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Results for “genetics”

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bioRxiv2019

Estimating the sensitivity of associations between risk factors and outcomes to shared genetic effects

Associations between exposures and outcomes reported in epidemiological studies are typically unadjusted for genetic confounding. We propose a two-stage approach for estimating the degree to which such observed associations can be explained by genetic confounding. First, we assess attenuation of exposure effects in regressions controlling for increasingly powerful polygenic scores. Second, we use structural equation models to estimate genetic confounding using heritability estimates derived from both SNP-based and twin-based studies. We examine associations between maternal education and three developmental outcomes - child educational achievement, Body Mass Index, and Attention Deficit Hyperactivity Disorder. Polygenic scores explain between 14.3% and 23.0% of the original associations, while analyses under SNP- and twin-based heritability scenarios indicate that observed associations could be almost entirely explained by genetic confounding. Thus, caution is needed when interpreting associations from non-genetically informed epidemiology studies. Our approach, akin to a genetically informed sensitivity analysis can be applied widely. Author summaryAn objective shared across the life, behavioural, and social sciences is to identify factors that increase risk for a particular disease or trait. However, identifying true risk factors is challenging. Often, a risk factor is statistically associated with a disease even if it is not really relevant, meaning that even successfully improving the risk factor will not impact the disease. One reason for the existence of such misleading associations stems from genetic confounding. This is when genetic factors influence both the risk factor and the disease, which generates a statistical association even in the absence of a true effect of the risk factor. Here, we propose a method to estimate genetic confounding and quantify its effect on observed associations. We show that a large part of the associations between maternal education and three child outcomes - educational achievement, body mass index and Attention-Deficit Hyperactivity Disorder-is explained by genetic confounding. Our findings can be applied to better understand the role of genetics in explaining associations of key risk factors with diseases and traits.

genetics↗

bioRxiv2019

Genetic factors underlie the association between anxiety, attitudes and performance in mathematics

Students struggling with mathematics anxiety (MA) tend to show lower levels of mathematics self-efficacy and interest as well as lower performance. The current study addresses: (1) how MA relates to different aspects of mathematics attitudes (self-efficacy and interest), ability (understanding numbers, problem-solving ability, and approximate number sense) and achievement (exam scores); (2) to what extent these observed relations are explained by overlapping genetic and environmental factors; and (3) the role of general anxiety in accounting for these associations. The sample comprised 3,410 twin pairs aged 16-21 years, from the Twins Early Development Study. Negative associations of comparable strength emerged between MA and the two measures of mathematics attitudes, phenotypically ([~] -.45) and genetically ([~] -.70). Moderate negative phenotypic ([~] -.35) and strong genetic ([~] -.70) associations were observed between MA and measures of mathematics performance. The only exception was approximate number sense whose phenotypic (-.10) and genetic (-.31) relation with MA was weaker. Multivariate quantitative genetic analyses indicated that all mathematics related measures combined accounted for [~]75% of the genetic variance in MA and [~]20% of its environmental variance. Genetic effects were largely shared across all measures of mathematics anxiety, attitudes, abilities and achievement, with the exception of approximate number sense. This genetic overlap was not accounted for by general anxiety. These results have important implications for future genetic research concerned with identifying the genetic underpinnings of individual variation in mathematics-related traits, as well as for developmental research into how children select and modify their mathematics-related experiences partly based on their genetic predispositions.

genetics↗

bioRxiv2026

X chromosome association analyses using multiple models identifies 18 genetic loci influencing dietary intake in UK Biobank

