ampliconflow
Archive records ENA PRJNA361046 SRA PRJNA361046 BioProject PRJNA361046

opens the authoritative record at ENA, SRA or BioSample; this page never replaces it

PRJNA361046 released 25 Sept 2026

PRJNA361046

Pipeline 0.1.0 Contract v0.1 Licence CC-BY-4.0

Tags

derived from the release metadata, not hand-written

Study

The study record carries no description, and its registered title is the accession itself. The figures below are computed from the 60 released samples and 60 runs.

Samples
60
Runs
60
Collection
2014-12 to 2014-12

Linked publication

Community- and genome-based evidence for a shaping influence of redox potential on bacterial protein evolution.

10.1128/msystems.00014-23 · 2023 · via europepmc

Linked by the enrich stage. Fields taken from the paper: . No per-sample coordinates in the paper.

abstract

Despite deep interest in how environments shape microbial communities, whether redox conditions influence the sequence composition of genomes is not well known. We predicted that the carbon oxidation state (<i>Z</i><sub>C</sub>) of protein sequences would be positively correlated with redox potential (Eh). To test this prediction, we used taxonomic classifications for 68 publicly available 16S rRNA gene sequence data sets to estimate the abundances of archaeal and bacterial genomes in river & seawater, lake & pond, geothermal, hyperalkaline, groundwater, sediment, and soil environments. Locally, <i>Z</i><sub>C</sub> of community reference proteomes (i.e., all the protein sequences in each genome, weighted by taxonomic abundances but not by protein abundances) is positively correlated with Eh corrected to pH 7 (Eh7) for the majority of data sets for bacterial communities in each type of environment, and global-scale correlations are positive for bacterial communities in all environments. In contrast, archaeal communities show approximately equal frequencies of positive and negative correlations in individual data sets, and a positive pan-environmental correlation for archaea only emerges after limiting the analysis to samples with reported oxygen concentrations. These results provide empirical evidence that geochemistry modulates genome evolution and may have distinct effects on bacteria and archaea. IMPORTANCE The identification of environmental factors that influence the elemental composition of proteins has implications for understanding microbial evolution and biogeography. Millions of years of genome evolution may provide a route for protein sequences to attain incomplete equilibrium with their chemical environment. We developed new tests of this chemical adaptation hypothesis by analyzing trends of the carbon oxidation state of community reference proteomes for microbial communities in local- and global-scale redox gradients. The results provide evidence for widespread environmental shaping of the elemental composition of protein sequences at the community level and establish a rationale for using thermodynamic models as a window into geochemical effects on microbial community assembly and evolution.

Linked by the enrich stage from europepmc.

Location

sampling sites from the release coordinates
60sampling sites · drag to pan, scroll or pinch to zoom

Place name hierarchy

  1. ▸ 中国
  2. › 云南省
  3. › 会泽县

Districts named on the samples

  • 会泽县 1

Latitude 26.12 to 26.41, longitude 103.53 to 103.53. Names resolved with OpenStreetMap Nominatim from the release's own coordinates; Coordinates parsed from the released lat_lon text field, which the pipeline keeps but does not split into latitude/longitude columns.

How the sequences were obtained

sample to release
01 study metadata

Sample collection

60 samples, 2014-12 to 2014-12

26.1200 to 26.4100 N, 103.5300 to 103.5300 E

02 not reported

Storage

not reported

neither the archive nor the linked paper states storage conditions

03 not reported

Processing

not reported

no extraction kit or lysis protocol in the archive or the linked paper

04 per-run QC

PCR

16S rRNA V4

primers: trimmed; polymerase, cycle count and primer sequences are not stated in the linked paper

05 not reported

Sequencing preparation

not reported

no library kit or index strategy in the archive or the linked paper

06 study metadata

Sequencing

Illumina MiSeq

60 runs; PAIRED 253.0 bp reads; the linked paper's text supports 454

07 this release

Denoising

dada2 1.38.0

27,265 ASVs from 1,325,060 reads

ampliconflow branches off at step 6, Sequencing

this release

ampliconflow starts here: 1,325,060 reads from 60 runs, QC to 97.5% 16S identity and 98.0% above Q30, primers trimmed, dada2 1.38.0 to 27,265 ASVs, taxonomy against a SINTAX reference, then the release (CC-BY-4.0).

Steps 1 to 6 are how the sequences were obtained, from the study's own archive metadata. Step 7 is what the authors report doing with the sequences in the linked paper. ampliconflow starts at the deposited reads rather than repeating the wet lab.

