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bioRxiv2022

Gut microbiota composition in colorectal cancer patients is genetically regulated

The risk of colorectal cancer (CRC) depends on environmental and genetic factors. Among environmental factors, an imbalance in the gut microbiota can increase CRC risk. Also, microbiota is influenced by host genetics. However, it is not known if germline variants influence CRC development by modulating microbiota composition. We investigated germline variants associated with the abundance of bacterial populations in the normal (non-involved) colorectal mucosa of 93 CRC patients and evaluated their possible role in disease. Using a multivariable linear regression, we assessed the association between germline variants identified by genome wide genotyping and bacteria abundances determined by 16S rRNA gene sequencing. We identified 37 germline variants associated with the abundance of the genera Bacteroides, Ruminococcus, Akkermansia, Faecalibacterium and Gemmiger and with alpha diversity. These variants are correlated with the expression of 58 genes involved in inflammatory responses, cell adhesion, apoptosis and barrier integrity. Genes and bacteria appear to be involved in the same processes. In fact, expression of the pro-inflammatory genes GAL, GSDMD and LY6H was correlated with the abundance of Bacteroides, which has pro-inflammatory properties; abundance of the anti-inflammatory genus Faecalibacterium correlated with expression of KAZN, with barrier-enhancing functions. Both the microbiota composition and local inflammation are regulated, at least partially, by the same germline variants. These variants may regulate the microenvironment in which bacteria grow and predispose to the development of cancer. Identification of these variants is the first step to identifying higher-risk individuals and proposing tailored preventive treatments that increase beneficial bacterial populations. Authors summaryGenetic variants describe the variation in the DNA sequence in our genomes and are unique for each person. These variants modify the risk of developing colorectal cancer (CRC) by regulating genes that participate in CRC-associated mechanisms. CRC risk is also affected by microbiota (the microorganisms residing in ourselves). A balanced microbiota helps perform our normal body functions, but can induce cancer, if this balance is lost. Microbiota is affected by factors such as pollution and diet, but is also regulated by genetic variants. However, can genetic variants predispose to cancer risk by regulating microbiota? To answer this question, we sequenced the genetic variants of 93 CRC patients and examined the composition of their intestinal microbiota. We identified variants that regulate the presence of benefic or pathogenic bacteria. The same variants also affect the expression of genes that participate in inflammation, immunity and integrity of intestinal tissue. We found that genetic variants regulate gene expression and microbiota at the same time, predisposing to a higher or lower CRC risk. People with variants predisposing to a higher risk may be benefitted by tailored preventive treatments that increase beneficial bacteria.

genetics↗

bioRxiv2022

The intergenerational transmission of educational attainment: A closer look at the (interrelated) roles of paternal involvement and genetic inheritance

Numerous studies have documented a strong intergenerational transmission of educational attainment. In explaining this transmission, separate fields of research have studied separate mechanisms. To obtain a more complete understanding, the current study integrates insights from the fields of behavioural sciences and genetics and examines the extent to which factors from each field are unique underlying mechanisms, correlate with each other, and/or act as important confounders in the intergenerational transmission of educational attainment. Specifically, we focus on paternal involvement as our behavioural indicator and childrens polygenic score (PGS) for education as our genetic indicator and assess the role that fathers play in the intergenerational transmission of educational attainment. To answer our research questions, we use rich data from The National Longitudinal Study of Adolescent to Adult Health (n=4,579). Firstly, results from our mediation analyses showed that about 4 per cent of the effect of fathers educational attainment on childrens educational attainment is explained by paternal involvement, whereas a much larger share, 21 per cent, is explained by childrens education PGS. Secondly, our results showed that these genetic and behavioural influences are significantly correlated to each other. Thirdly, we found support for genetic confounding, as adding childrens education PGS to the model reduced the effect of paternal involvement by 11 per cent. Fourthly, evidence for social confounding was almost negligible (a reduction of half a per cent of the genetic effect). Our findings highlight the importance of integrating insights and data from multiple disciplines in understanding the mechanisms underlying the intergenerational transmission of inequality, as our study reveals that behavioural and genetic influences overlap, correlate, and confound each other as mechanisms underlying this transmission.

