manuscript. We also thank the experimental unit of  INRA Pierroton  for trial establishment at  Lacanau de Mios  and for measuring the survival and height growth of F2 trees. The Sequenom analysis was performed at the  Genomic and Sequencing Facility of Bordeaux  (grants from the  Conseil Regional d'Aquitaine : no. 20030304002FA  and  20040305003FA , from the  European Union :  FEDER  no.
2E ). We thus wondered whether the defect of this mutant in promoting actin cytoskeleton reorganization originated from its defect in invading HeLa cells. This was ruled out by treating HeLa cells with the E. coli CNF-1 toxin, that is known to promote internalization of bacteria in cultured cells  [19]. CNF-1 restored entry of the queF mutant without restoring actin cytoskeleton modifications (Fig. S4 ). Furthermore, the CNF-1 toxin promoted an increase in wild-type bacteria internalization, as compared to untreated cells, without exacerbating or accelerating the extent of cytoskeleton modifications (data not shown). This suggests that bacterial entry might not be required for cytoskeleton modifications. We assessed the symbiotic performances of the various S. meliloti queuosine deficient mutants on the model legume Medicago truncatula.
Acknowledgments We are very grateful to  Dr. Turlough Finan  for providing S. meliloti strains,  Dr. Susumu Nishimura  for providing the queuosine precursor preQ1,  Dr. Jacques Bertoglio  for providing the pGEX-RBD-rhotekin expression plasmid,  Dr. Florence Niedergang  for the (PAK)-Cdc42-Rac1 (CRIB) protein and  Dr Emmanuel Lemichez  for generous gift of CNF1 toxin.
Only studies performed with group housed pigs were used, any studies that used individual housing were excluded. For the comparisons incorporating anti-GnRF immunized males only studies that were performed with the commercial anti-GnRF vaccine, from Zoetis, and that utilized a 4 to 6 week post-second immunization period were used. Studies that used an experimental, non-commercially available anti-GnRF vaccine or that were purported to require a single immunization strategy were excluded. Only studies that reported a measure of variation from which a standard error of the difference could be derived were used. Where studies included treatments with ractopamine or somatotropin only, the data for the non-ractomamine/somatotropin controls were used. In addition, only studies that reported separate data from second immunization to slaughter as opposed to the entire growing/finishing period were included.
Optimized sequence capture led to a 4-fold increase in reads aligned to nonreference genome L1s per library compared to previous RC-seq based on solid-phase arrays and similar sequencing depth  (Baillie et al. , 2011). The improved resolution of RC-seq also allowed us to discriminate a required minimum of two unique amplicons in support of any nonreference genome insertion (see Extended Experimental Procedures). Frequent Retrotransposition in the Human Germline A total of 7,689 nonreference genome insertions were detected in 19 tumor (T) samples and 19 matched nontumor (NT) liver samples. Of these, we annotated 7,644 as putatively germline (Table  S3 ) because of their presence in (1) databases of retrotransposon-induced polymorphisms  (Beck et al. , 2010; Ewing and Kazazian, 2010; Iskow et al.
, 2010; Wang et al. , 2006) , (2) pre-existing insertions annotated by pooled blood RC-seq  (Baillie et al. , 2011) , (3) multiple individuals, or (4) nontumor liver. L1, Alu, SVA, and LTR-flanked retrotransposons comprised 13. 5%, 81. 8%, 4. 3%, and 0. 4% of germline insertions, respectively. As expected, L1-Ta and L1-pre-Ta (99. 3%) and AluY (99. 7%) were the main L1 and Alu subfamilies active in germ cells  (Mills et al. , 2007). A total of 2,241 germline insertions were found in only one individual each (Table  1  and Table S3 ) and were not annotated by the aforementioned retrotransposon polymorphism databases, suggesting that these were private or rare mutations or, alternatively, had occurred in early development  (Garcia-Perez et al. , 2007; Kano et al. , 2009). RC-seq detected 1,489 (66.
PCR Validation Germline retrotransposon insertions detected by RC-seq were first validated by a standard empty site/filled site PCR assay and then, if unsuccessful, with PCR targeting an insertion site 5 0 or 3 0 end. Tumor-specific insertions were characterized with a similar strategy but also incorporated 5 0 and 3 0 end capillary sequencing. All validation was performed on nonamplified DNA stored and handled separately from postamplification RC-seq products. Primers were designed using custom Python scripts and Primer3.