35
samples such as soils (Abulencia et al. 2006). This flow cytometry is connecting the
hub technology necessary for the exploration of the heterogeneous microbial population (Muller et al. 2010). The recent whole-genome amplification (WGA) process
is boosted through nanoliter multiple-displacement amplification (Marcy et al.
2007), which results in accurate amplification without any biases. The resulting
amplicons are perfect for consequent genome assembly, production of a sequence
library, and generation of the full genome using high-throughput pyrosequencing.
Reports showed that the excellence of the cell sorter and WGA unravelled the mystery of the uncultivated microbial world (Walker and Parkhill 2008) and minimized
the drawbacks of PCR-based analysis of uncultivable microbial diversity.
Technological advancements in the area of single-cell isolation, complete genome
or transcriptome sequencing, specifically next-generation sequencing (NGS), and
genome-wide analysis platforms through high-end computational approaches
opened new avenues for high-resolution analysis of single-cell genomes or transcriptomes to disclose the hidden biological complexity (Macaulay and Voet 2014).
Next-generation sequencing is significant in facilitating an extremely sensitive analysis of gene expression, epigenetic configuration, nuclear structure, and other features of the cellular state (Trapnell 2015). Numerous sequencing assays were
optimized at the level of individual cells in the past few years and modifications
stemmed from advances in instruments that physically capture and isolate individual cells and from improvement in amplification technique, and reverse transcriptase, which enhances the process (Trapnell 2015).
Sequencing single bacterial cells was not feasible until very recently because
most of them contain only a minuscule amount of genetic material that is difficult to
extract and process (Amann and Fuchs 2008; Lasken 2012; Dhillon and Li 2015).
Shotgun-sequencing methods of DNA isolated from soil samples were the first
breakthrough that facilitated ease of access to sampling environments (Lasken
2012; Dhillon and Li 2015). The second most important strategy was the use of
multiple displacement amplification, which facilitated precise amplification of isolated genome sets, to ultimately reconstruct the genome of interest using bioinformatics algorithms (Lasken 2012; Kind et al. 2013; Lecault et al. 2012; Dhillon and
Li 2015). Single-cell amplification was developed through the ϕ-29 (phi 29) DNA
polymerase-dependent replication of mini-circular-deoxyribonucleic acid templates
(Lasken 2012; Martínez-García et al. 2014; Dhillon and Li 2015). Initial efforts on
reducing amplification bias were under-represented but with constant modification
in the protocols, in silico corrections, and revalidation with the authentic repository
of databases, minimum biases were found (Marcy et al. 2007; Lasken 2012;
Martínez-García et al. 2014). Still, the process of targeted genome assembly from
the amplified fragments is challenging (Rinke et al. 2013; Dhillon and Li 2015). In
maximum metagenomic studies of a single-cell genome, assembly of the genome of
a particular species apart from the most abundant species is an extremely difficult
task (Marcy et al. 2007; Macaulay and Voet 2014; Dhillon and Li 2015). Precisely
created assemblies from these samples were generated as a consensus genome from
numerous fragments (Kamke et al. 2012; Dhillon and Li 2015). To obtain the best
quality single-cell data and ensure separation of technical noise from the signal,
4.1 Single-Cell Genomics (SCG)
samples such as soils (Abulencia et al. 2006). This flow cytometry is connecting the
hub technology necessary for the exploration of the heterogeneous microbial population (Muller et al. 2010). The recent whole-genome amplification (WGA) process
is boosted through nanoliter multiple-displacement amplification (Marcy et al.
2007), which results in accurate amplification without any biases. The resulting
amplicons are perfect for consequent genome assembly, production of a sequence
library, and generation of the full genome using high-throughput pyrosequencing.
Reports showed that the excellence of the cell sorter and WGA unravelled the mystery of the uncultivated microbial world (Walker and Parkhill 2008) and minimized
the drawbacks of PCR-based analysis of uncultivable microbial diversity.
Technological advancements in the area of single-cell isolation, complete genome
or transcriptome sequencing, specifically next-generation sequencing (NGS), and
genome-wide analysis platforms through high-end computational approaches
opened new avenues for high-resolution analysis of single-cell genomes or transcriptomes to disclose the hidden biological complexity (Macaulay and Voet 2014).
Next-generation sequencing is significant in facilitating an extremely sensitive analysis of gene expression, epigenetic configuration, nuclear structure, and other features of the cellular state (Trapnell 2015). Numerous sequencing assays were
optimized at the level of individual cells in the past few years and modifications
stemmed from advances in instruments that physically capture and isolate individual cells and from improvement in amplification technique, and reverse transcriptase, which enhances the process (Trapnell 2015).
Sequencing single bacterial cells was not feasible until very recently because
most of them contain only a minuscule amount of genetic material that is difficult to
extract and process (Amann and Fuchs 2008; Lasken 2012; Dhillon and Li 2015).
Shotgun-sequencing methods of DNA isolated from soil samples were the first
breakthrough that facilitated ease of access to sampling environments (Lasken
2012; Dhillon and Li 2015). The second most important strategy was the use of
multiple displacement amplification, which facilitated precise amplification of isolated genome sets, to ultimately reconstruct the genome of interest using bioinformatics algorithms (Lasken 2012; Kind et al. 2013; Lecault et al. 2012; Dhillon and
Li 2015). Single-cell amplification was developed through the ϕ-29 (phi 29) DNA
polymerase-dependent replication of mini-circular-deoxyribonucleic acid templates
(Lasken 2012; Martínez-García et al. 2014; Dhillon and Li 2015). Initial efforts on
reducing amplification bias were under-represented but with constant modification
in the protocols, in silico corrections, and revalidation with the authentic repository
of databases, minimum biases were found (Marcy et al. 2007; Lasken 2012;
Martínez-García et al. 2014). Still, the process of targeted genome assembly from
the amplified fragments is challenging (Rinke et al. 2013; Dhillon and Li 2015). In
maximum metagenomic studies of a single-cell genome, assembly of the genome of
a particular species apart from the most abundant species is an extremely difficult
task (Marcy et al. 2007; Macaulay and Voet 2014; Dhillon and Li 2015). Precisely
created assemblies from these samples were generated as a consensus genome from
numerous fragments (Kamke et al. 2012; Dhillon and Li 2015). To obtain the best
quality single-cell data and ensure separation of technical noise from the signal,
4.1 Single-Cell Genomics (SCG)