Neurogenic Plasticity in a Serotonin Transporter Knockout Model: Effects of Maternal and Offspring Genotype

<p>Major depressive disorder (MDD) is debilitating mental disorder that is increasing in prevalence. Many theories have tried to explain the aetiology of depression including the classic monoamine deficiency hypothesis and the newer neurogenic hypothesis. The finding that selective serotonin transporter inhibitors (SSRIs) work by increasing extracellular serotonin levels in the brain and have antidepressant effects has formed the basis of the most widely accepted theory of depression, the monoamine hypothesis. However, a genetic reduction in human and animal serotonin reuptake transporters, which also increases extracellular serotonin, is associated with depressive symptomology. This paradox is not explained by the monoamine hypothesis. The key difference between these two scenarios is that genetically induced increases in serotonin occur from development onward, while SSRIs increase serotonin only in adulthood. Furthermore, SSRIs typically take several weeks to confer a therapeutic effect. This finding has led to the hypothesis that, rather than acute monoamine-increasing effects, it is the downstream effects of such increases on neurogenesis and neural plasticity which confer antidepressant effects. To further elucidate the neurobiology of depression, this study sought to examine the effects of genetically increasing serotonin on early postnatal neurogenesis in a serotonin knockout rat model using BrdU immunohistochemistry. We examined both the offspring and maternal genotype effects. We found that SERT-/- offspring had the highest levels of neurogenesis compared with SERT+/- and SERT+/+ at postnatal day 7. In addition we found a maternal genotype effect with SERT+/+ offspring born and reared by SERT+/- mothers having lower neurogenesis compared to SERT+/+ offspring from SERT+/+ mothers. The potential effects of maternal caregiving, neuroplasticity in altered mood and stress responses and the role of 5-HT receptors are discussed.</p>

Neurogenic Plasticity in a Serotonin Transporter Knockout Model: Effects of Maternal and Offspring Genotype

<p>Major depressive disorder (MDD) is debilitating mental disorder that is increasing in prevalence. Many theories have tried to explain the aetiology of depression including the classic monoamine deficiency hypothesis and the newer neurogenic hypothesis. The finding that selective serotonin transporter inhibitors (SSRIs) work by increasing extracellular serotonin levels in the brain and have antidepressant effects has formed the basis of the most widely accepted theory of depression, the monoamine hypothesis. However, a genetic reduction in human and animal serotonin reuptake transporters, which also increases extracellular serotonin, is associated with depressive symptomology. This paradox is not explained by the monoamine hypothesis. The key difference between these two scenarios is that genetically induced increases in serotonin occur from development onward, while SSRIs increase serotonin only in adulthood. Furthermore, SSRIs typically take several weeks to confer a therapeutic effect. This finding has led to the hypothesis that, rather than acute monoamine-increasing effects, it is the downstream effects of such increases on neurogenesis and neural plasticity which confer antidepressant effects. To further elucidate the neurobiology of depression, this study sought to examine the effects of genetically increasing serotonin on early postnatal neurogenesis in a serotonin knockout rat model using BrdU immunohistochemistry. We examined both the offspring and maternal genotype effects. We found that SERT-/- offspring had the highest levels of neurogenesis compared with SERT+/- and SERT+/+ at postnatal day 7. In addition we found a maternal genotype effect with SERT+/+ offspring born and reared by SERT+/- mothers having lower neurogenesis compared to SERT+/+ offspring from SERT+/+ mothers. The potential effects of maternal caregiving, neuroplasticity in altered mood and stress responses and the role of 5-HT receptors are discussed.</p>

Evaluating the accuracy of variant calling methods using the frequency of parent-offspring genotype mismatch

The use of NGS datasets has increased dramatically over the last decade, however, there have been few systematic analyses quantifying the accuracy of the commonly used variant caller programs. Here we used a familial design consisting of diploid tissue from a single Pinus contorta parent and the maternally derived haploid tissue from 106 full-sibling offspring, where mismatches could only arise due to mutation or bioinformatic error. Given the rarity of mutation, we used the rate of mismatches between parent and offspring genotype calls to infer the SNP genotyping error rates of FreeBayes, HaplotypeCaller, SAMtools, UnifiedGenotyper, and VarScan. With baseline filtering HaplotypeCaller and UnifiedGenotyper yielded one to two orders of magnitude larger numbers of SNPs and error rates, whereas FreeBayes, SAMtools and VarScan yielded lower numbers of SNPs and more modest error rates. To facilitate comparison between variant callers we standardized each SNP set to the same number of SNPs using additional filtering, where UnifiedGenotyper consistently produced the smallest proportion of genotype errors, followed by HaplotypeCaller, VarScan, SAMtools, and FreeBayes. Additionally, we found that error rates were minimized for SNPs called by more than one variant caller. Finally, we evaluated the performance of various commonly used filtering metrics on SNP calling. Our analysis provides a quantitative assessment of the accuracy of five widely used variant calling programs and offers valuable insights into both the choice of variant caller program and the choice of filtering metrics, especially for researchers using non-model study systems.