Taxonomy assigned with SILVA 138.2. (SINTAX).

The linked paper's methods run to 21,799 characters. It supports: platform.

Conflict on sequencing platform: the release has Illumina MiSeq, the linked paper's text supports 454.

60

Samples

60 runs

27.3k

Features

OTUs at 97%

1.3M

Reads

mapped total

145 MB

Release size

149 files

Depth floor

1,000 reads

no samples below

QC warnings

60

100% of runs warned

Reads per sample

log scale
min
6,556
median
23,351
max
37,041

Feature detection

100.0% non-zero

27,265 / 27,265 features

Features with at least one observed read. The remainder are present in the reference set but not detected in these samples.

Composition

Top phyla

  • Chloroflexota 457,676 (34.5%)
  • Pseudomonadota 215,700 (16.3%)
  • Acidobacteriota 174,381 (13.2%)
  • Planctomycetota 65,549 (4.9%)
  • Actinomycetota 44,127 (3.3%)
  • Thermodesulfobacteriota 44,088 (3.3%)
  • Verrucomicrobiota 42,360 (3.2%)
  • Myxococcota 31,637 (2.4%)
  • Bacteroidota 30,783 (2.3%)
  • Methylomirabilota 25,337 (1.9%)
  • Nitrospirota 23,385 (1.8%)
  • Thermoproteota 16,197 (1.2%)
  • Bacillota 14,904 (1.1%)
  • Gemmatimonadota 14,282 (1.1%)
  • Cyanobacteriota 13,357 (1.0%)
  • Candidatus Eremiobacterota 9,596 (0.7%)
  • Latescibacterota 9,459 (0.7%)
  • Armatimonadota 9,089 (0.7%)
  • Campylobacterota 7,667 (0.6%)
  • Thermoplasmatota 7,390 (0.6%)

Top genera

  • Incertae Sedis 825,887 (62.3%)
  • RBG-16-58-14 41,863 (3.2%)
  • HSB OF53-F07 26,553 (2.0%)
  • Anaerolinea 20,142 (1.5%)
  • Thiobacillus 19,198 (1.4%)
  • Aminicenans 14,566 (1.1%)
  • Candidatus Udaeobacter 12,672 (1.0%)
  • Leptolinea 11,077 (0.8%)
  • Anaeromyxobacter 10,813 (0.8%)
  • Candidatus Solibacter 10,159 (0.8%)
  • Sh765B-TzT-35 9,156 (0.7%)
  • Acidothermus 8,849 (0.7%)
  • Desulfobacca 8,696 (0.7%)
  • Sulfurifustis 8,147 (0.6%)
  • Gallionella 6,368 (0.5%)
  • Sphingomonas 6,283 (0.5%)
  • Aggregatilinea 5,872 (0.4%)
  • Bryobacter 5,703 (0.4%)
  • Acidibacter 5,678 (0.4%)
  • Sideroxydans 5,640 (0.4%)

