The rhizosphere is the hotspot for microbial enzyme activities and contributes to carbon cycling. Precipitation is an important component of global climate change that can profoundly alter belowground microbial communities. However, the impact of precipitation on conifer rhizospheric microbial populations has not been investigated in detail. In the present study, using high-throughput amplicon sequencing, we investigated the impact of precipitation on the rhizospheric soil microbial communities in two Norway Spruce clonal seed orchards, Lipová Lhota (L-site) and Prenet (P-site). P-site has received nearly double the precipitation than L-site for the last three decades. P-site documented higher soil water content with a significantly higher abundance of Aluminium (Al), Iron (Fe), Phosphorous (P), and Sulphur (S) than L-site. Rhizospheric soil metabolite profiling revealed an increased abundance of acids, carbohydrates, fatty acids, and alcohols in P-site. There was variance in the relative abundance of distinct microbiomes between the sites. A higher abundance of Proteobacteria, Acidobacteriota, Ascomycota, and Mortiellomycota was observed in P-site receiving high precipitation, while Bacteroidota, Actinobacteria, Chloroflexi, Firmicutes, Gemmatimonadota, and Basidiomycota were prevalent in L-site. The higher clustering coefficient of the microbial network in P-site suggested that the microbial community structure is highly interconnected and tends to cluster closely. The current study unveils the impact of precipitation variations on the spruce rhizospheric microbial association and opens new avenues for understanding the impact of global change on conifer rizospheric microbial associations.

• Keywords
• FUNGuild, Norway spruce, PICRUSt2, amplicon sequencing, microbial communities, network analysis, precipitation, rhizosphere, seed orchards, soil metabolites,
• MeSH
• Bacteria genetics   classification   metabolism   MeSH
• Rain MeSH
• Climate Change MeSH
• Microbiota * genetics   MeSH
• Soil chemistry   MeSH
• Soil Microbiology * MeSH
• Rhizosphere * MeSH
• Seeds growth & development   microbiology   MeSH
• Picea * microbiology   MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Soil MeSH

By sequencing 727 ancient individuals from the Southern Arc (Anatolia and its neighbors in Southeastern Europe and West Asia) over 10,000 years, we contextualize its Chalcolithic period and Bronze Age (about 5000 to 1000 BCE), when extensive gene flow entangled it with the Eurasian steppe. Two streams of migration transmitted Caucasus and Anatolian/Levantine ancestry northward, and the Yamnaya pastoralists, formed on the steppe, then spread southward into the Balkans and across the Caucasus into Armenia, where they left numerous patrilineal descendants. Anatolia was transformed by intra-West Asian gene flow, with negligible impact of the later Yamnaya migrations. This contrasts with all other regions where Indo-European languages were spoken, suggesting that the homeland of the Indo-Anatolian language family was in West Asia, with only secondary dispersals of non-Anatolian Indo-Europeans from the steppe.

• MeSH
• White People genetics   MeSH
• History, Ancient MeSH
• Genome, Human * MeSH
• Humans MeSH
• Human Migration * history   MeSH
• Gene Flow * MeSH
• Check Tag
• History, Ancient MeSH
• Humans MeSH
• Publication type
• Journal Article MeSH
• Historical Article MeSH
• Geographicals
• Asia MeSH
• Balkan Peninsula MeSH
• Europe MeSH

BACKGROUND: The investigation of plant genome structure and evolution requires comprehensive characterization of repetitive sequences that make up the majority of higher plant nuclear DNA. Since genome-wide characterization of repetitive elements is complicated by their high abundance and diversity, novel approaches based on massively-parallel sequencing are being adapted to facilitate the analysis. It has recently been demonstrated that the low-pass genome sequencing provided by a single 454 sequencing reaction is sufficient to capture information about all major repeat families, thus providing the opportunity for efficient repeat investigation in a wide range of species. However, the development of appropriate data mining tools is required in order to fully utilize this sequencing data for repeat characterization. RESULTS: We adapted a graph-based approach for similarity-based partitioning of whole genome 454 sequence reads in order to build clusters made of the reads derived from individual repeat families. The information about cluster sizes was utilized for assessing the proportion and composition of repeats in the genomes of two model species, Pisum sativum and Glycine max, differing in genome size and 454 sequencing coverage. Moreover, statistical analysis and visual inspection of the topology of the cluster graphs using a newly developed program tool, SeqGrapheR, were shown to be helpful in distinguishing basic types of repeats and investigating sequence variability within repeat families. CONCLUSIONS: Repetitive regions of plant genomes can be efficiently characterized by the presented graph-based analysis and the graph representation of repeats can be further used to assess the variability and evolutionary divergence of repeat families, discover and characterize novel elements, and aid in subsequent assembly of their consensus sequences.

• MeSH
• DNA, Plant genetics   MeSH
• Genome, Plant MeSH
• Glycine max genetics   MeSH
• Pisum sativum genetics   MeSH
• Chromosome Mapping MeSH
• Repetitive Sequences, Nucleic Acid * MeSH
• Sequence Analysis, DNA * MeSH
• Cluster Analysis MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• DNA, Plant MeSH