75
agroecosystem processes. So, the presence or speciation of such keystone taxa or
microorganisms causing ecological suicide may certainly alter microbial community structure and functions. (iii) The third point is related to the technological
aspect of microbiome analysis. The operational taxonomic unit (OTU) has been
much explored to define the structure of the microbiome, but recent studies suggest
going beyond the OTU and emphasizing the use of “exact sequence variant” for
microbiome analysis (Knight et al. 2018). These aforesaid points should be considered during all microbiome analysis. The pan-genome can also be utilized while
studying the microbial community structure of any habitat. Pan-genome is a metagenomic tool to provide better understanding of the phylogenetic resolution of the
microbial genome. Pan-genome covers the extended core genes (control translation,
replication), characters gene (control photosynthesis, endosymbionts, adaptation to
environmental niche), and accessory gene pool of a microbial species. Greater niche
diversity has a larger pan-genome size and has a greater opportunity for lateral gene
flux across the strain, providing the framework for understanding the mechanism of
species evolution and estimating genomic diversity (Bentley 2009). Limited dataset,
inadequate functional features, and difficult installation are the major problems of
existing pan-genome software. This problem can be resolved using the ultrafast
computational pipeline bacterial pan-genome analysis tool (BPGA). BPGA combined with a diverse clustering method such as USEARCH, CD-HIT, or OrthoMCL
provide novel features for downstream analysis such as multi-locus sequence typing
(MLST) phylogeny, presence/absence of genes in the specific strain, unique genes,
and atypical G+C content analysis (Chaudhari et al. 2016). Advanced DNA sequencing, metagenomic, and metabolomic technology are producing large datasets in the
field of microbiome research. These datasets need precise and coherent analysis to
acquire correct information to explore bacterial community composition, interactions, and their role in plant, human, and environmental health and ecosystem
services.
Navigating the whole earth microbiome, oceanic microbiome, seed microbiome,
plant microbiome, and human gut microbiome are ongoing research efforts exploring the potential of the complete microbiome in ocean science, soil ecological science, agricultural science, and human health (Turnbaugh et al. 2007; Tseng and
Tang 2014; Gilbert et al. 2014; Berg and Raaijmakers 2018). Knowledge acquired
from these studies must rectify and enhance scientific understanding and help us
meet the global challenges for developing a sustainable world.
7.2 Future Microbiome Research Directions: How Do They Engage Themselves?
agroecosystem processes. So, the presence or speciation of such keystone taxa or
microorganisms causing ecological suicide may certainly alter microbial community structure and functions. (iii) The third point is related to the technological
aspect of microbiome analysis. The operational taxonomic unit (OTU) has been
much explored to define the structure of the microbiome, but recent studies suggest
going beyond the OTU and emphasizing the use of “exact sequence variant” for
microbiome analysis (Knight et al. 2018). These aforesaid points should be considered during all microbiome analysis. The pan-genome can also be utilized while
studying the microbial community structure of any habitat. Pan-genome is a metagenomic tool to provide better understanding of the phylogenetic resolution of the
microbial genome. Pan-genome covers the extended core genes (control translation,
replication), characters gene (control photosynthesis, endosymbionts, adaptation to
environmental niche), and accessory gene pool of a microbial species. Greater niche
diversity has a larger pan-genome size and has a greater opportunity for lateral gene
flux across the strain, providing the framework for understanding the mechanism of
species evolution and estimating genomic diversity (Bentley 2009). Limited dataset,
inadequate functional features, and difficult installation are the major problems of
existing pan-genome software. This problem can be resolved using the ultrafast
computational pipeline bacterial pan-genome analysis tool (BPGA). BPGA combined with a diverse clustering method such as USEARCH, CD-HIT, or OrthoMCL
provide novel features for downstream analysis such as multi-locus sequence typing
(MLST) phylogeny, presence/absence of genes in the specific strain, unique genes,
and atypical G+C content analysis (Chaudhari et al. 2016). Advanced DNA sequencing, metagenomic, and metabolomic technology are producing large datasets in the
field of microbiome research. These datasets need precise and coherent analysis to
acquire correct information to explore bacterial community composition, interactions, and their role in plant, human, and environmental health and ecosystem
services.
Navigating the whole earth microbiome, oceanic microbiome, seed microbiome,
plant microbiome, and human gut microbiome are ongoing research efforts exploring the potential of the complete microbiome in ocean science, soil ecological science, agricultural science, and human health (Turnbaugh et al. 2007; Tseng and
Tang 2014; Gilbert et al. 2014; Berg and Raaijmakers 2018). Knowledge acquired
from these studies must rectify and enhance scientific understanding and help us
meet the global challenges for developing a sustainable world.
7.2 Future Microbiome Research Directions: How Do They Engage Themselves?