Although dietary intake is a leading risk factor for many common diseases, adherence to dietary recommendations remains low. This may partly reflect limited consideration of individual differences in eating behavior that arise from both environmental and genetic factors. While genome-wide association studies (GWAS) of dietary intake have identified hundreds of associated loci, the X chromosome has largely been ignored. To address this gap, we applied multiple X-chromosome-wide association study (X-WAS) models on dietary intake phenotypes to identify novel associations. We performed X-WAS of 46 dietary intake traits from food frequency questionnaires in up to 424,758 European participants from the UK Biobank. Phenotypes included quantitative measures (e.g., fruit intake), binary traits (e.g., decaffeinated vs caffeinated coffee), and principal component-derived food groups. We tested for genetic associations using several models: a traditional sex-combined additive GWAS, additive models stratified by sex, and two joint models accounting for sex-interaction effects and non-additivity. We also conducted X-WAS in five additional genetic ancestry groups and performed a sex-combined multi-ancestry additive GWAS meta-analysis with up to 445,773 individuals. We identified 18 loci associated with 20 dietary intake traits (P < 5x10-8), including 17 variants without prior associations in the GWAS Catalog. Among these loci, 10 were significant across multiple X-WAS models, and 5 were strongest in a model other than the traditional sex-combined additive GWAS, highlighting the value of approaches that address known complexities of the X chromosome. These results demonstrate that incorporating the X chromosome in GWAS can reveal novel loci, even for complex behavioral traits such as dietary intake. Applying multiple association models further improves discovery by accounting for unique features of the X chromosome. Author SummaryAlthough diet is a major risk factor for many common diseases, adherence to healthy eating guidelines remains low. One reason is that current recommendations do not account for individual differences in food choice that arise from environmental or genetic factors. Previous genetic studies have identified hundreds of genetic variants associated with dietary behaviors, but most have excluded the X chromosome due to its analytical complexity and differences between males and females. However, accumulating evidence suggests that the X chromosome contains important genetic variation that impacts complex traits. We analyzed data from hundreds of thousands of individuals to identify genetic variants on the X chromosome associated with dietary intake. To address the unique features of the X chromosome, we applied multiple different models that account for sex-differences and non-additive genetic effects. We identified 18 regions in the genome associated with at least one dietary intake trait. These results reveal new insights into the genetics underlying eating behavior and highlight the importance of incorporating the X chromosome in genetic studies of complex traits.

genetics↗

bioRxiv2026

Comprehensive analysis of mulberry genetic diversity based on 1-DNJ content and SNP markers

Mulberry trees have high economic and ecological value, and a robust molecular marker system plus germplasm genetic diversity analysis is critical for innovative utilization of high-quality medicinal and economic mulberry germplasm. Here, 51 mulberry samples were used to develop SNP primers via genome resequencing, with the SNP-PCR system optimized by single-factor and orthogonal assays. The phenotypic diversity and SNP molecular marker genetic diversity of 1-deoxynojirimycin (1-DNJ) in mulberry leaves were analyzed respectively, and the genetic correlation between molecular markers and phenotypic traits was evaluated by Mantel test. Tested germplasm showed marked 1-DNJ variation (0.4805-2.5300 mg/g, CV=0.4241), reflecting rich genetic diversity. The optimal SNP-PCR system included Buffer (containing Mg{superscript 2}+) 2.2 L, 2.5 mM dNTP 0.4 L, forward and reverse primers (10 mol{middle dot}L-1) totaling 2.75 L, Taq DNA polymerase (5 U{middle dot}L-1) 0.3 L, DNA (50 ng{middle dot}L-1) 1.1 L, and ddH2O 13.65 L. 23 highly polymorphic ones amplified 91 loci (81 polymorphic, 89.10% polymorphism rate). Genetic diversity analysis showed that the average genetic distance was 0.3010, and the average expected heterozygosity (H) and Shannon information index (I) reached 0.4667 and 0.3104 respectively, indicating that the genetic differentiation among the tested mulberry germplasms was significant and the population had a moderate to upper level of genetic diversity. UPGMA clustering divided 51 germplasms into 6 major groups at a genetic similarity coefficient of about 0.7, while phenotypic clustering based on 1-DNJ content divided them into 2 major categories and 4 subcategories, with high 1-DNJ germplasm clustered independently. Mantel correlation analysis showed that 6 SNP sites were significantly weakly correlated with 1-DNJ content (r < 0.3, p < 0.05), and can be used as candidate molecular markers for subsequent genetic analysis of 1-DNJ content.This study established a stable mulberry SNP-PCR system, Analyze the molecular genetic characteristics of mulberry germplasm and DNJ phenotypic variation rules respectively, and provide basic data for cluster comparison. and provided a scientific basis for marker database improvement, germplasm identification and molecular-assisted breeding.