Rank-abundance

log-log
1 10 100 1k 1 10 100 ASV_1 · Incertae Sedis: 8195 reads ASV_2 · Incertae Sedis: 3628 reads ASV_3 · Incertae Sedis: 3024 reads ASV_4 · Incertae Sedis: 2442 reads ASV_5 · RBG-16-58-14: 2327 reads ASV_6 · RBG-16-58-14: 2136 reads ASV_7 · Sulfurifustis: 2036 reads ASV_8 · Incertae Sedis: 1872 reads ASV_9 · Incertae Sedis: 1854 reads ASV_10 · Incertae Sedis: 1847 reads ASV_11 · Incertae Sedis: 1778 reads ASV_12 · Incertae Sedis: 1672 reads ASV_13 · Incertae Sedis: 1626 reads ASV_14 · HSB OF53-F07: 1535 reads ASV_15 · Incertae Sedis: 1454 reads ASV_16 · RBG-16-58-14: 1444 reads ASV_17 · RBG-16-58-14: 1426 reads ASV_18 · RBG-16-58-14: 1374 reads ASV_19 · Incertae Sedis: 1372 reads ASV_20 · Incertae Sedis: 1330 reads ASV_21 · Incertae Sedis: 1228 reads ASV_22 · Anaerolinea: 1226 reads ASV_23 · Candidatus Udaeobacter: 1218 reads ASV_24 · Incertae Sedis: 1214 reads ASV_25 · Incertae Sedis: 1192 reads ASV_26 · Incertae Sedis: 1165 reads ASV_27 · Incertae Sedis: 1140 reads ASV_28 · Incertae Sedis: 1136 reads ASV_29 · RBG-16-58-14: 1120 reads ASV_30 · Thiobacillus: 1112 reads ASV_31 · Sulfurifustis: 1111 reads ASV_32 · Incertae Sedis: 1110 reads ASV_33 · Incertae Sedis: 1106 reads ASV_34 · Incertae Sedis: 1099 reads ASV_35 · Incertae Sedis: 1088 reads ASV_36 · RBG-16-58-14: 1076 reads ASV_37 · RBG-16-58-14: 1072 reads ASV_38 · Incertae Sedis: 1072 reads ASV_39 · Incertae Sedis: 1063 reads ASV_40 · Gallionella: 1062 reads ASV_41 · Incertae Sedis: 1055 reads ASV_42 · Incertae Sedis: 1008 reads ASV_43 · Incertae Sedis: 976 reads ASV_44 · Incertae Sedis: 955 reads ASV_45 · Incertae Sedis: 945 reads ASV_46 · Acidothermus: 937 reads ASV_47 · Incertae Sedis: 936 reads ASV_48 · Incertae Sedis: 932 reads ASV_49 · Incertae Sedis: 927 reads ASV_50 · Incertae Sedis: 920 reads ASV_51 · Incertae Sedis: 918 reads ASV_52 · Incertae Sedis: 905 reads ASV_53 · Incertae Sedis: 898 reads ASV_54 · HSB OF53-F07: 896 reads ASV_55 · Candidatus Udaeobacter: 885 reads ASV_56 · Candidatus Udaeobacter: 883 reads ASV_57 · Incertae Sedis: 878 reads ASV_58 · RBG-16-58-14: 864 reads ASV_59 · Incertae Sedis: 864 reads ASV_60 · RBG-16-58-14: 862 reads ASV_61 · Incertae Sedis: 861 reads ASV_62 · Incertae Sedis: 860 reads ASV_63 · Thiobacillus: 858 reads ASV_64 · RBG-16-58-14: 846 reads ASV_65 · Sulfurisoma: 832 reads ASV_66 · Sulfurifustis: 825 reads ASV_67 · Incertae Sedis: 820 reads ASV_68 · Incertae Sedis: 818 reads ASV_69 · HSB OF53-F07: 818 reads ASV_70 · Thiobacillus: 809 reads ASV_71 · Gallionella: 807 reads ASV_72 · Candidatus Udaeobacter: 804 reads ASV_73 · Anaerolinea: 801 reads ASV_74 · Thiobacillus: 800 reads ASV_75 · Aggregatilinea: 798 reads ASV_76 · RBG-16-58-14: 791 reads ASV_77 · Incertae Sedis: 786 reads ASV_78 · Incertae Sedis: 785 reads ASV_79 · Incertae Sedis: 784 reads ASV_80 · Incertae Sedis: 781 reads ASV_81 · Incertae Sedis: 776 reads ASV_82 · Incertae Sedis: 765 reads ASV_83 · Sulfurifustis: 758 reads ASV_84 · Leptolinea: 756 reads ASV_85 · RBG-16-58-14: 756 reads ASV_86 · Incertae Sedis: 754 reads ASV_87 · RBG-16-58-14: 752 reads ASV_88 · Incertae Sedis: 745 reads ASV_89 · Bradyrhizobium: 740 reads ASV_90 · Incertae Sedis: 735 reads ASV_91 · Incertae Sedis: 730 reads ASV_92 · Incertae Sedis: 730 reads ASV_93 · Incertae Sedis: 723 reads ASV_94 · Incertae Sedis: 706 reads ASV_95 · Thiobacillus: 704 reads ASV_96 · RBG-16-58-14: 704 reads ASV_97 · Incertae Sedis: 698 reads ASV_98 · Thiobacillus: 694 reads ASV_99 · Incertae Sedis: 692 reads ASV_100 · Thiobacillus: 688 reads ASV_101 · Incertae Sedis: 