31 Gametic Incompatibility: Improving the Success of Mate Allocation in Dairy Cattle

In the dairy industry, mate allocation is mainly based on the parents’ breeding values and inbreeding coefficients aiming to achieve the producer’s breeding goal. With artificial insemination, the portfolio of sires to choose from is large and the quality of the semen doses is standardized. However, not all sire-dam matings are equally likely to produce a successful pregnancy. Among other reproduction issues, the success of a mating could vary due to the incompatibility of gametes coming from the sire and the dam and could influence the fertilization’s success, additionally to the reproductive capacity of the parents. Considering the gametic incompatibility of the potential parents could be a novel option to improve mating plans. Under the hypothesis that gametic incompatibility has a significant effect on reproduction and reduces the odds of fertilization and pregnancy, this study aimed to determine the genetic background of gametic incompatibility. Transmission ratio distortion (TRD), which detects deviations from Mendelian inheritance expectations, is commonly used to identify deleterious mutations. We adapted the TRD model by including an interaction effect between the gametes leading to the offspring genotype to detect regions with TRD effects and gametic incompatibility. Our dataset contained 436,651 genotyped (50K SNP) Canadian Holstein cattle from 283,817 parents-offspring trios. A total of 482 regions with TRD containing 671 positional genes were found. The functional analysis detected biological pathways associated with uterus development, embryonic skeletal system development, and nervous system development. Additionally, gene ontology terms from the topology-based pathway enrichment analysis were mostly related to the steroid hormones signalling pathway. Although difficult, genes specific to gametic incompatibility could be differentiated from genes underlying other reproduction processes by refining the genetic regions with TRD. With further investigation, we will provide new information to improve mate allocation for the dairy cattle industry.

Evaluating the accuracy of variant calling methods using the frequency of parent-offspring genotype mismatch

The use of NGS datasets has increased dramatically over the last decade, however, there have been few systematic analyses quantifying the accuracy of the commonly used variant caller programs. Here we used a familial design consisting of diploid tissue from a single Pinus contorta parent and the maternally derived haploid tissue from 106 full-sibling offspring, where mismatches could only arise due to mutation or bioinformatic error. Given the rarity of mutation, we used the rate of mismatches between parent and offspring genotype calls to infer the SNP genotyping error rates of FreeBayes, HaplotypeCaller, SAMtools, UnifiedGenotyper, and VarScan. With baseline filtering HaplotypeCaller and UnifiedGenotyper yielded one to two orders of magnitude larger numbers of SNPs and error rates, whereas FreeBayes, SAMtools and VarScan yielded lower numbers of SNPs and more modest error rates. To facilitate comparison between variant callers we standardized each SNP set to the same number of SNPs using additional filtering, where UnifiedGenotyper consistently produced the smallest proportion of genotype errors, followed by HaplotypeCaller, VarScan, SAMtools, and FreeBayes. Additionally, we found that error rates were minimized for SNPs called by more than one variant caller. Finally, we evaluated the performance of various commonly used filtering metrics on SNP calling. Our analysis provides a quantitative assessment of the accuracy of five widely used variant calling programs and offers valuable insights into both the choice of variant caller program and the choice of filtering metrics, especially for researchers using non-model study systems.

Calculating Probable Theoretical Offspring Genotype in Fruit Flies

Being able to calculate an offspring's theoretical genotype is critical in genetic sciences. We calculate the theoretical genotype and phenotype of fruit fly offspring. Using the product rule, we determine the probability for each trait and then for each genotype. In conclusion, we calculate 64 different genotypes that are supposed to be possible, but only 8 phenotypes are possible.

