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Figure 4 in Rediscovery and description of Paramormyrops sphekodes (Sauvage, 1879) and a new cryptic Paramormyrops (Mormyridae: Osteoglossiformes) from the Ogooué River of Gabon using morphometrics, DNA sequencing and electrophysiology

Figure 4. The short EOD and SN4 Paramormyrops differ in the ratio of head length (HL) to head depth (HD) when measurements are taken from radiographs. (A) HLx/HDx is plotted against standard length for 41 specimens including short EOD specimens (n = 9, blue circles), SN4 specimens (n = 30, red squares) and the two existing types (* = lectotype of P. sphekodes and 'x' = the paralectotype). Solid lines show linear regression lines showing that head shape changes little with overall size. The measurements of the lectotype (LT) of P. sphekodes (MNHN-A893) and paralectotype (PLT) (MNHN 1998-1050) identify the short EOD individuals as P. sphekodes. The specimens with SN4-type EODs belong to a new species (red * indicates the new species holotype). Specimen 1185 is shown in x-ray in C. (B) Non-overlapping histograms of HLx/ HDx allow for good diagnosis of the two EOD types even if no EOD is available, as with the two types of P. sphekodes. (C) Radiographs of two specimens (Specimen CUMV 98134 tag number JPS-1185, an SN4 fish and MNHN-A893) illustrate landmarks used for measuring HLx and HDx (see Material and Methods). Scale bars = 1 cm.

Figure 10 in Rediscovery and description of Paramormyrops sphekodes (Sauvage, 1879) and a new cryptic Paramormyrops (Mormyridae: Osteoglossiformes) from the Ogooué River of Gabon using morphometrics, DNA sequencing and electrophysiology

Figure 10. Distribution map of West-Central Africa showing collection localities of specimens of P. sphekodes (blue), P. ntotom sp. nov. (red) and P. curvifrons (green). Stars mark collection locations of holotypes (or lectotype) and circles mark locations of other specimens.

Figure 6 in Rediscovery and description of Paramormyrops sphekodes (Sauvage, 1879) and a new cryptic Paramormyrops (Mormyridae: Osteoglossiformes) from the Ogooué River of Gabon using morphometrics, DNA sequencing and electrophysiology

Figure 6. Relevant portion of the phylogram produced from maximum likelihood analysis in RAxML of cyt-b sequences from nine individuals of the 'short EOD' form (blue), eight specimens of species 'SN4' from the Doumé and Sébé sites (red) aligned to data matrix (73 Paramormyrops individuals) of Sullivan et al. (2002), rooted with sequence of M. ntemensis (not shown). Sequence of P. curvifrons individual is shown in green. For species codes, follow Sullivan et al. (2002). Bootstrap values are shown at nodes (filled circles). Haplotypes of SN4 and 'short EOD' do not constitute monophyletic groups. However, no haplotypes are shared between these forms and nowhere on the tree do haplotypes from the two forms appear as nearest relatives. This result is consistent with the hypothesis of heterospecificity of the two forms.

Figure 7 in Rediscovery and description of Paramormyrops sphekodes (Sauvage, 1879) and a new cryptic Paramormyrops (Mormyridae: Osteoglossiformes) from the Ogooué River of Gabon using morphometrics, DNA sequencing and electrophysiology

Figure 7. Five specimens of P. sphekodes from Ogooué basin of Gabon. From top to bottom: specimen tag number 1192, female, 113.5 mm; 1201, female, 111 mm from the Ogooué River at Doumé; 1214, male, 112.5 mm; 1230, male, 133 mm and 1238, male, 119 mm from the Sébé River nearby. Scale bars = 1 cm.

Figure 3 in Rediscovery and description of Paramormyrops sphekodes (Sauvage, 1879) and a new cryptic Paramormyrops (Mormyridae: Osteoglossiformes) from the Ogooué River of Gabon using morphometrics, DNA sequencing and electrophysiology

Figure 3. The Paramormyrops specimens with short EODs, and those called SN4 have overlapping meristics but differ in a number of morphometric ratios. Here, the short EOD specimens are shown as blue circles, while '*' indicates the lectotype of P. sphekodes and '+' indicates the paralectotype. The red circles show those with longer EODs referred to as SN4 specimens. The short EOD forms have elevated ratios of interorbital width to snout length and correspondingly blunter snout angles than the SN4 specimens. They also have slightly reduced caudal peduncle depth to length ratios. There is overlap in each ratio taken separately, but combined they provide a convenient morphological basis for diagnosis between these two EOD types. EOD traces are 10 ms long.

