Some features of free-living microorganisms and obligate parasites.

<p>Some features of free-living microorganisms and obligate parasites.</p

Estimation of the quality of the mapping onto KEGG maps by performing a re-prediction of the annotation of <i>S. pombe</i> proteome through intermediary data set consisting of one, two, three, or 18 fungal proteomes.

<p>The KO - <i>S. pombe</i> association pairs obtained by “blasting” an intermediary data set were evaluated <i>a posteriori</i> as true positive (TP) or false positive (FP) according to the KO - <i>S. pombe</i> mapping which is provided by KEGG. Those missed KO - <i>S. pombe</i> pairs existing in KEGG were taken as false negatives (FN). The overall quality of the obtained mapping can be expressed in terms of precision TP/(TP+FP) and recall TP/(TP+FN).</p

Number of enzymes dedicated to the biosyntheses of amino acids identified in <i>P. carinii</i> and <i>S. pombe</i>^a.

a<p>The reference gene numbers of <i>S. pombe</i> are those obtained from KEGG.</p>b<p>The four enzymes are the same for Ile and Val syntheses.</p>c<p>One of the enzymes is also involved in Ile and Val syntheses.</p

Proteomes investigated for transfer the KEGG annotations of the <i>P. carinii</i> predicted proteome.

<p>Proteomes investigated for transfer the KEGG annotations of the <i>P. carinii</i> predicted proteome.</p

Fungal OTUs distribution in plots

Fungal OTUs distribution in plot

Plant and environmental data

Plant species (frequency estimate) and environmental data in each of the 212 plots used in Pellissier et al. (In Review) Mol. Ecol

ITS1 sequences from soil

ITS1 sequences coming from the soil of 204 plots have been obtained with the fungal universal primers ITS1F ITS2. The pyrosequencing outputs of six half 454 runs have been pooled in this unique fasta file. The number of each half of run (R meaning run and H meaning half) and of each MID used are mentionned in the name of each sequence. More information is provided on the information associated to these sequences in the "readme.txt" fil

Study design.

<p>Thirty-three BXD lines plus the 2 parental strains and their reciprocal F1 progeny were phenotyped. Mice were submitted to either one of 2 experiments. In Experiment 1 (left), EEG/EMG signals and LMA were recorded under standard 12:12 h light–dark conditions (white and black bars under top-left panel) for 2 baseline days (B1, B2), a 6 h SD (red bar) from ZT0–6 (ZT0 = light onset), followed by 2 recovery days (R1, R2). The deep sleep-wake phenome consists of 341 sleep-wake state-, LMA-, and EEG-related phenotypes quantified in each mouse, among which time spent in NREM sleep (gray area spans mean maximum and minimum NREM sleep time among BXD lines, respectively, for consecutive 90 min intervals). Mice in Experiment 2 (right) were used to collect cortex, liver, and blood samples at ZT6. Half of the mice were challenged with an SD as in Experiment 1, the other half were left undisturbed and served as controls (labeled Ctr). Cortex and liver samples were used to quantify gene expression by RNA-seq, blood samples for a targeted analysis of 124 metabolites by LC/MS, or with FIA/MS. For <i>ph</i>QTLs, <i>m</i>QTLs, and <i>e</i>QTLs, a high-density genotype dataset (Genome; approximately 11,000 SNPs) was created, merging identified RNA-seq variants with a publicly available database (<a href="http://www.genenetwork.org/" target="_blank">www.genenetwork.org</a>). The entirety of the multilevel dataset was integrated in a systems genetics analysis to chart molecular pathways underlying the many facets of sleep and the EEG, using newly developed computational tools to interactively visualize the results and pathways, and to prioritize candidate genes. EEG/EMG, electroencephalography/electromyogram; <i>e</i>QTL, expression quantitative trait locus; FIA/MS, flow injection analysis/mass spectrometry; LC/MS, liquid chromatography/mass spectrometry; LMA, locomotor activity; <i>m</i>QTL, metabolic quantitative trait locus; NREM, non-REM; <i>ph</i>QTL, phenotypic quantitative trait locus; RNA-seq, RNA sequencing; SD, sleep deprivation; ZT, zeitgeber time.</p

Genetic diversity in the BXD panel greatly impacts behavioral, metabolic, and molecular traits.