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bioRxiv2022

Genetic admixture history and forensic characteristics of Tibeto-Burman-speaking Qiang people explored via the newly developed Y-STR panel and genome-wide SNP data

Fine-scale patterns of population genetic structure and diversity of ethnolinguistically diverse populations are important for biogeographical ancestry inference, kinship testing and also for the development and validation of new kits focused on forensic personal identification. Analyses focused on forensic markers and genome-wide SNP data can provide new insights into the origin, admixture processes and forensic characteristics of targeted populations. Qiang people with a large sample size among Tibeto-Burman-speaking populations widely reside in the middle latitude of the Tibetan Plateau. However, their genetic structure and forensic features have remained uncharacterized due to the paucity of comprehensive genetic analyses. Here, we first developed and validated the AGCU-Y30 Y-STR panel, which contains slowly and moderately mutating Y-STRs, and then we conducted comprehensive population genetic analyses based on Y-STRs and genome-wide SNPs to explore the admixture history of Qiang people and their neighbours. The validated results of this panel showed that the new Y-STR kit was sensitive and robust enough for forensic applications. Haplotype diversity (HD) ranging from 0.9932 to 0.9996 and allelic frequencies ranging from 0.001946 to 0.8326 in 514 Qiang people demonstrated that all included markers were highly polymorphic in Tibeto-Burman people. Population genetic analyses based on Y-STRs (RST, FST, MDS, NJ, PCA and MJNs) revealed that the Qiang people harboured a paternally close relationship with lowland Tibetan-Yi corridor populations. Furthermore, we made a comprehensive population admixture analysis among Eurasian modern and ancient populations based on the shared alleles. We determined that the Qiang people were a genetically admixed population and showed the closest relationship with Tibetan and Neolithic Yellow River farmers. Admixture modelling showed that Qiang people shared the primary ancestry with Tibetan and was derived from North China, supporting the hypothesis of common origin between Tibetan and Qiang people.

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bioRxiv2022

Maintenance of quantitative genetic variance in complex, multi-trait phenotypes: The contribution of rare, large effect variants in two Drosophila species

The interaction of evolutionary processes to determine quantitative genetic variation has implications for contemporary and future phenotypic evolution, as well as for our ability to detect causal genetic variants. While theoretical studies have provided robust predictions to discriminate among competing models, empirical assessment of these has been limited. In particular, theory highlights the importance of pleiotropy in resolving observations of selection and mutation, but empirical investigations have typically been limited to few traits. Here, we applied high dimensional Bayesian Sparse Factor Genetic modelling to 3,385 gene expression traits from Drosophila melanogaster and from D. serrata to explore how genetic variance is distributed across high-dimensional phenotypic space. Surprisingly, most of the heritable trait covariation was due to few lines (genotypes) with extreme (>3 IQR from the median) values. This observation, in the two independently sampled species, suggests that the House of Cards (HoC) model might apply not only to individual expression traits, but also to emergent co-expression phenotypes. Intriguingly, while genotypes extreme for a multivariate factor also tended to have a higher proportion of individual traits that were extreme, we also observed genotypes that were outliers for multivariate factors but not for any individual traits. We observed other consistent differences between heritable multivariate factors with outlier lines versus those factors that conformed to a Gaussian distribution of genetic effects, including differences in gene functions. We use these observations to identify further data required to advance our understanding of the evolutionary dynamics and nature of standing genetic variation for quantitative traits.

genetics↗

bioRxiv2022

Human pancreatic islet microRNAs implicated in diabetes and related traits by large-scale genetic analysis

