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Opinion: Beyond the Model

How next-generation sequencing technologies will drive a new era of research on non-model organisms.

By | November 29, 2011

WIKIMEDIA COMMONS, PRINGLES, SUI-SETZ, ANDRE KARWATH AKA (HOMEPAGE IMAGE: WIKIMEDIA COMMONS, GEORGE SHUKLIN)

For much of its history, the field of biology has been primarily focused on diversity. Many early biologists focused on the detailed observation and characterization of living organisms, and a voluminous library of descriptive data ranging across all taxonomic groups was compiled as a result. Biologists could then use this information to propose hypotheses regarding the underlying principles of an observed phenomenon.

To test such hypotheses, however, required the experimental manipulation of organisms in the field or laboratory, which wasn’t made possible until the advances of the 19th and early 20th centuries.  The identification of the “laws” of heredity in the mid-1800s, for example, paved the way for the use of mutagenesis to investigate the underlying genetics of biological phenomena. But these approaches suffered from another set of limitations—namely, that they required organisms that reproduce quickly and can be feasibly reared in large numbers in the laboratory. As a result, researchers focused on a small number of model organisms that possessed these attributes, including representatives of major taxonomic groups such as the fruit fly (Drosophila melanogaster), the small weed Arabidopsis thaliana, brewer’s yeast (Saccharomyces cerevisiae), and the house mouse (Mus musculus).

Through many decades of research with these organisms, we have significantly increased our understanding of cellular and developmental processes and have acquired a vast collection of genetic resources including reference genome sequences. Yet, for many of these species there is limited information about their ecological interactions and life histories. The lack of this context can make it difficult to connect genes to a function in the natural world. Additionally, many ecologically and evolutionarily important traits such as mimicry, mutualism, and parasitism are not exhibited in model organisms. It is time to branch out from science’s heavy focus on its longtime models—much knowledge remains to be gained by increasing the diversity of species under study.

Many researchers who are interested in traits that affect how an organism interacts with its environment have turned to close relatives of model species. For example, the identification of the genetic mechanisms responsible for body pigmentation patterns among different species of fruit flies and among different species of deer mice was aided by previous work on the causative genes in D. melanogaster and the house mouse. Similarly, the genes responsible for variation in leaf complexity and life history in close relatives of A. thaliana were identified relatively easily given previous knowledge of how the genes function in the model plant. Others who have ventured further away from model organisms have enjoyed similar successes, but only after an initial investment of considerable time and labor to develop genetic maps and other tools.

As if on cue, next generation sequencing technologies have emerged as an important catalyst for a new revolution in biological understanding. These methods provide researchers with the ability to acquire unprecedented amounts of genetic information in a single experiment at a fraction of the historical cost. We believe that these technologies can be applied to the study of diverse forms of life with relative ease and only a limited investment in time and financial resources. For example, sequencing the entire genome of A. thaliana—an effort which took originally took several years and millions of dollars—can be now be accomplished via resequencing approaches, in which short sequences are aligned to an existing reference genome, in a few weeks for costs in the thousands of dollars. This has allowed for the extensive characterization of sequence differences between members of a single species, and as a result, an ongoing explosion in our understanding of the genetic basis of variation among individuals.

The promise of these technologies is not limited to well-established study systems. A major stumbling block for studies in non-model systems is the lack of a reference genome sequence, but high-throughput sequencing technologies show great promise in resolving this problem. Emerging sequencing methods can rapidly generate new, high quality reference sequences for species across a broad taxonomic range. The availability of reference sequences, in combination with the application of next-generation techniques to identify natural or induced sequence changes responsible for different phenotypes, can then enable investigations into the genetic basis of interesting traits in various organisms, even those with long generation times or that cannot be reared in the lab. The application of these techniques to DNA samples collected from wild populations, for example, will power genome-wide association (GWA) studies, which test for a correlation between a genotype and a phenotype of interest and take advantage of the “natural experiments” performed by millions of years of evolution.

