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Detecting maternal-effect loci by statistical cross-fostering.

ABSTRACT: Great progress has been made in understanding the genetic architecture of phenotypic variation, but it is almost entirely focused on how the genotype of an individual affects the phenotype of that same individual. However, in many species the genotype of the mother is a major determinant of the phenotype of her offspring. Therefore, a complete picture of genetic architecture must include these maternal genetic effects, but they can be difficult to identify because maternal and offspring genotypes are correlated and therefore, partially confounded. We present a conceptual framework that overcomes this challenge to separate direct and maternal effects in intact families through an analysis that we call "statistical cross-fostering." Our approach combines genotype data from mothers and their offspring to remove the confounding effects of the offspring's own genotype on measures of maternal genetic effects. We formalize our approach in an orthogonal model and apply this model to an experimental population of mice. We identify a set of six maternal genetic effect loci that explain a substantial portion of variation in body size at all ages. This variation would be missed in an approach focused solely on direct genetic effects, but is clearly a major component of genetic architecture. Our approach can easily be adapted to examine maternal effects in different systems, and because it does not require experimental manipulation, it provides a framework that can be used to understand the contribution of maternal genetic effects in both natural and experimental populations.

SUBMITTER: Wolf J

PROVIDER: S-EPMC3338265 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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Detecting maternal-effect loci by statistical cross-fostering.

Wolf Jason J Cheverud James M JM

Genetics 20120229 1

Great progress has been made in understanding the genetic architecture of phenotypic variation, but it is almost entirely focused on how the genotype of an individual affects the phenotype of that same individual. However, in many species the genotype of the mother is a major determinant of the phenotype of her offspring. Therefore, a complete picture of genetic architecture must include these maternal genetic effects, but they can be difficult to identify because maternal and offspring genotype ...[more]

PMID: 22377636

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Project description:Pre-reproductive environmental enrichment of female rats influences sensorimotor development and spatial behavior of the offspring, possibly through the changed maternal nurturing. Nevertheless, maternal care could be not the solely responsible for changing offspring developmental trajectories. To disentangle the specific contribution to the transgenerational inheritance of pre- and post-natal factors, a cross-fostering study was performed. Female rats were reared in an enriched environment from weaning to sexual maturity, while control female rats were reared under standard conditions. Following mating with standard-reared males, all females were housed individually. Immediately after delivery, in- or cross-fostering manipulations were performed so that any foster dams received pups born to another dam of the same (in-fostering) or the opposite (cross-fostering) pre-reproductive rearing condition. In lactating dams maternal care and nesting activities were assessed, while in their male pups spatial abilities were assessed through Morris Water Maze (MWM) test at post-natal day 45. Moreover, the expression of Brain-Derived-Neurotrophic-Factor (BDNF) was evaluated in the hippocampus and frontal cortex of dams and pups at weaning. Pre-reproductive maternal environmental enrichment, followed by adoption procedures, loosened its potential in modifying maternal care and offspring developmental trajectories, as indicated by the lack of differences between in-fostered groups of dams and pups. In addition, enriched dams rearing standard pups showed the least complex maternal repertoire (the highest sniffing duration and the lowest nest quality), and their pups showed a reduced spatial learning in the MWM. Nevertheless, pre-reproductive maternal enrichment kept influencing neurotrophic pattern, with enriched dams expressing increased frontal BDNF levels (regardless of the kind of fostered pups), and their offspring expressing increased hippocampal BDNF levels. The present findings enlighten the crucial importance of the early mother-pups interactions in influencing maternal care and offspring phenotype, with the enriched dam-standard pups couple resulting in the most maladaptive encounter. Our study thus sustains that the bidirectional interactions between mother and pups are able to deeply shape offspring phenotype.

Project description:BackgroundVocal learning is a central functional constituent of human speech, and recent studies showing that adult male mice emit ultrasonic sound sequences characterized as "songs" have suggested that the ultrasonic courtship sounds of mice provide a mammalian model of vocal learning.ObjectivesWe tested whether mouse songs are learned, by examining the relative role of rearing environment in a cross-fostering experiment.Methods and findingsWe found that C57BL/6 and BALB/c males emit a clearly different pattern of songs with different frequency and syllable compositions; C57BL/6 males showed a higher peak frequency of syllables, shorter intervals between syllables, and more upward frequency modulations with jumps, whereas BALB/c males produced more "chevron" and "harmonics" syllables. To establish the degree of environmental influences in mouse song development, sons of these two strains were cross-fostered to another strain of parents. Songs were recorded when these cross-fostered pups were fully developed and their songs were compared with those of male mice reared by the genetic parents. The cross-fostered animals sang songs with acoustic characteristics--including syllable interval, peak frequency, and modulation patterns--similar to those of their genetic parents. In addition their song elements retained sequential characteristics similar to those of their genetic parents' songs.ConclusionThese results do not support the hypothesis that mouse "song" is learned; we found no evidence for vocal learning of any sort under the conditions of this experiment. Our observation that the strain-specific character of the song profile persisted even after changing the developmental auditory environment suggests that the structure of these courtship sound sequences is under strong genetic control. Thus, the usefulness of mouse "song" as a model of mammalian vocal learning is limited, but mouse song has the potential to be an indispensable model to study genetic mechanisms for vocal patterning and behavioral sequences.

Project description:The maternal environment has been shown to influence female olfactory preferences through early chemosensory experience. However, little is known about the influence of the maternal environment on chemosignals. In this study, we used two inbred mouse strains, C57BL/6 (C57) and BALB/c (BALB), and explored whether adoption could alter male chemosignals and thus influence female olfactory preferences. In Experiment 1, C57 pups were placed with BALB dams. Adult BALB females then served as the subjects in binary choice tests between paired male urine odours (BALB vs. C57, BALB vs. adopted C57 and C57 vs. adopted C57). In Experiment 2, BALB pups were placed with C57 dams, and C57 females served as the subjects in binary choice tests between paired male urine odours (C57 vs. BALB, C57 vs. adopted BALB, and BALB vs. adopted BALB). In both experiments, we found that females preferred the urine of males from different genetic backgrounds, suggesting that female olfactory preferences may be driven by genetic compatibility. Cross-fostering had subtle effects on female olfactory preferences. Although the females showed no preference between the urine odours of adopted and non-adopted males of the other strain, the BALB females preferred the urine odour of BALB males to that of adopted C57 males, whereas the C57 females showed no preference between the urine odour of C57 and adopted BALB males. Using gas chromatography-mass spectrometry (GC-MS) and stepwise discriminant analysis, we found that the ratios of volatile chemicals from urine and preputial gland secretions were altered in the fostered male mice; these changes may have resulted in the behavioural changes observed in the females. Overall, the results suggest that female mice prefer urine odours from males with different genetic backgrounds; this preference may be driven by genetic compatibility. The early maternal environment influences the chemosignals of males and thus may influence the olfactory preferences of females. Our study provides additional evidence in support of genotype-dependent maternal influences on phenotypic variability in adulthood.

Project description:BackgroundInteractions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted.ResultsWe report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs.ConclusionThis comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list.

Dataset Information

Detecting maternal-effect loci by statistical cross-fostering.

Publications

Detecting maternal-effect loci by statistical cross-fostering.

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