686 reads ASV_102 · Incertae Sedis: 686 reads ASV_103 · RBG-16-58-14: 686 reads ASV_104 · Incertae Sedis: 682 reads ASV_105 · Incertae Sedis: 680 reads ASV_106 · Incertae Sedis: 678 reads ASV_107 · Thiobacillus: 678 reads ASV_108 · Incertae Sedis: 671 reads ASV_109 · Incertae Sedis: 660 reads ASV_110 · Incertae Sedis: 657 reads ASV_111 · Incertae Sedis: 656 reads ASV_112 · RBG-16-58-14: 656 reads ASV_113 · Thiobacillus: 654 reads ASV_114 · HSB OF53-F07: 654 reads ASV_115 · Incertae Sedis: 654 reads ASV_116 · Aminicenans: 652 reads ASV_117 · Incertae Sedis: 652 reads ASV_118 · HSB OF53-F07: 644 reads ASV_119 · Incertae Sedis: 644 reads ASV_120 · Incertae Sedis: 644 reads ASV_121 · Incertae Sedis: 641 reads ASV_122 · Incertae Sedis: 638 reads ASV_123 · Incertae Sedis: 629 reads ASV_124 · Incertae Sedis: 627 reads ASV_125 · Incertae Sedis: 622 reads ASV_126 · RBG-16-58-14: 622 reads ASV_127 · Anaeromyxobacter: 620 reads ASV_128 · Incertae Sedis: 620 reads ASV_129 · Incertae Sedis: 614 reads ASV_130 · HSB OF53-F07: 613 reads ASV_131 · Candidatus Udaeobacter: 608 reads ASV_132 · Incertae Sedis: 603 reads ASV_133 · Incertae Sedis: 602 reads ASV_134 · Incertae Sedis: 600 reads ASV_135 · Incertae Sedis: 594 reads ASV_136 · Incertae Sedis: 590 reads ASV_137 · Leptolinea: 590 reads ASV_138 · Incertae Sedis: 586 reads ASV_139 · Incertae Sedis: 584 reads ASV_140 · Incertae Sedis: 584 reads ASV_141 · Incertae Sedis: 583 reads ASV_142 · Sulfurifustis: 581 reads ASV_143 · Aminicenans: 578 reads ASV_144 · Thiobacillus: 576 reads ASV_145 · Anaeromyxobacter: 575 reads ASV_146 · Thiobacillus: 574 reads ASV_147 · Thiobacillus: 570 reads ASV_148 · Sphingomonas: 570 reads ASV_149 · Incertae Sedis: 570 reads ASV_150 · Incertae Sedis: 569 reads ASV_151 · Incertae Sedis: 568 reads ASV_152 · Incertae Sedis: 566 reads ASV_153 · RBG-16-58-14: 566 reads ASV_154 · Thiobacillus: 564 reads ASV_155 · Incertae Sedis: 564 reads ASV_156 · Incertae Sedis: 563 reads ASV_157 · Incertae Sedis: 563 reads ASV_158 · Sulfurisoma: 562 reads ASV_159 · Incertae Sedis: 560 reads ASV_160 · Incertae Sedis: 558 reads ASV_161 · Sulfurifustis: 556 reads ASV_162 · Ferritrophicum: 556 reads ASV_163 · Candidatus Nitrosotalea: 554 reads ASV_164 · Incertae Sedis: 552 reads ASV_165 · Incertae Sedis: 550 reads ASV_166 · Incertae Sedis: 550 reads ASV_167 · TPD-58: 544 reads ASV_168 · Incertae Sedis: 544 reads ASV_169 · Gallionella: 544 reads ASV_170 · Aquisphaera: 543 reads ASV_171 · Incertae Sedis: 542 reads ASV_172 · Incertae Sedis: 541 reads ASV_173 · Gallionella: 540 reads ASV_174 · Sulfuricurvum: 540 reads ASV_175 · Incertae Sedis: 536 reads ASV_176 · Incertae Sedis: 532 reads ASV_177 · Incertae Sedis: 526 reads ASV_178 · Candidatus Udaeobacter: 526 reads ASV_179 · Leptolinea: 524 reads ASV_180 · RBG-16-58-14: 523 reads ASV_181 · RBG-16-58-14: 522 reads ASV_182 · Incertae Sedis: 522 reads ASV_183 · RBG-16-58-14: 520 reads ASV_184 · RBG-16-58-14: 516 reads ASV_185 · Incertae Sedis: 516 reads ASV_186 · Incertae Sedis: 514 reads ASV_187 · Leptolinea: 512 reads ASV_188 · Incertae Sedis: 511 reads ASV_189 · Thiobacillus: 511 reads ASV_190 · Incertae Sedis: 508 reads ASV_191 · Incertae Sedis: 507 reads ASV_192 · Marine Benthic Group D and DHVEG-1: 504 reads ASV_193 · Incertae Sedis: 504 reads ASV_194 · Candidatus Anammoximicrobium: 504 reads ASV_195 · Sulfurifustis: 504 reads ASV_196 · Incertae Sedis: 503 reads ASV_197 · HSB OF53-F07: 502 reads ASV_198 · Incertae Sedis: 498 reads ASV_199 · Incertae Sedis: 498 reads ASV_200 · Sphingomonas: 498 reads rank reads