genetics↗

bioRxiv2020

Influence of isolation by environment and landscape heterogeneity on genetic structure of wild rice Zizania latifolia along a latitudinal gradient

Global aquatic habitats are undergoing rapid degradation and fragmentation as a result of land-use change and climate change. Understanding the genetic variability and adaptive potential of aquatic plant species is thus important for conservation purposes. In this study, we investigated the role of environment, landscape heterogeneity and geographical distance in shaping the genetic structure of 28 natural populations of Zizania latifolia (Griseb.) Turcz. Ex Stapf in China based on 25 microsatellite markers. Genetic structure was investigated by analysis of molecular variance (AMOVA), estimation of FST, Bayesian clustering and Thermodynamic Integration (TI) methods. Isolation by environment (IBE), isolation by resistance (IBR) and isolation by distance (IBD) hypotheses were compared using a reciprocal causal model (RCM). Further, generalized linear models and spatially explicit mixed models, by using geographic, landscape and genetic variables, were developed to elucidate the role of environment in driving Z. latifolia genetic diversity. The genetic differentiation across all populations was high: FST = 0.579; Opt = 0.578. RCM exclusively supported IBE in shaping genetic structuring, only partial support for IBR, but not for IBD. Maximum temperature of the warmest month and precipitation seasonality were the plausible parameters responsible for genetic diversity. After controlling for spatial effect and landscape complexity, precipitation seasonality was significantly associated with genetic diversity. Based on these findings, genetic structure of Z. latifolia across China seem to be as a result of local adaptation. Environmental gradient and topographical barriers, rather than geographical isolation, influence genetic differentiation of aquatic species across China resulting in instances of local adaptation.

ecology↗

bioRxiv2020

Wing Geometry and Genetic Analyses Reveal Contrasting Spatial Structures between Male and Female Aedes aegypti Populations in Metropolitan Manila, Philippines

BackgroundMany important arboviral diseases (e.g. dengue, chikungunya) are transmitted by the bite of a female mosquito vector, Aedes aegypti. Hence, the population genetic structure of the mosquito has been studied in order to understand its role as an efficient vector. Several studies utilized an integrative approach; to combine genetic and phenotypic data to determine the population structure of Ae. aegypti but these studies have only focused on female populations. To address this particular gap, our study compared the population variability and structuring between male and female Ae. aegypti populations using phenotypic (wing geometry) and genetic (microsatellites) data from a highly-urbanized and dengue-endemic region of the Philippines, Metropolitan Manila. MethodsFive mosquito populations comprised of female (n = 137) and male (n = 49) adult Ae. aegypti mosquitoes were used in this study. All mosquito individuals underwent geometric morphometric (26 landmarks), and genetic (11 microsatellite loci) analyses. ResultsResults revealed that FST estimates (genetic) were 0.055 and 0.009 while QST estimates (phenotypic) were 0.318 and 0.309 in in male and female populations, respectively. Wing shape variation plots showed that male populations were distinctly separated from each other while female populations overlapped. Similarly, discriminant analysis of principal components using genetic data revealed that male populations were also distinctly separated from each other while female populations showed near-overlapping populations. Genetic and phenetic dendrograms showed the formation of two groups in male populations but no groups in female populations. Further analysis indicated a significant correlation (r = 0.68, p = 0.02) between the genetic and phenetic distances of male populations. Bayesian analysis using genetic data also detected multiple clusters in male (K = 3) and female (K = 2) populations, while no clusters were detected using the phenotypic data from both sexes. ConclusionsOur results revealed contrasting phenotypic and genetic patterns between male and female Ae. aegypti, indicating that male populations were more spatially structured than female populations. Although genetic markers demonstrated higher sensitivity in detecting population structures than phenotypic markers, correlating patterns of population structure were still observed between the two markers.