However, not all phenotypes are caused by changes to the DNA sequence of genes. Many morphological differences among species, among individuals within a species, and even among different cells within an individual, are due to changes in how genes are expressed. Next-generation sequencing technologies have also provided a rapid way to assess the activity of genes through RNA sequencing, and unlike previous technologies, can be used to compare RNA levels within and among species simultaneously. Other elements that control gene expression such as the binding of regulatory transcription factors or modifications to the DNA nucleotides like methylation can also be interrogated on a genome-wide scale using these next-generation platforms.

Central goals of biology have always been to understand the basis for diversity within and among species, and to understand how the environment can influence the expression of different traits. These emerging genetic approaches enable studies in a greatly expanded number of organisms and potentially allow genetic approaches to be applied in natural habitats.  The use of model organisms is not dead, however. The utilization of previously generated resources and continued development of model systems will support and facilitate research in non-models. But with the ability to address molecular mechanisms in the natural world, we can truly begin to understand how all of these factors interact to generate the biological diversity that motivated the early scientists and continues to inspire us today.

Beth Rowan and Daniel Koenig are postdoctoral fellows working with Detlef Weigel at the Max Planck Institute for Developmental Biology. Rowan studies hybrid incompatibility in plants and Koenig studies the genetic factors which enable the success of a new species.

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Comments

Avatar of: Kay_U

Kay_U

Posts: 9

November 29, 2011

OMG, another one of those articles again that overemphasizes
the genome-wide studies… Regardless whether it is sequencing or expression
studies and what mathematical methods you apply later, one should recognize
that these methodologies are still quite descriptive. What we know today about
the biological functions of genes (wild-type or mutant) come from studies on
model systems - in vivo or cell culture. Genes were named after their
associated phenotypes, correct? [For example, “winglessâ€쳌, or "sonic hedgehogâ€쳌,
for those readers who are not familiar with genetics]. I don’t think anyone can
tell from the sequence (or, in addition, when and where genes are expressed)
what the essential functions of particular genes are. This applies to any
biological model, including deciphering the role of genes in abnormal
situations like cancer. Similar to this article, I often hear we don’t need
models any more in the future after we have sequenced every cancer on earth.
Well, keep on dreaming! With more than 50,000+ nucleotide changes in a single
cancer and 400+ of them within coding regions, for example, nobody can tell
from looking at the sequence which mutations are drivers (the ones that matter)
and which are passengers (the ones that don’t really matter). One can project
this to sequencing any living organism in any environment, or whatever the
authors mean with “genetic approaches to be applied in natural habitats.â€쳌  It is also a bit unclear what they mean with
“The ability to address molecular mechanisms in the natural world,…â€쳌. What
molecular “mechanismâ€쳌 is addressed by sequencing or comparing expression
studies? There is just one word for this kind of approach: descriptive. Genetic
modeling requires “modelsâ€쳌 to verify a mechanism in this era of research.
Finally, one should probably recognize that modeling should not generally be
done in “natural habitatsâ€쳌 or, as they say, “in the natural worldâ€쳌. The authors
of this article are from a country that has its problems accepting modified
organisms in “natural habitatsâ€쳌 and even applying genetic testing, stem cell
research, and reproductive technologies “in the natural worldâ€쳌. So, after the
tilde wave of genome wide this-and-that is over, we will finally learn that all
methods in science are complementary. Models are certainly not dead. I would
even predict that in vivo modeling will be more important than ever for actual “mechanistic
studiesâ€쳌 once we know all sequence variants of organisms (or single abnormal
cells) in divergent environments, including cancer cells in their abnormal
micro-environments.