Genetic studies have identified [≥]240 loci associated with risk of type 2 diabetes (T2D), yet most of these loci lie in non-coding regions, masking the underlying molecular mechanisms. Recent studies investigating mRNA expression in human pancreatic islets have yielded important insights into the molecular drivers of normal islet function and T2D pathophysiology. However, similar studies investigating microRNA (miRNA) expression remain limited. Here, we present data from 63 individuals, representing the largest sequencing-based analysis of miRNA expression in human islets to date. We characterize the genetic regulation of miRNA expression by decomposing the expression of highly heritable miRNAs into cis- and trans-acting genetic components and mapping cis-acting loci associated with miRNA expression (miRNA-eQTLs). We find (i) 81 heritable miRNAs, primarily regulated by trans-acting genetic effects, and (ii) 5 miRNA-eQTLs. We also use several different strategies to identify T2D-associated miRNAs. First, we colocalize miRNA-eQTLs with genetic loci associated with T2D and multiple glycemic traits, identifying one miRNA, miR-1908, that shares genetic signals for blood glucose and glycated hemoglobin (HbA1c). Next, we intersect miRNA seed regions and predicted target sites with credible set SNPs associated with T2D and glycemic traits and find 32 miRNAs that may have altered binding and function due to disrupted seed regions. Finally, we perform differential expression analysis and identify 13 miRNAs associated with T2D status--including miR-187-3p, miR-21-5p, miR-668, and miR-199b-5p--and 4 miRNAs associated with a polygenic score for HbA1c levels--miR-216a, miR-25, miR-30a-3p, and miR-30a-5p.

genetics↗

bioRxiv2022

Reconstructing the genetic history of Kra-Dai speakers from Thailand

Genetic history of the Thai people and, more generally, speakers of the Kra-Dai languages (also known as Tai-Kadai languages) in Thailand remains a topic of debate. Recently, Kutanan et al.1 analyzed genome-wide genetic data for dozens of present-day human populations from Thailand and surrounding countries and concluded that the Central Thai, Southern Thai, and Malay from Southern Thailand are genetically continuous with Austroasiatic speakers such as Mon, and thus the advent of Kra-Dai and Austronesian languages to Central and Southern Thailand was overwhelmingly a result of cultural rather than genetic diffusion. We re-analyzed the genetic data reported by Kutanan et al.1 using an advanced technique for inferring admixture graph models, using autosomal haplotypes, and other methods. We did not reproduce the results by Kutanan et al.1, and our analyses revealed a more complex picture of the genetic history of Kra-Dai speakers and other populations of Thailand.

genetics↗

bioRxiv2022

Estimating the genetic parameters of yield-related traits under different nitrogen conditions in maize

Understanding the genetic basis responding to nitrogen (N) fertilization in crop production is a long-standing research topic in plant breeding and genetics. Albeit years of continuous efforts, the genetic architecture parameters, such as heritability, polygenicity, and mode of selection, underlying the N responses in maize remain largely unclear. In this study, about n = 230 maize inbred lines were phenotyped under high N (HN) and low N (LN) conditions for two consecutive years to obtain six yield-related traits. Heritability analyses suggested that traits highly responsive to N treatments were less heritable. Using publicly available SNP genotypes, the genome-wide association study (GWAS) was conducted to identify n = 231 and n = 139 trait-associated loci (TALs) under HN and LN conditions, respectively, and n = 162 TALs for N-responsive (NR) traits. Furthermore, genome-wide complex trait Bayesian (GCTB) analysis, a method complementary to GWAS, was performed to estimate genetic parameters, including genetic polygenicity and the mode of selection (S). GCTB results suggested that the NR value of a yield component trait was highly polygenic and that four NR traits exhibited negative correlations between SNP effects and their minor allele frequencies (or the S value < 0) -- a pattern consistent with negative selection to purge deleterious alleles. This study reveals the complex genetic architecture underlying N responses for yield-related traits and provides insights into the future direction for N resilient maize development.

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bioRxiv2022

Common and distinct genetic architecture of age at diagnosis of diabetes in South Indian and European populations