<p>The phenome was divided into 3 phenotypic categories: (i) LMA, (ii) EEG features (labeled EEG), and (iii) sleep-wake state characteristics (labeled State), which were subdivided further (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2005750#sec015" target="_blank">Materials and methods</a>). The 5 classes of metabolites and the gene expression represent intermediate molecular phenotypic categories. (A) Heritability for EEG/behavioral and metabolite phenotypes. Dots represent single phenotypes within each category and subcategory indicated along the x-axis. Red dots represent phenotypes recorded in baseline (labeled bsl; B1 and B2), blue in recovery (labeled rec; R1 and R2), purple during SD, and green dots refer to the recovery-to-baseline contrasts. Values represent narrow-sense heritability. (B) Overview of significant and highly suggestive (FDR < 0.1) QTLs obtained for all 341 EEG/behavioral phenotypes (<i>ph</i>QTLs: LMA in red, EEG in blue, and sleep-wake state in green) and 124 blood metabolite levels in baseline and recovery (<i>m</i>QTLs; purple). Note that overlap of neighboring QTLs renders color shading darker. (C) Venn diagram of genes under significant <i>cis-e</i>QTL effect in liver and cortex for the two experimental conditions (SD and controls [labeled Ctr]). EEG, electroencephalography; <i>e</i>QTL, expression quantitative trait locus; FDR, false discovery rate; LMA, locomotor activity; <i>m</i>QTL, metabolic quantitative trait locus; <i>ph</i>QTL, phenotypic quantitative trait locus; QTL, quantitative trait locus; SD, sleep deprivation.</p

EEG delta power in NREM sleep after SD is associated with <i>Kif16b</i> and <i>Wrn</i>.

<p>(A) NREM sleep EEG spectra in the first 3 h after SD (ZT6–9) for the 2 BXD lines that displayed the lowest and highest EEG activity in the fast delta frequency band (2.5–4.25 Hz, δ2; top, see panel E) and for the 2 BXD lines that displayed the smallest and largest increase (or gain) in EEG power in the slow delta band (1.0–2.25 Hz, δ1; bottom, see panel E). Spectra were “1/f-corrected” (and therefore not directly comparable to the values in panel E) for better visualization of activity in higher frequency bands (theta [5–9 Hz, θ], sigma [11–16 Hz, σ], beta [18–30 Hz, β], and slow [32–55 Hz, γ1] and fast gamma [55–80 Hz, γ2]). Subsequent analyses were performed without this correction. (B) QTL mapping and prioritization for δ2 power identified a significant association on chromosome 2 and <i>Kif16b</i> in cortex as top-ranked gene (top). For the δ1 increase after SD, we obtained a suggestive QTL on chromosome 8 and a significant prioritization score for the DNA-helicase <i>Wrn</i>. (C) Hiveplot visualization of network connections for the δ1 and δ2 power after SD (top-left panels) and the SD-induced increase in δ1 and δ2 power over baseline (bottom-left panels). Note the marked differences in the networks and QTLs regulating the expression of these 2 delta bands. Right hiveplots highlight <i>Kif16b</i> in the δ2 power–associated network (top), and <i>Wrn</i> in the network associated with the δ1 increase (bottom). Only <i>Kif16b</i> expression in the cortex was linked to the chromosome 2 <i>cis</i>-<i>e</i>QTL and was not associated with any metabolite. <i>Wrn</i> expression was significantly linked to the chromosome 8 <i>cis-e</i>QTL and to the long phosphatidylcholine, PC-ae-C38:5. (D) <i>Kif16b</i> is highly significantly down-regulated in cortex (left), while it remains unchanged in liver after SD (<i>p</i> = 0.15; not shown). Also, <i>Wrn</i> expression was strongly down-regulated by SD in cortex (right) and only marginally so, albeit significantly, in liver (<i>p</i> = 0.02; not shown). (E) Strain distribution patterns. BXD lines carrying a <i>B6-</i>allele on the chromosome 2–associated region showed higher δ2 power after SD (left) and a significantly higher <i>Kif16b</i> expression (<i>p</i> = 1.3e−15; second to left) than <i>D2-</i>allele carriers. <i>D2-</i>allele carriers of the chromosome 8–associated region showed a larger δ1 increase after SD (second to right) as well as a significantly larger decrease in <i>Wrn</i> expression after SD (right) than <i>B6-</i>allele carriers. For color-coding of genotypes, see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2005750#pbio.2005750.g004" target="_blank">Fig 4</a>. CPM, counts per million; Ctr, control; EEG, electroencephalography; <i>e</i>QTL, expression quantitative trait locus; FDR, false discovery rate; <i>Kif16b</i>, <i>Kinesin family member 16B</i>; NREM, non-REM; PC-ae, phosphatidylcholine acyl-alkyl; QTL, quantitative trait locus; SD, sleep deprivation; <i>Wrn</i>, <i>Werner syndrome RecQ like helicase</i>; ZT, zeitgeber time</p