Figure 1 in Rediscovery and description of Paramormyrops sphekodes (Sauvage, 1879) and a new cryptic Paramormyrops (Mormyridae: Osteoglossiformes) from the Ogooué River of Gabon using morphometrics, DNA sequencing and electrophysiology

Figure 1. (A) Paramormyrops sphekodes (Sauvage, 1877) MNHN A.893 photographed in 1984 by W. Harder at which time the lot contained two specimens, suspended vertically in a tall jar from a glass floater. The original MNHN catalogue shows two specimens accessioned in 1878 under this number. The larger specimen (SL = 113.8 mm) is currently catalogued as A 893; the smaller specimen (SL = 98.7 mm) was subsequently catalogued in 1998 as MNHN 1050-1998. Sauvage's original description indicates multiple specimens with a largest of 140 mm total length, but he designated no holotype. We regard these specimens as syntypes prior to our designation of the larger as lectotype. (B) Radiograph of MNHN A893.

Figure 2 in Rediscovery and description of Paramormyrops sphekodes (Sauvage, 1879) and a new cryptic Paramormyrops (Mormyridae: Osteoglossiformes) from the Ogooué River of Gabon using morphometrics, DNA sequencing and electrophysiology

Figure 2. Electric organ discharge (EOD) waveforms recorded from 40 specimens of P. sphekodes-like mormyrids from the Ogooué River Basin of Gabon suggest the possibility of two species with distinct EOD waveforms. (A) For each specimen, EOD duration is plotted against standard length (SL). (B) Histogram of EOD durations reveals two modal peaks: one for short EODs, <2 ms duration, and one for longer EODs,> 2 ms. (C) EOD waveforms of longer (above) and shorter duration (below) are superimposed after each EOD's amplitude is normalized to the same peak-to-peak height and centred on the zero-crossing between positive and negative peaks. Blue lines are males and red lines are females. Head positivity is upward. EOD duration is measured between T1 and T2 (in E), first and last points of the waveform that deviate above or below the baseline by more than 2% of the peak-to-peak height. In previous publications, the longer EOD type was referred to by the code name 'SN4'. The fish with the 'short EOD' waveform is new to this study. (D) Histograms of SLs of all 40 specimens separated by EOD-type and by sex/age class show that within each EOD type there are males recognized by their dimorphic anal fins. Within each group, males tend to have the longest duration waveforms. This sex difference is especially pronounced for SN4 males recorded during the breeding season. Fish of both EOD types co-occur at two sites in Gabon: the main channel of the Ogooué River at Doumé and the Sébé River nearby (see map). (E) EOD waveform of specimen CUMV 98177 tag JPS-1238 showing how EOD duration is measured.

Figure 5 in Rediscovery and description of Paramormyrops sphekodes (Sauvage, 1879) and a new cryptic Paramormyrops (Mormyridae: Osteoglossiformes) from the Ogooué River of Gabon using morphometrics, DNA sequencing and electrophysiology

Figure 5. Morphometrics and ratios from the three species of Paramormyrops included in this study. (A–C) and (E–G) show measurement ratios useful in diagnosis of these three species. Snout angle measurements (see Material and Methods) are compared in (D) and (G). (D) plots snout angle against IOW/SNL. Holotypes or lectotypes are indicated by '*' symbols and paratypes are indicated by 'x' symbols. (H) compares IOW/SNL for specimens of differing standard lengths. Superimposed on the data points in (A–C) and (E–G) are box plots showing range, 25% quartile, median and 75% quartile. Black bars above box plots span samples where means differ significantly (P ≤ 0.05) using Tukey–Kramer multiple comparison tests for differences in sample means. See Table 1 for abbreviations.

