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Developmental Biology - Genetics

Our Genes Vary Our Physical Outcomes

How genetic background shapes differences between members of our species...

A new study reveals how genetic background influences inheritance of traits, laying the grounds for predicting personal risk for disease.

Almost every family has a hard-drinking, bacon-loving, exercise-averse relative who despite all odds lived happily to a ripe old age while another perished before their time despite being mindful about their health. Looking at their genomes, it would be impossible to tell who's the lucky one.

This is because of genetic background. Countless and mostly subtle differences exist in the genomes of any two people. Differences that affect gene function in ways scientists don't yet understand.

A new study led by investigators Brenda Andrews and Charles Boone, professors at the University of Toronto's (U of T) Donnelly Centre for Cellular and Biomolecular Research begins to unpick how genetic background shapes the differences between members of the same species. Andrews is also Director of the Centre and both are professors in the U of T's Department of Molecular Genetics and are Senior Fellows of the Genetic Networks program at the Canadian Institute for Advancement of Research. Boone is also a co-Director of the same CIFAR program. The team also included Gerry Fink, professor of genetics at MIT and member of the Whitehead Institute.

Their findings are published in the journal Proceedings of the National Academy of Science.(PNAS)

"Genetic background confounds our ability to interpret the information stored in an individual genome," says Andrews. It also makes it hard for physicians to predict disease severity in relatively straightforward cases where a disease-causing gene is well known. Two people carrying a mutation causing cystic fibrosis, an inherited lung disorder, can develop a mild or a severe form of the disease due to differences between their genetics.
With 3 million differences in the DNA code between any two people, the study of genetic background effects in humans is still a daunting prospect. But scientists are beginning to make headway by looking at simpler organisms such as yeast.

"Genetic background has the power to make the original phenotype (a physical outcome of gene function) less or more severe," says Jing Hou, a postdoctoral fellow in the lab who spearheaded the study. This is true for human diseases and it is also true in yeast which is a very good model to study this." This is because the yeast genome is smaller than human and therefore easier to study.
To begin to unpick genetic background effects, Hou compared how gene mutations manifest in two closely related yeast strains, S288c and sigma1278b also known as SC and Sigma. The two strains are 0.2 per cent different at the DNA level, which is about the same amount of genetic diversity between any two people.

In earlier work, Boone and Andrews labs, in collaboration with Fink's group, established how mutations in 57 genes — about one percent of all yeast genes — have different outcomes between SC and Sigma, causings cell death in either one or the other strain, but not both. These genes are called "conditional lethals" and whether or not a cell needs them depends on other modifier genes. But which ones are the modifiers?

By mating these two strains, Hou was able to identify modifier genes thanks to their ability to rescue offspring of their cross while masking any damage.
Hou found that while most conditional lethal genes have multiple modifiers, whose effects are more complex and harder to establish, some have only one modifier and are easier to study. This is the case with CYS3 and CYS4 genes, which help make cysteine, an essential amino acid. Both CYS3 and CYS4 are conditionally lethal in Sigma, but not in the SC strain, which means that Sigma cells die when either gene is missing.

She discovered this is thanks to a single modifier gene called OPT1, which works downstream from the CYS genes and can compensate for their loss in the SC strain. Sigma cells happen to carry a mutation in the OPT1 gene and this makes them fully reliant on the CYS genes to produce cysteine.

In another experiment, Hou looked at 20 different yeast strains, of about 1000 naturally found isolates whose genomes are sequenced. She found a different modifier of CYS genes in another strain used in making Japanese rice wine sake. With all this information, she was able to scan the genomes of all 1000 yeast isolates and accurately guess which strains will act like Sigma or like the Sake yeast, being completely reliant on CYS genes to survive.
This is similar to being able to single out, from 1000 patients with the same genetic disorder, those individuals who have a higher chance of developing a more severe form of a disease.

Being able to predict a biological outcome from genome sequence alone is one of the goals of precision medicine and this early work in yeast raises hopes that similar studies will be possible for human cells.

"Just based on sequence and the knowledge of this pathway we could predict gene essentiality across the whole species," says Hou. "I think we will be able to predict human risk of disease if we have good enough knowledge of how genes work together in pathways."

For Hou, the yeast work continues and on a much bigger scale. With research associate Guihong Tan, she is working to identify all genes across 200 isolates whose effects are modified by their genetic background. Tan thinks this number will be 800 genes, but Hou is more conservative: "I think we'll find about 200." With a bottle of champage as prize, Hou hopes to pop it open, once they collect and review all the data.

Genetic background impacts the phenotypic outcome of a mutation in different individuals; however, the underlying molecular mechanisms are often unclear. We characterized genes exhibiting conditional essentiality when mutated in two genetically distinct yeast strains. Hybrid crosses and whole-genome sequencing revealed that conditional essentiality can be associated with nonchromosomal elements or a single-modifier locus, but most involve a complex set of modifier loci. Detailed analysis of the cysteine biosynthesis pathway showed that independent, rare, single-gene modifiers, related to both up- and downstream pathway functions, can arise in multiple allelic forms from separate lineages. For several genes, we also resolved complex sets of modifying loci underlying conditional essentiality, revealing specific genetic interactions that drive an individual strain’s background effect.

The phenotypic consequence of a given mutation can be influenced by the genetic background. For example, conditional gene essentiality occurs when the loss of function of a gene causes lethality in one genetic background but not another. Between two individual Saccharomyces cerevisiae strains, S288c and ?1278b, ~1% of yeast genes were previously identified as “conditional essential.” Here, in addition to confirming that some conditional essential genes are modified by a nonchromosomal element, we show that most cases involve a complex set of genomic modifiers. From tetrad analysis of S288C/?1278b hybrid strains and whole-genome sequencing of viable hybrid spore progeny, we identified complex sets of multiple genomic regions underlying conditional essentiality. For a smaller subset of genes, including CYS3 and CYS4, each of which encodes components of the cysteine biosynthesis pathway, we observed a segregation pattern consistent with a single modifier associated with conditional essentiality. In natural yeast isolates, we found that the CYS3/CYS4 conditional essentiality can be caused by variation in two independent modifiers, MET1 and OPT1, each with roles associated with cellular cysteine physiology. Interestingly, the OPT1 allelic variation appears to have arisen independently from separate lineages, with rare allele frequencies below 0.5%. Thus, while conditional gene essentiality is usually driven by genetic interactions associated with complex modifier architectures, our analysis also highlights the role of functionally related, genetically independent, and rare variants.

Jing Hou, Guihong Tan, Gerald R. Fink, Brenda J. Andrews, and Charles Boone

The authors declare no conflict of interest.

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Feb 26 2019   Fetal Timeline   Maternal Timeline   News  

Scientists are beginning to understand how discrepancies between genomes translate to individual differences within a species. Credit: Mike Weber via WikiCommons. CC BY-SA 2.0

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