zoology↗

bioRxiv2020

PopAmaranth: A population genetic genome browser for grain amaranths and their wild relatives

The last decades of genomic, physiological, and population genetic research have accelerated the understanding and improvement of a numerous crops. The transfer of methods to minor crops could accelerate their improvement if knowledge is effectively shared between disciplines. Grain amaranth is an ancient nutritious pseudocereal from the Americas that is regaining importance due to its high protein content and favorable amino acid and micronutrient composition. To effectively combine genomic and population genetic information with molecular genetics, plant physiology, and use it for interdisciplinary research and crop improvement, an intuitive interaction for scientists across disciplines is essential. Here, we present PopAmaranth, a population genetic genome browser, which provides an accessible representation of the genetic variation of the three grain amaranth species (A. hypochondriacus, A. cruentus, and A. caudatus) and two wild relatives (A. hybridus and A. quitensis) along the A. hypochondriacus reference sequence. We performed population-scale diversity and selection analysis from whole-genome sequencing data of 88 curated genetically and taxonomically unambiguously classified accessions. We incorporate the domestication history of the three grain amaranths to make an evolutionary perspective for candidate genes and regions available. We employ the platform to show that genetic diversity in the water stress-related MIF1 gene declined during amaranth domestication and provide evidence for convergent saponin reduction between amaranth and quinoa. These examples show that our tool enables the detailed study of individual genes, provides target regions for breeding efforts and can enhance the interdisciplinary integration of population genomic findings across species. PopAmaranth is available through amaranthGDB at amaranthgdb.org/popamaranth.html SignificanceSharing population genetic results between disciplines can facilitate interdisciplinary research and accelerate the improvement of crops. Since the onset of genome sequencing online genome browser platforms have provide access to features of an organisms genetic information. Rarely this has been extended to population-wide summary statistics for evolutionary hypothesis testing. We implemented a population genetic genome browser PopAmaranth for three grain amaranth species and their two wild relatives. The intuitive and user-friendly interface of PopA-maranth makes the genetic diversity of the species complex available to broad audience of biologists across disciplines. We show how our tool can be used to study convergence across distant genera and find signals of past selection in domestication and stress related genes. Community platforms and genome browsers are an integrative element of numerous study systems. PopAmaranth can serve as template for other research communities to integrate and share their results.

genomics↗

bioRxiv2021

Plasticity in novel environments induces larger changes in genetic variance than adaptive divergence

Adaptive plasticity allows populations to cope with environmental variation but is expected to fail as conditions become unfamiliar. In novel conditions, populations may instead rely on rapid adaptation to increase fitness and avoid extinction. Adaptation should be fastest when both plasticity and selection occur in directions of the multivariate phenotype that contain abundant genetic variation. However, tests of this prediction from field experiments are rare. Here, we quantify how additive genetic variance in a multivariate phenotype changes across an elevational gradient, and test whether plasticity and selection align with genetic variation. We do so using two closely related, but ecologically distinct, sister species of Sicilian daisy (Senecio, Asteraceae) adapted to high and low elevations on Mount Etna. Using a paternal half-sibling breeding design, we generated and then reciprocally planted c.19,000 seeds of both species, across an elevational gradient spanning each species native elevation, and then quantified mortality and five leaf traits of emergent seedlings. We found that genetic variance in leaf traits changed more across elevations than between species. The high-elevation species at novel lower elevations showed changes in the distribution of genetic variance among the leaf traits, which reduced the amount of genetic variance in the directions of selection and the native phenotype. By contrast, the low-elevation species mainly showed changes in the amount of genetic variance at the novel high elevation, and genetic variance was concentrated in the direction of the native phenotype. For both species, leaf trait plasticity across elevations was in a direction of the multivariate phenotype that contained a moderate amount of genetic variance. Together, these data suggest that where plasticity is adaptive, selection on genetic variance for an initially plastic response could promote adaptation. However, large environmental effects on genetic variance are likely to reduce adaptive potential in novel environments.