27,265 ranked features, top 200 shown. A steep drop means a few taxa carry most of the reads.

Per-sample reads

60 samples
min
6,556
median
23,351
max
37,041

Downstream QC and analysis

computed from the released tables

Eleven modules, computed from the released count table, the sample metadata and the per-run QC reports. Each panel states its own n and the test it used; a module that cannot run on this release is shown as a flagged gap rather than an empty frame.

Rarefaction

median with p10 to p90
2k 5k 10k 20k 915 0

Expected richness when 60 samples are subsampled to a common depth, resampled 31 draws. Median 660 features observed at full depth.

Depth against richness

log depth
1,072 0 reads per sample, log scale

One point per sample. Correlation of log reads with observed features is 0.86, so the depth floor is doing most of the work of deciding how many features a sample shows.

Per-run QC

  • 16S identity 97.5% alignment call per run
  • Q30 rate 98.0% mean Q 37.5
  • Amplicon V4 primers trimmed
  • PhiX 0.0% control spike-in

60 run report(s), n/a GC, 0.0% ambiguous bases.

Diversity

Shannon
5.86
Simpson
0.994
Evenness
0.91
Chao1
660

Median across samples. Observed richness ranges 243 to 1,072.

Feature prevalence

0 of 27,265 features

present in at least half of the 60 samples (0.0%). 18,150 features appear in one sample only, which is the long tail rarefaction is fighting.

Ordination

pc1 pc2

One point per sample, 60 plotted. Choose the axes and the colour variable; hover a point for its sample id. The legend below the axes names the levels or the numeric range.

What explains each axis

pc1 · 7.1%

  • sample class 56.4%
  • shannon 10.3%
  • evenness 8.6%
  • observed 7.9%

pc2 · 5.0%

  • sample class 8.5%
  • shannon 5.4%
  • reads 5.2%
  • observed 4.0%

pc3 · 4.7%

  • sample class 21.4%
  • reads 14.3%
  • observed 10.1%
  • chao1 10.1%

Categorical variables use eta-squared (between-group share of the axis), numeric ones the squared Pearson correlation. Computed from the released sample metadata.

Alpha diversity per sample

Shannon
6.5 60 samples

Median Shannon 5.858 across the release; observed richness runs 243 to 1072.

Bray-Curtis dissimilarity

60 x 60, darker is closer

Sample order is the release order, 60 labels, and the matrix itself ships as beta_distance.tsv beside the analysis.

Phylogenetic diversity

Faith's PD median n/a

From tree.nwk, range to .

Community states

CLR, k by silhouette

k = 3 silhouette 0.369

  • state 0 52 samples
  • state 1 6 samples
  • state 2 2 samples

Clustered on the centred log-ratio of the top 200 features; 60 samples.

Batch-bias audit

states against

adjusted Rand n/a p = n/a

not enough levels to test

permutations. Every sample here carries both MiSeq and MiniSeq runs, so the batch variable used is the one with two levels, here .

Variance partitioning

mean R2 per feature, CLR
  • class 0.188
  • depth 0.000

Joint R2 0.188, so the metadata explains a modest slice of the feature variation, and the two variables are not independent of one another.

Effect size

No two-level comparison available.

Taxa against class

with

features tested, 0 survive the correction at q ≤ 0.05

Nothing survives. The smallest q is n/a, which is the honest answer for a study whose samples are spread across three years with two to thirteen samples per year.

Group difference and spread

Bray-Curtis, 999 permutations
PERMANOVA pseudo-F
1.486 · p 0.001
PERMDISP F
62.85 · p 0.015
Distance decay (Mantel r)
-0.014 · p 0.768
  • Cd-paddy10
  • Cd-sediment1
  • Cd-upland9
  • control10
  • moderate10
  • severe10
  • unknown10

The contamination class separates the communities beyond the spread within each class (PERMANOVA) with no evidence that the spread itself differs (PERMDISP). Distance decay runs over 11.3 to 32.2 km.

