In every generation, new mutations enter the human population for the first time. If a single copy of the new mutation causes a disease, its transmission may immediately affect the next generation. This grant challenges the idea that the frequency of male-derived mutations newly entering the population each generation is solely due to the frequency of new genetic lesions arising during the germline cell divisions. Another somewhat surprising possibility is that some new germline mutations alter the testis stem cell in which they arise so that this cell and its descendants acquire a proliferative advantage compared to wild type stem cells. This disproportionate increase in sperm carrying the new disease mutation, relative to unmutated sperm, increases the probability the disease will be transmitted to the next generation. A testis dissection/mutation detection approach coupled with computational modeling has shown five different disease-causing de novo mutations in four different genes produce the signature of germline selection. The diseases studied were Apert syndrome, multiple endocrine neoplasia 2B (MEN2B), achondroplasia, and Noonan syndrome. For these diseases, older fathers are at greater risk for having affected children than younger fathers (paternal age effect, PAE). As couples increasingly delay the age when they have children, this phenomenon becomes more important. Germline selection is a contributing factor to the PAE since it causes the disease mutation frequency in a man's sperm to increase exponentially as he ages. This application has four Aims. 1) Understand how the Apert syndrome, MEN2B, and Noonan syndrome mutated disease proteins alter the signaling pathways of spermatogonial stem cells. Cultures of undifferentiated spermatogonia from mouse models of each disease will be compared to controls in biochemical and stem cell transplantation experiments. 2) Use testis dissection in conjunction with a new deep next generation sequencing (NGS) method to test the hypothesis that the unusually high frequency of sporadic Noonan syndrome (one of the most common Mendelian diseases) is due to perhaps as many as 20 different gain-of-function mutations in the same gene with each providing a selective advantage. The idea that loss-of-function/dominant negative mutations can provide a germline selective advantage will be examined by studies on LEOPARD syndrome. Experiments on Rett syndrome will ask whether germline selection must always be accompanied by a marked PAE as has been the case in the previously studied diseases. 3) Further develop new NGS methods to measure the rate of very rare spontaneous mutations with both accuracy and high throughput. Such protocols could be useful in germline mutation studies as well as disease diagnosis. 4) Propose new computational models of germline selection based on the experimental work in both human and mouse and develop new statistical methods to test these models.

Public Health Relevance

Surprisingly, some testis stem cells with a spontaneous disease mutation have a growth advantage that increases the chance an unaffected father will transmit the disease to one of his children, despite the fact that serious illness or early death can occur. In this grant, we explore the molecular basis of the mutation-induced stem cell growth advantage; the insights gained may eventually make it possible to reduce this advantage thereby lowering the chance a father will have an affected child with a new mutation. Some of the technologies we will develop in our project may also contribute to the early diagnosis of cancer as well as to many other areas of biomedical interest.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM036745-30
Application #
8919373
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Krasnewich, Donna M
Project Start
1985-09-01
Project End
2018-08-31
Budget Start
2015-09-01
Budget End
2016-08-31
Support Year
30
Fiscal Year
2015
Total Cost
Indirect Cost
Name
University of Southern California
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
072933393
City
Los Angeles
State
CA
Country
United States
Zip Code
90032
Eboreime, Jordan; Choi, Soo-Kung; Yoon, Song-Ro et al. (2016) Estimating Exceptionally Rare Germline and Somatic Mutation Frequencies via Next Generation Sequencing. PLoS One 11:e0158340
Arnheim, Norman; Calabrese, Peter (2016) Germline Stem Cell Competition, Mutation Hot Spots, Genetic Disorders, and Older Fathers. Annu Rev Genomics Hum Genet 17:219-43
Fischer, Jared M; Calabrese, Peter P; Miller, Ashleigh J et al. (2016) Single cell lineage tracing reveals a role for Tgf?R2 in intestinal stem cell dynamics and differentiation. Proc Natl Acad Sci U S A 113:12192-12197
Yoon, Song-Ro; Choi, Soo-Kung; Eboreime, Jordan et al. (2013) Age-dependent germline mosaicism of the most common noonan syndrome mutation shows the signature of germline selection. Am J Hum Genet 92:917-26
Shinde, Deepali N; Elmer, Dominik P; Calabrese, Peter et al. (2013) New evidence for positive selection helps explain the paternal age effect observed in achondroplasia. Hum Mol Genet 22:4117-26
Choi, Soo-Kyung; Yoon, Song-Ro; Calabrese, Peter et al. (2012) Positive selection for new disease mutations in the human germline: evidence from the heritable cancer syndrome multiple endocrine neoplasia type 2B. PLoS Genet 8:e1002420
Qin, Jian; Subramanian, Jaichandar; Arnheim, Norman (2009) Detection of meiotic DNA breaks in mouse testicular germ cells. Methods Mol Biol 557:165-81
Yoon, Song-Ro; Qin, Jian; Glaser, Rivka L et al. (2009) The ups and downs of mutation frequencies during aging can account for the Apert syndrome paternal age effect. PLoS Genet 5:e1000558
Arnheim, Norman; Calabrese, Peter (2009) Understanding what determines the frequency and pattern of human germline mutations. Nat Rev Genet 10:478-88
Tiemann-Boege, Irene; Curtis, Christina; Shinde, Deepali N et al. (2009) Product length, dye choice, and detection chemistry in the bead-emulsion amplification of millions of single DNA molecules in parallel. Anal Chem 81:5770-6

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