Data from: Landscape-scale distribution patterns of earthworms inferred from soil DNA

Assessing land-use effect on the diversity of soil biota has long been hampered by difficulties in collecting and identifying soil organisms over large areas. Recently, environmental DNA-based approaches coupled with next-generation sequencing were developed to study soil biodiversity. Here, we optimized a protocol based on soil DNA to examine the effects of land-use on earthworm communities in a mountain landscape. This approach allowed an efficient detection of earthworm diversity and highlighted a significant land-use effect on the distribution patterns of earthworms that was not revealed by a classical survey. Our results show that the soil DNA-based earthworm survey at the landscape-scale improves over previous approaches, and opens a way towards large-scale assessment of soil biodiversity and its drivers.Pansu_et_al_SBB_ewDE_sequence_data_alternative_samplingThis fasta file contains merged reads assigned to their original sample obtained with the alternative soil sampling scheme covering the entire plot surface. Amplicons were amplified using ewDE primers (ewD: 5'- ATTCGGTTGGGGCGACC-3' and ewE: 5'- CTGTTATCCCTAAGGTAGCTT-3') (Bienert et al., 2012). Sequences were obtained by a 2 x 100 bp paired-end sequencing on Illumina HiSeq platform. First filtering steps were performed using the OBITOOLS software (http://metabarcoding.org/obitools) following the data filtering description in supplementary material (Pansu et al., 2015 Soil Biology and Biochemistry). Direct and reverse reads corresponding to the same sequence were aligned and merged thanks to the IlluminaPairEnd program. Only merged sequences with a high alignment quality score were retained (>=40). Then, the ngsfilter program assigned each merged sequence to its original sample using the tags information previously added to primers. Only sequences containing both primers (with a maximum of 3 mismatches per primer) and exact tag sequences were selected. Sequences containing ambiguous nucleotides or shorter than 55 bp were discarded. Strictly identical sequences were merged together while keeping information about the origin of sequences. Strict singletons (i.e. sequences occurring only once in the dataset) were removed.ewDE_vercors_alternative_sampling.fastaPansu_et_al_SBB_ewDE_sequence_data_subplots_samplingThis fasta file contains merged reads assigned to their original sample obtained with the subplots soil sampling scheme. Amplicons were amplified using ewDE primers (ewD: 5'- ATTCGGTTGGGGCGACC-3' and ewE: 5'- CTGTTATCCCTAAGGTAGCTT-3') (Bienert et al., 2012). Sequences were obtained by a 2 x 100 bp paired-end sequencing on Illumina HiSeq platform. First filtering steps were performed using the OBITOOLS software (http://metabarcoding.org/obitools) following the data filtering description in supplementary material (Pansu et al., 2015 Soil Biology and Biochemistry). Direct and reverse reads corresponding to the same sequence were aligned and merged thanks to the IlluminaPairEnd program. Only merged sequences with a high alignment quality score were retained (>=40). Then, the ngsfilter program assigned each merged sequence to its original sample using the tags information previously added to primers. Only sequences containing both primers (with a maximum of 3 mismatches per primer) and exact tag sequences were selected. Sequences containing ambiguous nucleotides or shorter than 55 bp were discarded. Strictly identical sequences were merged together while keeping information about the origin of sequences. Strict singletons (i.e. sequences occurring only once in the dataset) were removed.ewDE_vercors_subplots_sampling.fasta.zi