Spatial structure

observed richness over distance
Moran's I
0.0501 · p 0.116
Gradient response (rho)
0.368 · p 0.005 (increasing)

variogram, 8 distance bins, semivariance of richness

Constrained ordination

contamination class as the constraint

RDA · R2 0.138p 0.001

Hellinger-scaled, 6 dummy predictors over 60 samples. The constraint explains 13.8% of the community inertia, 0.040 adjusted.

CCA · p 0.343

Chi-square weighted SVD. Not significant here, which is the honest reading at this sample size and predictor count.

Co-occurrence network

100 nodes · 3,037 edges

positive
3,037
negative
0
density
0.614
components
4
mean degree
60.7

Spearman on log1p proportions, 100 features, |r| ≥ 0.50, FDR 0.05.

Hubs by degree

    Phylogenetic diversity

    27,265 tips · MAFFT alignment + FastTree (GTR+CAT)
    Faith's PD median
    76.41
    Faith's PD range
    41.67 – 115.44
    UniFrac PCo1
    22.0%
    UniFrac PCo2
    11.5%

    Faith's PD over the observed tips of each sample; the axes are a PCoA of unweighted UniFrac across the 60 samples.

    Phylogenetic signal

    top 200 features by abundance; trait is mean abundance
    Pagel's lambda
    0.200 · p 0.135
    Blomberg's K
    0.000 · p n/a

    A lambda near 0 means the trait is phylogenetically independent, near 1 means it tracks the tree. Reported scoped to the abundant features because the covariance is quadratic in the feature count.

    ASV phylogeny

    60 most abundant of the tree
    ASV_46 · Actinomycetota · Acidothermus · mean 15.62ASV_46ASV_1 · Chloroflexota · Incertae Sedis · mean 136.58ASV_9 · Chloroflexota · Incertae Sedis · mean 30.90ASV_20 · Chloroflexota · Incertae Sedis · mean 22.17ASV_2 · Chloroflexota · Incertae Sedis · mean 60.47ASV_28 · Chloroflexota · Incertae Sedis · mean 18.93ASV_14 · Chloroflexota · HSB OF53-F07 · mean 25.58ASV_14ASV_54 · Chloroflexota · HSB OF53-F07 · mean 14.93ASV_38 · Chloroflexota · Incertae Sedis · mean 17.87ASV_17 · Chloroflexota · RBG-16-58-14 · mean 23.77ASV_5 · Chloroflexota · RBG-16-58-14 · mean 38.78ASV_16 · Chloroflexota · RBG-16-58-14 · mean 24.07ASV_36 · Chloroflexota · RBG-16-58-14 · mean 17.93ASV_36ASV_18 · Chloroflexota · RBG-16-58-14 · mean 22.90ASV_29 · Chloroflexota · RBG-16-58-14 · mean 18.67ASV_6 · Chloroflexota · RBG-16-58-14 · mean 35.60ASV_58 · Chloroflexota · RBG-16-58-14 · mean 14.40ASV_37 · Chloroflexota · RBG-16-58-14 · mean 17.87ASV_60 · Chloroflexota · RBG-16-58-14 · mean 14.37ASV_60ASV_52 · Chloroflexota · Incertae Sedis · mean 15.08ASV_27 · Chloroflexota · Incertae Sedis · mean 19.00ASV_35 · Chloroflexota · Incertae Sedis · mean 18.13ASV_22 · Chloroflexota · Anaerolinea · mean 20.43ASV_42 · Chloroflexota · Incertae Sedis · mean 16.80ASV_33 · Chloroflexota · Incertae Sedis · mean 18.43ASV_33ASV_24 · Chloroflexota · Incertae Sedis · mean 20.23ASV_49 · Chloroflexota · Incertae Sedis · mean 15.45ASV_34 · Chloroflexota · Incertae Sedis · mean 18.32ASV_53 · Chloroflexota · Incertae Sedis · mean 14.97ASV_44 · Chloroflexota · Incertae Sedis · mean 15.92ASV_48 · Chloroflexota · Incertae Sedis · mean 15.53ASV_48ASV_25 · Candidatus Eremiobacterota · Incertae Sedis · mean 19.87ASV_19 · Thermoproteota · Incertae Sedis · mean 22.87ASV_45 · Cyanobacteriota · Incertae Sedis · mean 15.75ASV_10 · Methylomirabilota · Incertae Sedis · mean 30.78ASV_8 · Methylomirabilota · Incertae Sedis · mean 31.20ASV_4 · Methylomirabilota · Incertae Sedis · mean 40.70ASV_4ASV_11 · Methylomirabilota · Incertae Sedis · mean 29.63ASV_43 · Acidobacteriota · Incertae Sedis · mean 16.27ASV_59 · Verrucomicrobiota · Incertae Sedis · mean 14.40ASV_23 · Verrucomicrobiota · Candidatus Udaeobacter · mean 20.30ASV_55 · Verrucomicrobiota · Candidatus Udaeobacter · mean 14.75ASV_56 · Verrucomicrobiota · Candidatus Udaeobacter · mean 14.72ASV_56ASV_15 · Planctomycetota · Incertae Sedis · mean 24.23ASV_3 · Acidobacteriota · Incertae Sedis · mean 50.40ASV_13 · Acidobacteriota · Incertae Sedis · mean 27.10ASV_7 · Pseudomonadota · Sulfurifustis · mean 33.93ASV_31 · Pseudomonadota · Sulfurifustis · mean 18.52ASV_50 · Pseudomonadota · Incertae Sedis · mean 15.33ASV_50ASV_32 · Pseudomonadota · Incertae Sedis · mean 18.50ASV_30 · Pseudomonadota · Thiobacillus · mean 18.53ASV_41 · Pseudomonadota · Incertae Sedis · mean 17.58ASV_47 · Pseudomonadota · Incertae Sedis · mean 15.60ASV_51 · Pseudomonadota · Incertae Sedis · mean 15.30ASV_40 · Pseudomonadota · Gallionella · mean 17.70ASV_40ASV_57 · Pseudomonadota · Incertae Sedis · mean 14.63ASV_39 · Nitrospirota · Incertae Sedis · mean 17.72ASV_21 · Nitrospirota · Incertae Sedis · mean 20.47ASV_26 · Pseudomonadota · Incertae Sedis · mean 19.42ASV_12 · Acidobacteriota · Incertae Sedis · mean 27.87
    Chloroflexota30Pseudomonadota11Methylomirabilota4Acidobacteriota4Verrucomicrobiota4Nitrospirota2Actinomycetota1Candidatus Eremiobacterota1Thermoproteota1Cyanobacteriota1Planctomycetota1