evolutionary biology↗

bioRxiv2021

A genetic mouse model with postnatal Nf1 and p53 loss recapitulates the histology and transcriptome of human malignant peripheral nerve sheath tumor

BackgroundMalignant peripheral nerve sheath tumors (MPNST) are aggressive sarcomas. Somatic inactivation of NF1 and cooperating tumor suppressors, including CDKN2A/B, PRC2, and p53, is found in most MPNST. Inactivation of the LATS1/2 kinases of the Hippo pathway was recently shown to cause tumors resembling MPNST histologically, although Hippo pathway mutations are rarely found in MPNST. Because existing genetically engineered mouse (GEM) models of MPNST do not recapitulate some of the key genetic features of human MPNST, we aimed to establish a mouse MPNST model that recapitulated the human disease genetically, histologically, and molecularly. MethodsWe combined two genetically modified alleles, an Nf1;Trp53 cis-conditional allele and an inducible Plp-CreER allele (NP-Plp), to model the somatic, possibly postnatal, mutational events in human MPNST. We also generated conditional Lats1;Lats2 knockout mice. We performed histopathologic analysis of mouse MPNST models and transcriptomic comparison of mouse models and human nerve sheath tumors. ResultsPostnatal Nf1;Trp53 cis-deletion resulted in GEM-MPNST that was histologically more similar to human MPNST than the widely used germline Nf1;Trp53 cis-heterozygous (NPcis) model and showed partial loss of H3K27me3. At the transcriptome level, Nf1;p53-driven GEM-MPNST were distinct from Lats-driven GEM-MPNST and resembled human MPNST more closely than do Lats-driven tumors. ConclusionsThe NP-Plp model recapitulates human MPNST genetically, histologically, and molecularly. Key PointsO_LIPostnatal Nf1;p53 cis-deletion in NP-Plp mice results in tumors similar to MPNST. C_LIO_LIThe transcriptomes of Nf1;p53-driven and Lats-driven MPNST models are distinct. C_LIO_LINP-Plp model resembles human MPNST genetically, histologically, and molecularly. C_LI Importance of the StudyMalignant peripheral nerve sheath tumors (MPNST) are aggressive sarcomas with a poor prognosis and limited treatment options. Existing genetically engineered mouse (GEM) models of MPNST do not recapitulate some of the key genetic features of human MPNST. To model the somatic, possibly postnatal, mutational events seen in MPNST patients, we generated a GEM-MPNST model by combining two genetically modified alleles, an Nf1;Trp53 cis-conditional allele and a Plp-CreER allele. Our histologic and transcriptomic analyses showed that this NP-Plp model resembles human MPNST genetically, histologically, and molecularly--more so than the widely used NPcis model and the recently published Lats-driven model. The NP-Plp model is genetically simple, making it easy to maintain and an ideal platform for preclinical studies. Given its tamoxifen-inducible nature, this model can be used to study the time/stage dependency of the tumorigenic potential of Schwann cells.

cancer biology↗

bioRxiv2021

Macrosystem community assembly patterns are predicted by foundation tree species genetic connectivity and environment across the American Southwest