Avatar of:

Posts: 0

November 29, 2011

OMG, another one of those articles again that overemphasizes
the genome-wide studies… Regardless whether it is sequencing or expression
studies and what mathematical methods you apply later, one should recognize
that these methodologies are still quite descriptive. What we know today about
the biological functions of genes (wild-type or mutant) come from studies on
model systems - in vivo or cell culture. Genes were named after their
associated phenotypes, correct? [For example, “winglessâ€쳌, or "sonic hedgehogâ€쳌,
for those readers who are not familiar with genetics]. I don’t think anyone can
tell from the sequence (or, in addition, when and where genes are expressed)
what the essential functions of particular genes are. This applies to any
biological model, including deciphering the role of genes in abnormal
situations like cancer. Similar to this article, I often hear we don’t need
models any more in the future after we have sequenced every cancer on earth.
Well, keep on dreaming! With more than 50,000+ nucleotide changes in a single
cancer and 400+ of them within coding regions, for example, nobody can tell
from looking at the sequence which mutations are drivers (the ones that matter)
and which are passengers (the ones that don’t really matter). One can project
this to sequencing any living organism in any environment, or whatever the
authors mean with “genetic approaches to be applied in natural habitats.â€쳌  It is also a bit unclear what they mean with
“The ability to address molecular mechanisms in the natural world,…â€쳌. What
molecular “mechanismâ€쳌 is addressed by sequencing or comparing expression
studies? There is just one word for this kind of approach: descriptive. Genetic
modeling requires “modelsâ€쳌 to verify a mechanism in this era of research.
Finally, one should probably recognize that modeling should not generally be
done in “natural habitatsâ€쳌 or, as they say, “in the natural worldâ€쳌. The authors
of this article are from a country that has its problems accepting modified
organisms in “natural habitatsâ€쳌 and even applying genetic testing, stem cell
research, and reproductive technologies “in the natural worldâ€쳌. So, after the
tilde wave of genome wide this-and-that is over, we will finally learn that all
methods in science are complementary. Models are certainly not dead. I would
even predict that in vivo modeling will be more important than ever for actual “mechanistic
studiesâ€쳌 once we know all sequence variants of organisms (or single abnormal
cells) in divergent environments, including cancer cells in their abnormal
micro-environments.

Avatar of:

Posts: 0

November 29, 2011

OMG, another one of those articles again that overemphasizes
the genome-wide studies… Regardless whether it is sequencing or expression
studies and what mathematical methods you apply later, one should recognize
that these methodologies are still quite descriptive. What we know today about
the biological functions of genes (wild-type or mutant) come from studies on
model systems - in vivo or cell culture. Genes were named after their
associated phenotypes, correct? [For example, “winglessâ€쳌, or "sonic hedgehogâ€쳌,
for those readers who are not familiar with genetics]. I don’t think anyone can
tell from the sequence (or, in addition, when and where genes are expressed)
what the essential functions of particular genes are. This applies to any
biological model, including deciphering the role of genes in abnormal
situations like cancer. Similar to this article, I often hear we don’t need
models any more in the future after we have sequenced every cancer on earth.
Well, keep on dreaming! With more than 50,000+ nucleotide changes in a single
cancer and 400+ of them within coding regions, for example, nobody can tell
from looking at the sequence which mutations are drivers (the ones that matter)
and which are passengers (the ones that don’t really matter). One can project
this to sequencing any living organism in any environment, or whatever the
authors mean with “genetic approaches to be applied in natural habitats.â€쳌  It is also a bit unclear what they mean with
“The ability to address molecular mechanisms in the natural world,…â€쳌. What
molecular “mechanismâ€쳌 is addressed by sequencing or comparing expression
studies? There is just one word for this kind of approach: descriptive. Genetic
modeling requires “modelsâ€쳌 to verify a mechanism in this era of research.
Finally, one should probably recognize that modeling should not generally be
done in “natural habitatsâ€쳌 or, as they say, “in the natural worldâ€쳌. The authors
of this article are from a country that has its problems accepting modified
organisms in “natural habitatsâ€쳌 and even applying genetic testing, stem cell
research, and reproductive technologies “in the natural worldâ€쳌. So, after the
tilde wave of genome wide this-and-that is over, we will finally learn that all
methods in science are complementary. Models are certainly not dead. I would
even predict that in vivo modeling will be more important than ever for actual “mechanistic
studiesâ€쳌 once we know all sequence variants of organisms (or single abnormal
cells) in divergent environments, including cancer cells in their abnormal
micro-environments.

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