South Asians are diagnosed with type 2 diabetes (T2D) more than a decade earlier in life than seen in European populations. We hypothesised that studying the genomics of age of onset in these populations may give insight into earlier age at onset of T2D among individuals of South Asian descent. We conducted a meta-analysis of GWAS of age at diagnosis of T2D in 34,001 individuals from four independent cohorts of European and Asian Indians. We identified two signals near the TCF7L2 and CDKAL1 associated with age at onset of T2D. The strongest genome-wide significant variants at chromosome 10q25.3 in TCF7L2 (lead SNP rs7903146; p = 2.4 x10-12; p-het =0.01; Beta = -0.436; SE = 0.02) and chromosome 6 p22.3 in CDKAL1 (rs9368219; p = 2.29 x10-8; p-het =0.007; Beta = -0.053; SE=0.01) were directionally consistent across ethnic groups and present at similar frequencies, however both loci harboured additional independent signals that were only present in the South Asian cohorts. A genome wide signal was also obtained at chromosome 10q26.12 in WDR11 (rs3011366; p = 2.4 x10-8; p-het =0.25; Beta = 1.44; SE=0.25) specifically in the South Asian Indian cohorts. Our study estimated 17% of heritability (h2) for age onset of T2D among South Indians; higher than the 5% heritability we observed in Europeans suggesting different genetic architectures between these populations. We further estimated the Asian Indian genome-wide polygenic risk score for T2D risk and identified that the variance explained by the Indian specific polygenic risk score (PRS) for age at onset of T2D is substantially higher (2%) in an independent cohort of Asian Indians compared to that seen in White Europeans (<0.1%). This reveals that although variants do exist that are shared between the two population there are also genetic disparities of age onset of T2D between the ethnicities. Author SummaryRecent large multi-ancestry genome-wide meta-analyses have identified over 277 genetic loci associated with type 2 diabetes (T2D). Most association studies for T2D have focused on populations of European ancestry, and the specific genetic architecture of T2D in the South Asian population has not been extensively investigated. Increasing evidence indicates that the prevalence of T2D is higher in South Asians with a strikingly earlier age at diagnosis when compared to Europeans. Genome-wide association studies (GWAS) on age at age at diagnosis of T2D are limited and can help elucidate underlying mechanisms. We conducted the largest meta-analysis to date of genome-wide association studies of age at diagnosis as a surrogate for age of onset of T2D in South Indians and Europeans. Our trans-ancestry meta-analysis identified genetic loci near TCF7L2 and CDKAL1 with substantial ethnic heterogeneity in both allele frequencies and effect sizes in early diagnosis with T2D. Two novel variants near TCF7L2 (rs570193324) and CDKAL1 (rs143316471) were associated with age of diagnosis of T2D only in South Indians and were present at much lower frequency in the European populations. Heritability estimates for age of onset were much stronger in Asian Indians compared to Europeans and a polygenic risk score was constructed using a South Indians, which explained about 2% trait variance compared to European ancestry (<0.1%). Our novel findings provide a better understanding of ethnic differences in the age at onset of T2D and indicate the potential importance of ethnic differences in the genetic architecture underpinning T2D.

genetics↗

bioRxiv2022

The genetic architecture of Arabidopsis thaliana in response to native non-pathogenic leaf bacterial species revealed by GWA mapping in field conditions

Non-pathogenic bacteria can largely contribute to plant health by mobilizing and supplying nutrients and by providing protection against pathogens and resistance to abiotic stresses. Yet, the number of GWAS reporting the genetic architecture of the response to individual members of the beneficial microbiota remains limited. In this study, we established a GWAS under field conditions to estimate the level of genetic variation and the underlying genetic architecture, among 162 accessions of Arabidopsis thaliana originating from 54 natural populations located south-west of France, in response to 13 strains of seven of the most abundant and prevalent non-pathogenic bacterial species isolated from the leaf compartment of A. thaliana in the same geographical region. Using a high-throughput phenotyping methodology to score vegetative growth-related traits, extensive genetic variation was detected within our local set of A. thaliana accessions in response to these leaf bacteria, both at the species and strain levels. The presence of crossing reaction norms among strains indicates that declaring a strain as a plant-growth promoting bacterium is highly dependent on the host genotype tested. In line with the strong genotype-by-genotype interactions, we detected a complex and highly flexible genetic architecture between the 13 strains. Finally, the candidate genes underlying the QTLs revealed a significant enrichment in several biological pathways, including cell, secondary metabolism, signalling and transport. Altogether, plant innate immunity appears as a significant source of natural genetic variation in plant-microbiota interactions and opens new avenues for better understanding the ecologically relevant molecular dialog during plant-microbiota interactions.

genetics↗

bioRxiv2022

A Multivariate Approach to Understanding the Genetic Overlap between Externalizing Phenotypes and Substance Use Disorders