    The tree is the release's FastTree over all ASVs; this is the subtree of its 60 most abundant, drawn as a cladogram. Branch lengths are the tree's; the bar is mean abundance in the release. Hover a tip for its taxonomy.

    ASV panel

    27265 sequences

    ungapped length · median 233 bp (136–251)

    GC content · median 56.0%

    Most abundant ASVs

    ASVphylumgenusmeanprev.
    ASV_1ChloroflexotaIncertae Sedis136.68%
    ASV_2ChloroflexotaIncertae Sedis60.510%
    ASV_3AcidobacteriotaIncertae Sedis50.43%
    ASV_4MethylomirabilotaIncertae Sedis40.75%
    ASV_5ChloroflexotaRBG-16-58-1438.810%
    ASV_6ChloroflexotaRBG-16-58-1435.63%
    ASV_7PseudomonadotaSulfurifustis33.93%
    ASV_8MethylomirabilotaIncertae Sedis31.25%
    ASV_9ChloroflexotaIncertae Sedis30.92%
    ASV_10MethylomirabilotaIncertae Sedis30.85%
    ASV_11MethylomirabilotaIncertae Sedis29.62%
    ASV_12AcidobacteriotaIncertae Sedis27.910%

    Similar studies

    composition, metadata, location, shared authors
    PRJDB797860%
    • taxonomy 80% similar (genus)
    • same region (V4)

    65 samples

    PRJNA103154057%
    • taxonomy 73% similar (genus)
    • same region (V4)

    33 samples

    PRJNA30759651%
    • taxonomy 61% similar (genus)
    • same region (V4)

    31 samples

    Ranked from the released tables: genus composition as Bray-Curtis similarity, shared environment and method terms, the distance between sample centroids, and authors shared with the linked publication.

