Introduction Apple replant disease (ARD) is a complex syndrome that causes reduced growth in apple trees that are replanted in the same soil. A precise etiology of this disease has not been described yet, although it is thought to have a microbiological origin. In the last years, thanks to NGS, some light was cast on the microbiome of ARD-affected soils, however, such single case studies often do not deliver results that may considered generalizable. Objectives The aim of this study was to estimate the main microbiological drivers in ARD-affected soils by using a meta-analytical approach. Materials and Methods A literature search was performed, looking for all the deep-sequencing studies and datasets on ARD-affected soil microbiomes. From these studies, metadata on both environmental variables of soil sampling sites and molecular techniques used were extracted, together with the raw sequencing data from NCBI SRA database. The sequencing datasets of bacteria (n=5) and fungi (n=3) were analyzed using a taxonomic approach in mothur, using SILVA and UNITE databases, respectively. Results Both bacterial and fungal communities in ARD-affected soils had a significantly different structure and were genetically different from those in healthy soils. Thanks to the broader meta-analysis approach, a pool of co-occurring fungal and bacterial OTUs was also identified in ARD-affected soils. For bacteria, it was possible to explain most genetic variability with the environmental and molecular meta-data collected; however, the different molecular methods used accounted for 25% of the variability. For fungi, instead, the meta-data collected explained 40% of the observed variability, which seemed not influenced by the difference in molecular methods among the studies. The variables that affected most the microbial communities were the presence of ARD, the soil treatments and the plant rootstock. Conclusion Our meta-analysis showed that healthy and ARD-affected soils exhibited significantly different soil microbiomes and shared differentially abundant microbial groups. However, an important fraction of the signal was obscured by diverse analytical approaches.

Nicola, L.; Insam, H.; Pertot, I.; Stres, B. (2016). Meta-analysis of microbiomes in soils affected by Apple Replant Disease. In: 3rd Thünen Symposium on Soil Metagenomics: from gene predictions to systems ecology: plus Workshop on Bioinformatic Omics-Tools, Braunschweig, Germany, 14-16 December 2016. Braunschweig: Thünen: 162-163. url: http://www.soil-metagenomics.org/index.php?eID=tx_nawsecuredl&u=0&g=0&t=901519813232&hash=90734f0e39580ed96bd6d8503a64bdbf8f3875fc&file=fileadmin/congress/media/sm/druckelemente/Soil_Metagenomics_2016_Program.pdf handle: http://hdl.handle.net/10449/40248

Meta-analysis of microbiomes in soils affected by Apple Replant Disease

Nicola, Lidia;Pertot, Ilaria;
2016-01-01

Abstract

Introduction Apple replant disease (ARD) is a complex syndrome that causes reduced growth in apple trees that are replanted in the same soil. A precise etiology of this disease has not been described yet, although it is thought to have a microbiological origin. In the last years, thanks to NGS, some light was cast on the microbiome of ARD-affected soils, however, such single case studies often do not deliver results that may considered generalizable. Objectives The aim of this study was to estimate the main microbiological drivers in ARD-affected soils by using a meta-analytical approach. Materials and Methods A literature search was performed, looking for all the deep-sequencing studies and datasets on ARD-affected soil microbiomes. From these studies, metadata on both environmental variables of soil sampling sites and molecular techniques used were extracted, together with the raw sequencing data from NCBI SRA database. The sequencing datasets of bacteria (n=5) and fungi (n=3) were analyzed using a taxonomic approach in mothur, using SILVA and UNITE databases, respectively. Results Both bacterial and fungal communities in ARD-affected soils had a significantly different structure and were genetically different from those in healthy soils. Thanks to the broader meta-analysis approach, a pool of co-occurring fungal and bacterial OTUs was also identified in ARD-affected soils. For bacteria, it was possible to explain most genetic variability with the environmental and molecular meta-data collected; however, the different molecular methods used accounted for 25% of the variability. For fungi, instead, the meta-data collected explained 40% of the observed variability, which seemed not influenced by the difference in molecular methods among the studies. The variables that affected most the microbial communities were the presence of ARD, the soil treatments and the plant rootstock. Conclusion Our meta-analysis showed that healthy and ARD-affected soils exhibited significantly different soil microbiomes and shared differentially abundant microbial groups. However, an important fraction of the signal was obscured by diverse analytical approaches.
2016
Nicola, L.; Insam, H.; Pertot, I.; Stres, B. (2016). Meta-analysis of microbiomes in soils affected by Apple Replant Disease. In: 3rd Thünen Symposium on Soil Metagenomics: from gene predictions to systems ecology: plus Workshop on Bioinformatic Omics-Tools, Braunschweig, Germany, 14-16 December 2016. Braunschweig: Thünen: 162-163. url: http://www.soil-metagenomics.org/index.php?eID=tx_nawsecuredl&u=0&g=0&t=901519813232&hash=90734f0e39580ed96bd6d8503a64bdbf8f3875fc&file=fileadmin/congress/media/sm/druckelemente/Soil_Metagenomics_2016_Program.pdf handle: http://hdl.handle.net/10449/40248
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