Substance use disorders (SUDs) are phenotypically and genetically correlated with each other and with other psychological traits characterized by behavioral undercontrol, termed externalizing phenotypes. In this study, we used Genomic Structural Equation Modeling to explore the shared genetic architecture among six externalizing phenotypes and four SUDs used in two previous multivariate GWAS of an externalizing and an addiction risk factor, respectively. Using a preregistered set of criteria, we first evaluated the performance of five confirmatory factor analytic models, including a common factor model, alternative parameterizations of two-factor structures, and a bifactor model. We used a combination of model fit, factor reliability, and model characteristics to adjudicate among the models. We next explored the genetic correlations between factors identified in these models and other relevant psychological traits. We found that a common factor model, in which all externalizing phenotypes and SUDs were influenced by a single dimension of genetic risk best characterized the relationships among our phenotypes. Although two two-factor models also performed well, we found that the factors in those models were very highly correlated with each other (rgS > .87) and similarly genetically correlated with external criteria, suggesting they did not represent meaningfully distinct dimensions. Results from this study can be used to inform future efforts to characterize genetic liability for broad externalizing as well as specific externalizing phenotypes.

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bioRxiv2022

Genetic analysis of a phenotypic loss in the mechanosensory entrainment of a circalunar clock

Genetic variants underlying traits that become either non-adaptive or selectively neutral are expected to have altered evolutionary trajectories. Uncovering genetic signatures associated with phenotypic loss presents the opportunity to discover the molecular basis for the phenotype in populations where it persists. Here we study circalunar clocks in populations of marine midge Clunio marinus. The circalunar clock synchronizes development to the lunar phase, and it is set by moonlight and tidal cycles of mechanical agitation. Two out of ten studied populations have lost their sensitivity to mechanical agitation while preserving sensitivity to moonlight. Intriguingly, the F1 offspring of the two insensitive populations regained the sensitivity to mechanical entrainment, implying a genetically independent loss of the phenotype. By combining quantitative trait locus mapping and genome-wide screens, we explored the genetics of this phenotypic loss. QTL analysis suggested an oligogenic origin with one prevalent additive locus in one of the strains. In addition, it confirmed a distinct genetic architecture in the two insensitive populations. Genomic screens further uncovered several candidate genes underlying QTL regions. The strongest signal under the most prominent QTL contains a duplicated STAT1 gene, which has a well-established role in development, and CG022363, an ortholog of the Drosophila melanogaster CG32100 gene, which plays a role in gravitaxis. Our results support the notion that adaptive phenotypes have a complex genetic basis with mutations occurring at several loci. By dissecting the most prevalent signals, we started to reveal the molecular machinery responsible for the entrainment of the circalunar clock.

genetics↗

bioRxiv2022

Mapping genetic variants for nonsense-mediated mRNA decay regulation across human tissues

BackgroundNonsense-mediated mRNA decay (NMD) was originally conceived as an mRNA surveillance mechanism to prevent the production of potentially deleterious truncated proteins. Recent research shows NMD is an important post-transcriptional gene regulation mechanism selectively targeting many non-aberrant mRNAs. However, how natural genetic variants affect NMD and modulate gene expressions remains elusive. ResultsHere we elucidate NMD regulation of individual genes across human tissues through genetical genomics. Genetic variants corresponding to NMD regulation are identified based on the GTEx data through unique and robust transcript expression modelling. We identify genetic variants that influence the percentage of NMD-targeted transcripts (pNMD-QTLs), as well as genetic variants regulating the decay efficiency of NMD-targeted transcripts (dNMD-QTLs). Many such variants are missed in traditional expression quantitative trait locus (eQTL) mapping. NMD-QTLs show strong tissue specificity especially in the brain. They are more likely to colocalize with disease single-nucleotide polymorphisms (SNPs). Compared to eQTLs, NMD-QTLs are more likely to be located within gene bodies and exons, especially the penultimate exons from the 3 end. Furthermore, NMD-QTLs are more likely to be found in the binding sites of miRNAs and RNA binding proteins (RBPs). ConclusionsWe reveal the genome-wide landscape of genetic variants associated with NMD regulation across human tissues. Our analysis results indicate important roles of NMD in the brain. The preferential genomic positions of NMD-QTLs suggest key attributes for NMD regulation. Furthermore, the colocalization with disease-associated SNPs and post-transcriptional regulatory elements implicate regulatory roles of NMD-QTLs in disease manifestation and their interactions with other post-transcriptional regulators.