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    Samples

    60 samples
    Sample Collected sample class Reads Features Shannon State
    SAMN06219828 2014-12 control 23,464 587 5.801 0
    SAMN06219829 2014-12 control 21,767 692 6.073 0
    SAMN06219830 2014-12 control 15,253 643 6.049 0
    SAMN06219831 2014-12 control 26,958 645 5.841 0
    SAMN06219832 2014-12 control 20,348 648 5.977 0
    SAMN06219833 2014-12 control 22,927 754 6.261 0
    SAMN06219834 2014-12 control 25,509 543 5.271 0
    SAMN06219835 2014-12 control 18,976 544 5.738 0
    SAMN06219836 2014-12 control 26,958 749 6.02 0
    SAMN06219837 2014-12 control 8,155 399 5.603 0
    SAMN06219838 2014-12 unknown 6,556 243 4.979 0
    SAMN06219839 2014-12 moderate 14,029 532 5.776 0
    SAMN06219840 2014-12 moderate 14,017 489 5.633 0
    SAMN06219841 2014-12 moderate 34,188 798 6.115 0
    SAMN06219842 2014-12 moderate 7,981 323 5.37 0
    SAMN06219843 2014-12 moderate 7,013 283 5.235 0
    SAMN06219844 2014-12 moderate 18,905 563 5.851 0
    SAMN06219845 2014-12 moderate 37,041 882 6.08 0
    SAMN06219846 2014-12 moderate 31,489 812 5.922 0
    SAMN06219847 2014-12 moderate 25,684 718 5.793 0
    SAMN06219848 2014-12 severe 22,839 660 5.903 0
    SAMN06219849 2014-12 severe 12,901 481 5.591 0
    SAMN06219850 2014-12 severe 27,211 662 5.765 2
    SAMN06219851 2014-12 severe 30,964 724 5.842 0
    SAMN06219852 2014-12 severe 23,351 563 5.704 0
    SAMN06219853 2014-12 severe 24,540 681 5.866 0
    SAMN06219854 2014-12 severe 10,576 349 5.269 0
    SAMN06219855 2014-12 severe 23,765 682 5.904 0
    SAMN06219856 2014-12 severe 30,865 855 6.108 0
    SAMN06219857 2014-12 severe 19,695 648 5.906 0
    SAMN06704748 2014-12 Cd-upland 14,029 532 5.776 0
    SAMN06704749 2014-12 Cd-upland 10,158 389 5.441 0
    SAMN06704750 2014-12 Cd-upland 20,630 460 5.292 0
    SAMN06704751 2014-12 Cd-upland 24,074 551 5.372 0
    SAMN06704752 2014-12 Cd-upland 27,017 641 5.842 0
    SAMN06704753 2014-12 Cd-upland 7,013 283 5.235 0
    SAMN06704754 2014-12 Cd-upland 18,905 563 5.851 0
    SAMN06704755 2014-12 Cd-upland 30,870 786 6.108 0
    SAMN06704756 2014-12 Cd-upland 33,580 854 6.082 0
    SAMN06704757 2014-12 Cd-upland 31,489 812 5.922 0
    SAMN06704758 2014-12 Cd-paddy 22,839 660 5.903 0
    SAMN06704759 2014-12 Cd-paddy 12,901 481 5.591 0
    SAMN06704760 2014-12 Cd-paddy 27,211 662 5.765 2
    SAMN06704761 2014-12 Cd-paddy 30,964 724 5.842 0
    SAMN06704762 2014-12 Cd-paddy 23,351 563 5.704 0
    SAMN06704763 2014-12 Cd-paddy 24,540 681 5.866 0
    SAMN06704764 2014-12 Cd-paddy 19,006 523 5.302 0
    SAMN06704765 2014-12 Cd-paddy 25,115 768 6.069 0
    SAMN06704766 2014-12 Cd-paddy 21,389 762 6.187 0
    SAMN06704767 2014-12 Cd-paddy 27,741 801 6.092 0
    SAMN06704768 2014-12 Cd-sediment 19,166 721 6.085 1
    SAMN06704769 2014-12 Cd-sediment 23,268 790 6.183 0
    SAMN06704770 2014-12 Cd-sediment 25,063 794 6.022 0
    SAMN06704771 2014-12 Cd-sediment 29,305 1,003 6.43 1
    SAMN06704772 2014-12 Cd-sediment 8,479 367 5.458 1
    SAMN06704773 2014-12 Cd-sediment 33,163 1,072 6.465 1
    SAMN06704774 2014-12 Cd-sediment 15,263 637 6.03 1
    SAMN06704775 2014-12 Cd-sediment 28,477 966 6.403 0
    SAMN06704776 2014-12 Cd-sediment 31,647 1,003 6.403 0
    SAMN06704777 2014-12 Cd-sediment 24,482 919 6.289 1

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