Macrosystems ecology is an emerging science that aims to integrate traditionally distinct disciplines to predict how hierarchical interacting processes influence the emergence of complex patterns across local to regional and global scales. Despite increased focus on cross-scale relationships and cross-disciplinary integration, few macroecology studies incorporate genetic-based processes. Here we used a community genetics approach to investigate the pattern-process relationships underlying the emergence of macroscale biodiversity patterns. We tested the hypothesis that environmental variation, geography, and genetic connectivity in a foundation tree species differentially predict associated community assembly patterns from local to continental scales. Using genome-wide SNP data, we assessed genetic connectivity as a function of genetic similarity and structure in Fremont cottonwood (Populus fremontii) across its distribution throughout the southwestern US and Mexico. For the same trees, we measured community composition, diversity, and abundance of leaf modifying arthropods and sequenced targeted amplicons of twig fungal endophytes. Five key findings emerged. (1) We identified three primary and six secondary population genetic groups within P. fremontii, which occupy distinct climate niches. (2) Both the leaf modifying arthropod and fungal endophyte communities were significantly differentiated across host tree ecotypes, with genetic distance among sampling locations explaining 13-17% of respective macroscale community structure. (3) For arthropods, environmental distance was the strongest driver of community similarity. (4) Conversely, host genetic connectivity was the most important contributor to macroscale endophyte community structure, with no significant contribution of environmental distance. (5) Furthermore, we observed a shift in the strength of interspecific relationships, with host genetics most strongly influencing associated communities at the intermediate population scale. Our findings suggest that genetic connectivity and environmental variation play integrated roles in macroscale community assembly, and their relative importance changes with scale. Thus, conservation genetic management of the diversity harbored within foundation species is vital for sustaining associated regional biodiversity.

ecology↗

bioRxiv2021

Modeling minimum viable population size with multiple genetic problems of small populations

An important goal for conservation is to define minimum viable population (MVP) sizes for long-term persistence. Although many MVP size estimates focus on ecological processes, with increasing evidence for the role of genetic problems in population extinction, conservation practitioners have also increasingly started to incorporate inbreeding depression (ID). However, small populations also face other genetic problems such as mutation accumulation (MA) and loss of genetic diversity through genetic drift that are usually factored into population viability assessments only via verbal arguments. Comprehensive quantitative theory on interacting genetic problems is missing. Here we develop eco-evolutionary quantitative models that track both population size and levels of genetic diversity. Our models assume a biallelic multilocus genome whose loci can be under either a single or interacting genetic forces. In addition to mutation-selection-drift balance (for loci facing ID and MA), we include three forms of balancing selection (for loci where variation is lost through genetic drift). We define MVP size as the lowest population size that avoids an eco-evolutionary extinction vortex after a time sufficient for an equilibrium allele frequency distribution to establish. Our results show that MVP size decreases rapidly with increasing mutation rates for populations whose genomes are only under balancing selection, while for genomes under mutation-selection-drift balance, the MVP size increases rapidly. MVP sizes also increase rapidly with increasing number of loci under the same or different selection mechanisms until a point is reached at which even arbitrarily large populations cannot survive anymore. In the case of fixed number of loci under selection, interaction of genetic problems did not necessarily increase MVP sizes. To further enhance our understanding about interaction of genetic problems, there is need for more empirical studies to reveal how different genetic processes interact in the genome.

evolutionary biology↗

bioRxiv2021

Genomes contain relics of a triplet code connecting the origins of primordial RNA synthesis to the origins of genetically coded protein synthesis