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bioRxiv2023

Intermediate molecular phenotypes to identify genetic markers of anthracycline-induced cardiotoxicity risk

Cardiotoxicity due to anthracyclines (CDA) affects cancer patients, but we cannot predict who may suffer from this complication. CDA is a complex disease whose polygenic component is mainly unidentified. We propose that levels of intermediate molecular phenotypes in the myocardium associated with histopathological damage could explain CDA susceptibility; so that variants of genes encoding these intermediate molecular phenotypes could identify patients susceptible to this complication. A genetically heterogeneous cohort of mice generated by backcrossing (N = 165) was treated with doxorubicin and docetaxel. Cardiac histopathological damage was measured by fibrosis and cardiomyocyte size by an Ariol slide scanner. We determine intramyocardial levels of intermediate molecular phenotypes of CDA associated with histopathological damage and quantitative trait loci (ipQTLs) linked to them. These ipQTLs seem to contribute to the missing heritability of CDA because they improve the heritability explained by QTL directly linked to CDA (cda-QTLs) through genetic models. Genes encoding these molecular subphenotypes were evaluated as genetic markers of CDA in three cancer patient cohorts (N = 517) whose cardiac damage was quantified by echocardiography or Cardiac Magnetic Resonance. Many SNPs associated with CDA were found using genetic models. LASSO multivariate regression identified two risk score models, one for pediatric cancer patients and the other for women with breast cancer. Molecular intermediate phenotypes associated with heart damage can identify genetic markers of CDA risk, thereby allowing a more personalized patient management. A similar strategy could be applied to identify genetic markers of other complex trait diseases.

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bioRxiv2023

Seven naturally variant loci serve as genetic modifiers of Lamc2jeb induced non-Herlitz Junctional Epidermolysis Bullosa in mice

Epidermolysis Bullosa (EB) is a group of rare genetic disorders that compromise the structural integrity of the skin such that blisters and subsequent erosions occur after minor trauma. While primary genetic risk of all subforms of EB adhere to Mendelian patterns of inheritance, their clinical presentations and severities can vary greatly, implying genetic modifiers. The Lamc2jeb mouse model of non-Herlitz junctional EB (JEB-nH) demonstrated that genetic modifiers can contribute substantially to the phenotypic variability of JEB and likely other forms of EB. The innocuous changes in an EB related gene, Col17a1, have shown it to be a dominant modifier of Lamc2jeb. This work identifies six additional Quantitative Trait Loci (QTL) that modify disease in Lamc2jeb/jeb mice. Three QTL include other known EB related genes, with the strongest modifier effect mapping to a region including the epidermal hemi-desmosomal structural gene dystonin (Dst-e/Bpag1-e). Three other QTL map to intervals devoid of known EB-associated genes. Of these, one contains the nuclear receptor coactivator Ppargc1a as its primary candidate and the others contain related genes Pparg and Igf1, suggesting modifier pathways. These results, demonstrating the potent disease modifying effects of normally innocuous genetic variants, greatly expand the landscape of genetic modifiers of EB and therapeutic approaches that may be applied.

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bioRxiv2023

Models to Estimate Genetic Gain of Soybean Seed Yield from Annual Multi-Environment Field Trials