A unifying framework for rare variant association testing in family-based designs, including higher criticism approaches, SKATs, and burden tests

Motivation Analysis of rare variants in family-based studies remains a challenge. Transmission-based approaches provide robustness against population stratification, but the evaluation of the significance of test statistics based on asymptotic theory can be imprecise. In addition, power will depend heavily on the choice of the test statistic and on the underlying genetic architecture of the locus, which will be generally unknown. Results In our proposed framework, we utilize the FBAT haplotype algorithm to obtain the conditional offspring genotype distribution under the null hypothesis given the sufficient statistic. Based on this conditional offspring genotype distribution, the significance of virtually any association test statistic can be evaluated based on simulations or exact computations, without the need for asymptotic approximations. Besides standard linear burden-type statistics, this enables our approach to also evaluate other test statistics such as SKATs, higher criticism approaches, and maximum-single-variant-statistics, where asymptotic theory might be involved or does not provide accurate approximations for rare variant data. Based on the p-values, combined test statistics such as the aggregated Cauchy association test (ACAT) can also be utilized. In simulation studies, we show that our framework outperforms existing approaches for family-based studies in several scenarios. We also applied our methodology to a TOPMed whole-genome sequencing dataset with 897 asthmatic trios from Costa Rica. Availability FBAT software is available at https://sites.google.com/view/fbatwebpage. Simulation code is available at https://github.com/julianhecker/FBAT_rare_variant_test_simulations. Supplementary information Supplementary data are available at Bioinformatics online.

Baby makes three: maternal, paternal, and zygotic genetic effects shape larval phenotypic evolution

The evolutionary potential of a population is shaped by the genetic architecture of its life-history traits. Early-life phenotypes are influenced by both maternal and offspring genotype, and efforts to understand life-history evolution therefore require consideration of the interactions between these separate but correlated genomes. We used a four-generation experimental pedigree to estimate the genetic architecture of early-life phenotypes in a species with dramatic variation in larval size and morphology. In the polychaete annelid Streblospio benedicti, females make either many small eggs that develop into complex larvae that feed in the plankton or few large eggs that develop into benthic juveniles without having to feed as larvae. By isolating the contributions of maternal, paternal, and zygotic genotype to larval traits, we determined that larval anatomical structures are governed by the offspring genotype at a small number of large-effect loci. Larval size is not shaped by the larva's own genotype but instead depends on loci that act in the mother, and at two genomic locations, by loci that act in the father. The overall phenotype of each larva thus depends on three separate genomes, and a population's response to selection on larval traits will reflect the interactions among them.

Methodology Aspects of Colony Maintain for a Murine Model of Amyotrophic Lateral Sclerosis (ALS) TDP-43 Proteinopathy

The use of genetically engineered mouse (GEMs) models provides an unprecedented opportunity to study the genetic basis of diseases and gene function, therefore it is paramount to determine reproductive parameters that guarantee proper colony maintenance. We studied the reproductive parameters of mice hemizygous for TDP-43A315T transgene, which are viable, fertile, and express a mutant human TAR DNA binding protein (hTDP-43) cDNA harboring an amino acid substitution associated with familial amyotrophic lateral sclerosis (fALS). TDP43A315T mice were backcrossed to a C57Bl6/J pure background for four consecutive generations. The Tg offspring genotype were then confirmed by PCR assays. Our statistical analysis indicated there were no differences in the sex and number of pups per offspring when hemizygous female and male TDP43A315T mice were backcrossed to C57Bl6/J mice. Interestingly, our results showed significant differences in the number of offspring expressing the transgene when hemizygous TDP43A315T male mice were used as breeders. Therefore, our findings suggest that male TDP43A315T mice transfer the transgene with a greater genetic strengths. Such is an important breeding consideration to ensure the principle of reduction in animal experimentation considering most basic research with models focuses on males and excludes female mice.

The Role of Offspring Genotype-by-Sex Interactions, Independently of Environmental Cues, on the Phenotype Traits of an Obese Swine Model

The present study aimed to assess the importance of offspring genotype on postnatal development, independently of confounding factors related to prenatal environment and postnatal lifestyle, using a translational model of obesity and metabolic syndrome (the Iberian pig). Hence, we compared two genotypes (purebred Iberian and crossbreds Iberian × Large White), produced in one single maternal environment (pure Iberian mothers) through artificial insemination of Iberian sows with Iberian and Large White heterospermic semen and maintained in the same conditions during postnatal development. The results indicate that, under same pre- and postnatal environments, the interaction genotype-by-sex has a determinant role on offspring phenotype (i.e., growth and development, metabolic and antioxidant status and fatty acid composition of different tissues). These results may set the basis for future preclinical and clinical research on the differences in the metabolic phenotype among genotypes.