Biology subjects

Han Chen

Publications and source records attributed to Han Chen.

4 recordsLinked to original sources

bioRxiv2016

The regulator-executor-phenotype architecture shaped by natural selection

The genotype-phenotype relationships are a central focus of modern genetics. While deletion analyses have uncovered many regulatory genes of specific traits, it remains largely unknown how these regulators execute their commands through downstream genes, or executors. Here, we wish to know the number of executors for each trait, their relationships with the regulators and the role natural selection may play in shaping the regulator-executor-phenotype architecture. By analyzing [~]500 morphological traits of the yeast Saccharomyces cerevisiae we found that a trait is often controlled directly by a large number of executors, the expressions of which are affected by regulators. By recruiting a set of \"coordinating\" regulators, natural selection helps organize the large number of executors into a small number of co-expression modules. This way, the individual executors can be readily recognized by observational approaches that examine the statistical association between gene activity and trait. When the trait is subject to little or no selection, however, the executors are controlled only by \"non-coordinating\" regulators that evolve passively and do not build the executors co-expression. As a result, none of the executors remain a statistically tractable relationship with the trait. Thus, natural selection by governing some traits strongly (such as fertility) and others weakly (such as aging-related phenotypes) profoundly influences the genotype-phenotype relationships as well as their tractability.

Genetics↗

bioRxiv2016

The non-essentiality of essential genes suggests a loss-of-function therapeutic strategy for loss-of-function human diseases

Essential genes refer to those whose null mutation leads to lethality or sterility. We propose that the fatal effect of inactivating an essential gene can be attributed to either the loss of indispensable core cellular function (type I), or the gain of fatal side effects after losing dispensable periphery function (type II). In principle, inactivation of the type I essential genes can be rescued only by regain of the core functions, whereas inactivation of the type II essential genes could be rescued by a further loss of function of another gene to eliminate the otherwise fatal side effects. Because such loss-of-function rescuing mutations may occur spontaneously, type II essential genes may become non-essential in a few individuals of a large population. We tested this idea in the yeast Sacchromyces cerevisiae. Large-scale whole genome sequencing of such essentiality-reversing mutants reveals 14 cases where inactivation of an essential gene is rescued by loss-of-function mutations on another gene. In particular, the essential gene encoding the enzyme adenylosuccinate lyase (ADSL) is shown to be type II, suggesting a loss-of-function therapeutic strategy for the human disorder ADSL deficiency. A proof-of-principle test of this strategy in the nematode Caenorhabditis elegans shows promising results.

Genetics↗

bioRxiv2015

Principles of studying a cell - a non-boastful paper for all molecular biologists

Studies of a cell rely on either observational approaches or perturbational/genetic approaches to define the contribution of a gene to specific cellular traits. It is unclear, however, under what circumstances each of the two approaches can be most successful and when they are doomed to fail. By analyzing over 500 complex traits of the yeast Saccharomyces cerevisiae we show that the trait relatedness to fitness determines the performance of observational approaches. Specifically, in traits subject to strong natural selection, genes identified using observational approaches are often highly coordinated in expression, such that the gene-trait associations are readily recognizable; in sharp contrast, the lack of such coordination in traits subject to weak selection leads to no detectable activity-trait associations for any individual genes and thus the failure of observational approaches. We further show that genetic approaches can be successful when the genes responsible for coordinating the target genes of observational approaches are perturbed. However, because the system-level cellular responses to a random mutation affect more or less every gene and consequently every trait, most genetic effects convey no trait-specific functional information for understanding the traits, which is particularly true for traits subject to weak selection.\n\nSignificance statementCell research is nearly exclusively based on empirical data obtained through either observational approaches or perturbational/genetic approaches. It is, however, increasingly clear that an analytical framework able to guide the empirical strategies is necessary to drive the field further ahead. This study analyzes ~500 complex traits of the yeast Saccharomyces cerevisiae and reveals the organizing principles of a cell. Specifically, a cell can be viewed as a factory, with each trait being the product of a production line operated directly by workers who are supervised by managers. For a cellular trait produced by many workers, the coordination level of the workers determines the performance of observational approaches. Meanwhile, the coordination of workers is realized by managers that are recruited and/or maintained by natural selection. Thus, observational approaches are expected to fail for traits subject to little selection, and genetic approaches can be successful only when the managers of fitness-tightly-coupled traits are perturbed. The manager-worker architecture built by natural selection explains well the origins of global epistasis and ubiquitous genetic effects, two major issues confusing current genetics and molecular and cellular biology, providing a clear guideline on how to study a cell.

Systems Biology↗

bioRxiv2015

Natural selection defines the cellular complexity

Current biology is perplexed by the lack of a theoretical framework for understanding the organization principles of the molecular system within a cell. Here we first studied growth rate, one of the seemingly most complex cellular traits, using functional data of yeast single-gene deletion mutants. We observed nearly one thousand expression informative genes (EIGs) whose expression levels are linearly correlated to the trait within an unprecedentedly large functional space. A simple model considering six EIG-formed protein modules revealed a variety of novel mechanistic insights, and also explained [~]50% of the variance of cell growth rates measured by Bar-seq technique for over 400 yeast mutants (Pearsons R = 0.69), a performance comparable to the microarray-based (R = 0.77) or colony-size-based (R = 0.66) experimental approach. We then applied the same strategy to 501 morphological traits of the yeast and achieved successes in most fitness-coupled traits each with hundreds of trait-specific EIGs. Surprisingly, there is no any EIG found for most fitness-uncoupled traits, indicating that they are controlled by super-complex epistases that allow no simple expression-trait correlation. Thus, EIGs are recruited exclusively by natural selection, which builds a rather simple functional architecture for fitness-coupled traits, and the endless complexity of a cell lies primarily in its fitness-uncoupled features.

Evolutionary Biology↗