In Arabidopsis, a small group of undiffer- entiated stem cells in the center of the flo- ral meristem give rise to the flower. These
stem cells produce daughter cells that differ-
entiate into the four whorls of organs (sepals,
petals, stamens, and carpels) underlying the
basic flower structure. The different organ
identities are determined by the complex
interplay of floral organ identity genes, most
of which are transcription factors. On page
505 in this issue, Sun et al. (1) describe an
elegant timing mechanism that allows tran-
scriptional changes specified in the stem cells
to be executed only in daughter cells and only
after a predefined number of cell divisions.
The meristem identity gene WUSCHEL
(WUS) is required to maintain the stem cell
population in the floral meristem. The transcription factor AGAMOUS (AG) drives differentiation of the stem cells into stamens and
carpels and is induced by both the floral activator LEAFY (LFY) and WUS in early flowers (stage 3). At a later stage (stage 6), AG
represses WUS in a negative feedback loop
to convert the stem cells to organ primordia
(2) (see the figure). Although AG induction
by WUS, and WUS repression by AG, both
to Terminate Stem Cell Identity
A cell-cycle timing mechanism in Arabidopsis is critical for flower development through the
staggered expression of two transcription factors.
Department of Plant Biology, University of Georgia, Athens,
GA 30602, USA. E-mail: email@example.com
teome network for HSP from information available in protein interaction databases. They observed
that candidate genes and known
HSP genes were more highly connected within this network than
expected by chance. The authors
then created a network of proteins encoded
by known HSP genes, their nominated candidate genes, and proximal interactors, naming this expanded network the “HSPome.”
This not only provides a global view of the
processes and proteins underlying HSP, but
also identifies genes as new candidates to
bear disease-causing mutations. Novarino
et al. validated this last point by returning to
genetics. They identified likely pathogenic
variants in three new genes mined from the
HSPome, one of which was independently
implicated in HSP (4).
Novarino et al. illustrate a subtle and perhaps necessary shift in genetics work. The
burden of proving mutation pathogenicity has traditionally rested on the shoulders
of genetics alone, relying on association of
mutations with disease, segregation of mutations within families, and independent replication of results. Given the pace and nature
of genetic mutation discovery, these proofs
are no longer always tenable. Instead, genetics increasingly relies on functional and
bioinformatics work. This change has been
contentious among those who believe that
genetic evidence should be the foundation of
functional work. There is admittedly potential danger in using functional work to identify candidate genes—most important is the
inevitable issue of circularity where studies
are limited to what investigators believe to
be biologically plausible genes and proteins.
This runs the risk not only of incorrectly
self-affirming hypotheses, but also of ignoring new and critically important pathways
because they don’t fit into a current understanding of the disease process. This is not
the case in the study by Novarino et al. The
authors have been careful to question the significance of their observations, and they have
in some instances the reassurance of independent replication. It is exactly this type of
care that the field needs to take.
Novarino et al. also examined the relation-
ship of the HSPome to genes implicated in
other diseases, and found significant overlap
with gene sets linked to Alzheimer’s disease,
Parkinson’s disease, and amyotrophic lateral
sclerosis. If this fascinating observation holds
true, it raises a critical question: If varied neu-
rodegenerative disorders are linked by a com-
mon pathway, what is the underlying cause of
the distinct cellular vulnerability seen in these
disorders? One might predict that identify-
ing disease-linked protein networks is a key
step toward understanding this phenomenon.
In this regard, the type of work described by
Novarino et al. shows not only the power of
comprehensive genetic analysis in identify-
ing the pathogenic networks involved in that
disease but also the potential of such work to
inform outside of the disease in question (see
This study clearly adds another dimension to our understanding of HSP. With this
knowledge, we can turn toward fulfilling the
ultimate promise of genetics: translating this
understanding into etiology-based therapies.
1. G. Novarino et al., Science 343, 506 (2014).
2. J. Hardy, D. J. Selkoe, Science 297, 353 (2002).
3. J. K. Fink, Acta Neuropathol. 126, 307 (2013).
4. E. C. Oates et al., Am. J. Hum. Genet. 92, 965 (2013).
A global view of disease pathogenesis. The scheme illustrates an investigative approach that connects gene
mutations in one disease through protein networks. This network can be used
to nominate additional candidate genes
and infer mechanistic overlap with other
diseases. It may be possible to derive a
core network that can guide the development of therapeutics.