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F. Raible and P.R.H. Steinmetz
analyses, e.g. by microarrays or high-throughput sequencing. As outlined above,
such experiments now become feasible in a limited set of marine model species
(like Ciona, Nematostella, sea urchin, Amphioxus, or Platynereis) and these experimental approaches should cast some light on the basic wiring, and thus complexity,
of regulatory networks in diverse phyla.
Molecular correlates of classical features of complexity: Another fundamental
question that still awaits future experimentation concerns the connection between
the new, molecular measures of complexity and the traditional measures of morphological complexity and cell type diversity. For instance, what are the molecular
correlates that enabled the evolution of multicellularity? Similarly, is the number of
differentiated cell types correlated with the complexity of developmental networks,
or is there an independent degree of “regulatory capacity” of an animal (e.g. depending on the individual mode of development). To date, our understanding of cell type
differentiation is limited to a few cases such as the lymphoid lineage, or pancreatic
beta cells. There is still much groundwork to do to identify the correlates of distinct cell types on the molecular level. In turn, such analyses could also determine
whether apparently identical cells in fact represent molecularly distinct cell types.
Evolution acting on different regulatory layers: More and more evidence indicates that non-coding DNA (previously referred to as “junk-DNA”) carries out
important regulatory functions: such as providing binding sites for transcriptional
regulators, being a substrate for epigenetic modifications, or producing non-coding
transcripts with regulatory function. Each of these aspects is of relevance for the
proper understanding of genomic and morphological complexity (Hahn and Wray
2002, Levine and Tjian 2003, Mattick 2007). For instance, modification of cisregulatory elements is associated with changes in complex pigment patterns in
the dipteran wing (reviewed in Prud’homme et al. 2007). Moreover, non-coding
microRNAs have emerged as a previously unknown layer of post-transcriptional
regulation. Given that many microRNAs are expressed in a tissue- or cell typespecific manner, they might be good indicators – or even determinants – of cellular
complexity. Several studies have tried to correlate the absence or presence of
microRNAs with the different extents of complexity in animals, with a trend towards
reproducing the assumed patterns of complex vertebrate microRNA repertoires versus poorer repertoires of more basally branching animals (Grimson et al. 2008,
Heimberg et al. 2008). Due the absence of comparable microRNA datasets from
the different groups, it is, however, difficult to assess to what degree experimental
coverage skews the outcome of such analyses.
New approaches to assess homology and morphological evolution: The revolution in sequencing technology, combined with the progress in the establishment of
new molecular model systems that can make use of the new sequence data, also pave
the way to re-approach many of the questions that were dealt with in pre-molecular
times. One fundamental impact concerns the more precise description of homology: As outlined above, the availability of molecular markers helps to distinguish
and compare tissues and cells on the molecular level, for instance to trace back
mesodermal features in cnidarians, and to discriminate – with fresh data – between
different scenarios concerning their relationship to tissues in other taxa. Moreover,
F. Raible and P.R.H. Steinmetz
analyses, e.g. by microarrays or high-throughput sequencing. As outlined above,
such experiments now become feasible in a limited set of marine model species
(like Ciona, Nematostella, sea urchin, Amphioxus, or Platynereis) and these experimental approaches should cast some light on the basic wiring, and thus complexity,
of regulatory networks in diverse phyla.
Molecular correlates of classical features of complexity: Another fundamental
question that still awaits future experimentation concerns the connection between
the new, molecular measures of complexity and the traditional measures of morphological complexity and cell type diversity. For instance, what are the molecular
correlates that enabled the evolution of multicellularity? Similarly, is the number of
differentiated cell types correlated with the complexity of developmental networks,
or is there an independent degree of “regulatory capacity” of an animal (e.g. depending on the individual mode of development). To date, our understanding of cell type
differentiation is limited to a few cases such as the lymphoid lineage, or pancreatic
beta cells. There is still much groundwork to do to identify the correlates of distinct cell types on the molecular level. In turn, such analyses could also determine
whether apparently identical cells in fact represent molecularly distinct cell types.
Evolution acting on different regulatory layers: More and more evidence indicates that non-coding DNA (previously referred to as “junk-DNA”) carries out
important regulatory functions: such as providing binding sites for transcriptional
regulators, being a substrate for epigenetic modifications, or producing non-coding
transcripts with regulatory function. Each of these aspects is of relevance for the
proper understanding of genomic and morphological complexity (Hahn and Wray
2002, Levine and Tjian 2003, Mattick 2007). For instance, modification of cisregulatory elements is associated with changes in complex pigment patterns in
the dipteran wing (reviewed in Prud’homme et al. 2007). Moreover, non-coding
microRNAs have emerged as a previously unknown layer of post-transcriptional
regulation. Given that many microRNAs are expressed in a tissue- or cell typespecific manner, they might be good indicators – or even determinants – of cellular
complexity. Several studies have tried to correlate the absence or presence of
microRNAs with the different extents of complexity in animals, with a trend towards
reproducing the assumed patterns of complex vertebrate microRNA repertoires versus poorer repertoires of more basally branching animals (Grimson et al. 2008,
Heimberg et al. 2008). Due the absence of comparable microRNA datasets from
the different groups, it is, however, difficult to assess to what degree experimental
coverage skews the outcome of such analyses.
New approaches to assess homology and morphological evolution: The revolution in sequencing technology, combined with the progress in the establishment of
new molecular model systems that can make use of the new sequence data, also pave
the way to re-approach many of the questions that were dealt with in pre-molecular
times. One fundamental impact concerns the more precise description of homology: As outlined above, the availability of molecular markers helps to distinguish
and compare tissues and cells on the molecular level, for instance to trace back
mesodermal features in cnidarians, and to discriminate – with fresh data – between
different scenarios concerning their relationship to tissues in other taxa. Moreover,