16S rDNA sequence data of research--Different periods of high-fat diet during peri-pregnancy cause variant offspring gut microbiota

These are the 16S rRNA gene sequencing data based on the Illumina HiSeq2500 platform. Group a, b, c, d stand for group CD-CD, CD-HFD, HFD-CD, HFD-HFD separately. Each mouse of one group had two samples such as a1_1 and a1_2.

Supplementary File to "Both binding strength and evolutionary accessibility affect the population frequency of transcription factor binding sequences in Arabidopsis thaliana" (Genome Biology and Evolution)

This data is supplementary file 1 of the following publication: Schweizer G, Wagner A. "Both binding strength and evolutionary accessibility affect the population frequency of transcription factor binding sequences in Arabidopsis thaliana" (Genome Biology and Evolution)

FIG. 2 in First record of Bursaphelenchus hildegardae Braasch et al., 2006 (Nematoda) in New Zealand with updated information on morphology, sequencing and a key to species of the eggersi-group

FIG. 2. Light microscope photographs of Bursaphelenchus hildegardae. A: Anterior part of female; B–C:Vulva with flap; D: Female tail; E: Anterior part of male; F: Male lateral lines; G–J: Male spicules, busa & Tail. (Scale bars: A–J = 10 μm)

FIG. 6 in First record of Bursaphelenchus hildegardae Braasch et al., 2006 (Nematoda) in New Zealand with updated information on morphology, sequencing and a key to species of the eggersi-group

FIG. 6. Bayesian phylogenetic tree inferred from ITS gene region DNA sequences of Bursaphelenchus hildegardae. Posterior probabilities greater than 50% are given on appropriate clades. Nematode species, GenBank accession numbers and locations are listed for each taxon, if known.

FIG. 5. Bayesian phylogenetic tree inferred from D2D3 in First record of Bursaphelenchus hildegardae Braasch et al., 2006 (Nematoda) in New Zealand with updated information on morphology, sequencing and a key to species of the eggersi-group

FIG. 5. Bayesian phylogenetic tree inferred from D2D3 gene DNA sequences of Bursaphelenchus hildegardae. Posterior probabilities greater than 50% are given on appropriate clades. Nematode species, GenBank accession numbers and locations are listed for each taxon, if known.

FIG. 1. Bursaphelenchus hildegardae. A in First record of Bursaphelenchus hildegardae Braasch et al., 2006 (Nematoda) in New Zealand with updated information on morphology, sequencing and a key to species of the eggersi-group

FIG. 1. Bursaphelenchus hildegardae. A: Female; B: Male; C: Anterior part of female; D: Reproductive system of female; E: Posterior part of female; F: Spicules; G: Bursa; H: Posterior end of male; I: Lateral lines. (Scale bars: A–C = 50 μm; D–I = 20 μm)

FIG. 4 in First record of Bursaphelenchus hildegardae Braasch et al., 2006 (Nematoda) in New Zealand with updated information on morphology, sequencing and a key to species of the eggersi-group

FIG. 4. Bayesian phylogenetic tree inferred from SSU gene DNA sequences of Bursaphelenchus hildegardae. Posterior probabilities greater than 50% are given on appropriate clades. Nematode species, GenBank accession numbers and locations are listed for each taxon, if known.

FIG. 3 in First record of Bursaphelenchus hildegardae Braasch et al., 2006 (Nematoda) in New Zealand with updated information on morphology, sequencing and a key to species of the eggersi-group

FIG. 3. Light microscope photographs of Bursaphelenchus hildegardae. Dauer juvenile. A–B: Anterior part; C–D: Posterior part. (Scale bars: A–D = 10 μm)

Single-cell RNA sequencing of CNS-infiltrating HSC-derived phagocytes of Ms4a3Ai14, BM chimeric mice (CD45.2 Csf2rb-/-: CD45.1 Csf2rb+/+ and CD45.2 Ifngr1-/-: CD45.1 Ifngr1+/+) using 10X Genomics platform. IFN-γ and GM-CSF control complementary differentiation programs in the monocyte to phagocyte transition during neuroinflammation.