1Genetic improvements of discrete characteristics such as flower color, the genetic improvements are obvious and easy to demonstrate; however, for characteristics that are measured on continuous scales, the genetic contributions are incremental and less obvious. Reliable and accurate methods are required to disentangle the confounding genetic and non-genetic components of quantitative traits. Stochastic simulations of soybean (Glycine max (L.) Merr.) breeding programs were performed to evaluate models to estimate the realized genetic gain (RGG) from 30 years of multi-environment trials (MET). True breeding values were simulated under an infinitesimal model to represent the genetic contributions to soybean seed yield under various MET conditions. Estimators were evaluated using objective criteria of bias and linearity. Results indicated all estimation models were biased. Covariance modeling as well as direct versus indirect estimation resulted in substantial differences in RGG estimation. Although there were no unbiased models, the three best-performing models resulted in an average bias of {+/-}7.41 kg/ha-1/yr-1 ({+/-}0.11 bu/ac-1/yr-1). Rather than relying on a single model to estimate RGG, we recommend the application of multiple models and consider the range of the estimated values. Further, based on our simulations parameters, we do not think it is appropriate to use any single models to compare breeding programs or quantify the efficiency of proposed new breeding strategies. Lastly, for public soybean programs breeding for maturity groups II and III in North America from 1989 to 2019, the range of estimated RGG values was from 18.16 to 39.68 kg/ha-1/yr-1 (0.27 to 0.59 bu/ac-1/yr-1).

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bioRxiv2023

Genetic characterization of a captive marmoset colony using genotype-by-sequencing

The marmoset is a fundamental non-human primate model for the study of aging, neurobiology, and many other topics. Genetic management of captive marmoset colonies is complicated by frequent chimerism in the blood and other tissues, a lack of tools to enable cost-effective, genome-wide interrogation of variation, and historic mergers and migrations of animals between colonies. We implemented genotype-by-sequencing (GBS) of hair follicle derived DNA (a minimally chimeric DNA source) of 82 marmosets housed at the Southwest National Primate Research Center (SNPRC). Our primary goals were the genetic characterization of our marmoset population for pedigree verification and colony management and to inform the scientific community of the functional genetic makeup of this valuable resource. We used the GBS data to reconstruct the genetic legacy of recent mergers between colonies, to identify genetically related animals whose relationships were previously unknown due to incomplete pedigree information, and to show that animals in the SNPRC colony appear to exhibit low levels of inbreeding. Of the >99,000 single-nucleotide variants (SNVs) that we characterized, >9,800 are located within gene regions known to harbor pathogenic variants of clinical significance in humans. Overall, we show the combination of low-resolution (sparse) genotyping using hair follicle DNA is a powerful strategy for the genetic management of captive marmoset colonies and for identifying potential SNVs for the development of biomedical research models.

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bioRxiv2023

Estimation of heritabilities and genetic correlations by time slices using predictivity in large genomic models

Under genomic selection, genetic parameters may change rapidly from generation to generation. Unless genetic parameters used for a selection index are current, the expected genetic gain may be unrealistic, possibly with a decline for antagonistic traits. Existing methods for parameter estimation are computationally unfeasible with large genomic data. We present formulas for estimating heritabilities and genetic correlations applicable for large models with any number of genotyped individuals. Heritabilities are calculated by combining 2 formulas for genomic accuracies: one that relies on predictivity and another that depends on the number of independent chromosome segments. Genetic correlations are calculated from predictivities across traits. Both formulas include approximate standard errors. The formula for heritabilities was evaluated based on information for 4 commercial data sets extracted from published studies. Calculated heritabilities were close to those used initially, except for a much lower new heritability for one single case; that heritability was later confirmed as valid. Formulas for genetic correlations were tested with simulated data and 1,000 replicates. The formula-based estimates were always close to the values assumed for simulation. Standard errors were high with 1,000 validation animals but small with 10,000. The proposed formulas can be used routinely as a check on the evaluation system whenever the number of validation individuals is large enough. If excessive changes are detected from generation to generation, the selection index can be modified appropriately.

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bioRxiv2023

Genetic associations of dimensional autistic phenotypes

Since there is a large variation in the symptoms shown by persons affected with ASD, analyzing genetics data using a case-control design is not straightforward. To avoid the difficult problem of defining heterogeneous groups, we used four different methods to compute a latent representation of a merged set of three psychometric tests. Computing the genetic contribution of each representation using a subset of participants with genetic data, we showed that factor analysis as well as variable autoencoders separates information contained in psychometric tests into genetically distinct phenotypic domains. Using the individual-level loadings of the domains as quantitative phenotypes in genome-wide association studies we detected statistically significant genetic associations in the domain related to insistence on routine, as well as suggestive genetic signals in other domains. We hope that these results can suggest possible domain-specific interventions in the future.

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