Single-cell RNA sequencing of CNS-infiltrating HSC-derived phagocytes of Ms4a3Ai14 at onset and peak EAE,  BM chimeric mice (CD45.2 Csf2rb-/-: CD45.1 Csf2rb+/+ and CD45.2 Ifngr1-/-: CD45.1 Ifngr1+/+) using 10X Genomics platform. The sorted cells were loaded into 10x Genomics Chromium in parallel. Libraries were prepared as per the manufacturer's protocol (Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 protocol) and sequenced on an Illumina NovaSeq sequencer according to 10X Genomics recommendations (paired-end reads, R1=28, i7=8, R2=91) to a depth of around 50,000 reads per cell. Initial processing was done using Cell Ranger (v3.1.0) mkfastq and count (reads were aligned to GENCODE reference build GRCm38.p6 Release M23 with added tdTomato sequence for the dataset from Ms4a3Ai14 mouse and collapse UMIs). Starting from the filtered gene-cell count matrix produced by CellRranger's in-built cell calling algorithms, we proceeded with Seurat v4 workflow.

Single-cell RNA sequencing of Lymph node-infiltrating HSC-derived phagocytes of Ms4a3Ai14 using 10X Genomics platform. IFN-γ and GM-CSF control complementary differentiation programs in the monocyte to phagocyte transition during neuroinflammation.

Single-cell RNA sequencing of Lymph node-infiltrating HSC-derived phagocytes of Ms4a3Ai14 at onset and peak EAE using 10X Genomics platform. The sorted cells were loaded into 10x Genomics Chromium in parallel. Libraries were prepared as per the manufacturer's protocol (Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 protocol) and sequenced on an Illumina NovaSeq sequencer according to 10X Genomics recommendations (paired-end reads, R1=28, i7=8, R2=91) to a depth of around 50,000 reads per cell. Initial processing was done using Cell Ranger (v3.1.0) mkfastq and count (reads were aligned to GENCODE reference build GRCm38.p6 Release M23 with added tdTomato sequence for the dataset from Ms4a3Ai14 mouse and collapse UMIs). Starting from the filtered gene-cell count matrix produced by CellRranger's in-built cell calling algorithms, we proceeded with Seurat v4 workflow.

Single-cell RNA sequencing of Bone Marrow-infiltrating HSC-derived phagocytes of Ms4a3Ai14 using 10X Genomics platform. IFN-γ and GM-CSF control complementary differentiation programs in the monocyte to phagocyte transition during neuroinflammation.

Single-cell RNA sequencing of Bone Marrow-infiltrating HSC-derived phagocytes of Ms4a3Ai14 at onset and peak EAE using 10X Genomics platform. The sorted cells were loaded into 10x Genomics Chromium in parallel. Libraries were prepared as per the manufacturer's protocol (Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 protocol) and sequenced on an Illumina NovaSeq sequencer according to 10X Genomics recommendations (paired-end reads, R1=28, i7=8, R2=91) to a depth of around 50,000 reads per cell. Initial processing was done using Cell Ranger (v3.1.0) mkfastq and count (reads were aligned to GENCODE reference build GRCm38.p6 Release M23 with added tdTomato sequence for the dataset from Ms4a3Ai14 mouse and collapse UMIs). Starting from the filtered gene-cell count matrix produced by CellRranger's in-built cell calling algorithms, we proceeded with Seurat v4 workflow.

Single-cell RNA sequencing of Blood-infiltrating HSC-derived phagocytes of Ms4a3Ai14 using 10X Genomics platform. IFN-γ and GM-CSF control complementary differentiation programs in the monocyte to phagocyte transition during neuroinflammation.

Single-cell RNA sequencing of Blood-infiltrating HSC-derived phagocytes of Ms4a3Ai14 at onset and peak EAE using 10X Genomics platform. The sorted cells were loaded into 10x Genomics Chromium in parallel. Libraries were prepared as per the manufacturer's protocol (Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 protocol) and sequenced on an Illumina NovaSeq sequencer according to 10X Genomics recommendations (paired-end reads, R1=28, i7=8, R2=91) to a depth of around 50,000 reads per cell. Initial processing was done using Cell Ranger (v3.1.0) mkfastq and count (reads were aligned to GENCODE reference build GRCm38.p6 Release M23 with added tdTomato sequence for the dataset from Ms4a3Ai14 mouse and collapse UMIs). Starting from the filtered gene-cell count matrix produced by CellRranger's in-built cell calling algorithms, we proceeded with Seurat v4 workflow.