Life on earth relies on three types of information polymers-DNA, RNA and proteins. In all organisms and viruses, these molecules are synthesized by the copying of pre-existing templates. A triplet-based code known as the genetic code guides the synthesis of proteins by complex enzymatic machines that decode genetic information in RNA sequences. The origin of the genetic code is one of the most fundamental questions in biology. In this study, computational analysis of about 5,000 species level metagenomes using techniques for the analysis of human language suggests that the genomes of extant organisms contain relics of a distinct triplet code that potentially predates the genetic code. This code defines the relationship between adjacent triplets in DNA/RNA sequences, whereby these triplets predominantly differ by a single base. Furthermore, adjacent triplets encode amino acids that are thought to have emerged around the same period in the earths early history. The results suggest that the order of triplets in primordial RNA sequences was associated with the availability of specific amino acids, perhaps due to a coupling of a triplet-based primordial RNA synthesis mechanism to a primitive mechanism of peptide bond formation. Together, this coupling could have given rise to early nucleic acid sequences and a system for encoding amino acid sequences in RNA, i.e. the genetic code. Thus, the central role of triplets in biology potentially extends to the primordial world, contributing to both the origins of genomes and the origins of genetically coded protein synthesis. SignificanceOne of the most intriguing discoveries in biology is that the order of amino acids in each protein is determined by the order of nucleotides (commonly represented by the letters A, U, G, C) in a biological molecule known as RNA. The genetic code serves as a dictionary that maps each of the 64 triplets words in RNA to the 20 amino acids, thereby specifying how information encoded in RNA is decoded into sequences of amino acids (i.e., proteins). The deciphering of the genetic code was one of the greatest discoveries of the 20th century (1968 Nobel Prize in Medicine and Physiology) and is central to modern molecular biology. Yet, how it came to be that the order of triplets in RNA encodes the sequence of the protein synthesized remains one of the most important enigmas of biology. Paradoxically, in all life forms proteins cannot be synthesized without RNA and RNA itself cannot also be synthesized without proteins, presenting a chicken and egg dilemma. By analyzing thousands of microbial genomes using approaches drawn from the field of natural language processing, this study finds that the order of triplets across genomes contains relics of an ancient triplet code, distinct from but closely connected to the genetic code. Unlike the genetic code which specifies the relationship between information in RNA and the sequence of proteins, this ancient code describes the relationship between adjacent triplets in extant genome sequences, whereby such triplets are often different from each other by a single letter. Triplets that are closely related by this ancient code encode amino acids that are thought to have emerged around the same period in the earths early history. In other words, a fossil record of the chronological order of appearance of amino acids on early earth appears written in genome sequences. This potentially demonstrates that the process by which RNA sequences were synthesized in the primordial world relied on triplets and was coupled to amino acids available at the time. Hence, the connections between primordial RNA synthesis and a primitive mechanism for linking amino acids to form peptides could have enabled one type of molecule (RNA) to code for the other (protein), facilitating the emergence of the genetic code.

evolutionary biology↗

bioRxiv2021

Optimizing bulk segregant analysis of drug resistance using Plasmodium falciparum genetic crosses conducted in humanized mice

BackgroundClassical genetic crosses in malaria parasites involve isolation, genotyping, and phenotyping of multiple progeny parasites, which is time consuming and laborious. Bulk segregant analysis (BSA) offers a powerful and efficient alternative to identify loci underlying complex traits in the human malaria parasite, Plasmodium falciparum. MethodsWe have used BSA, which combines genetic crosses using humanized mice with pooled sequencing of progeny populations to measure changes in allele frequency following selection with antimalarial drugs. We used dihydroartemisinin (DHA) drug selection in two genetic crosses (Mal31xKH004 and NF54xNHP1337). We specifically investigated how synchronization, cryopreservation, and the drug selection regimen of progeny pools impacted the success of BSA experiments. FindingsWe detected a strong and repeatable quantitative trait locus (QTL) at chr13 kelch13 locus in both crosses, but did not detect QTLs at ferredoxin (fd), the apicoplast ribosomal protein S10 (arps10), multidrug resistance protein 2 (mdr2). QTLs were detected using synchronized, but not unsynchronized pools, consistent with the stage-specific action of DHA. We also successfully applied BSA to cryopreserved progeny pools. InterpretationOur results provide proof-of-principal of the utility of BSA for rapid, robust genetic mapping of drug resistance loci. Use of cryopreserved progeny pools expands the utility of BSA because we can conduct experiments using archived progeny pools from previous genetic crosses. BSA provides a powerful approach that complements traditional QTL methods for investigating the genetic architecture of resistance to antimalarials, and to reveal new or accessory loci contributing to artemisinin resistance. FundingNational Institutes of Health (NIH); Wellcome trust. O_TEXTBOXResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSGenetic crosses have been immensely successful for determining the genetic basis of drug resistance in malaria parasites, but require laborious cloning, characterization of drug resistance and genome-wide genotyping of individual progeny. This is a major limitation given that genetic crosses can now be conducted efficiently using humanized mice, rather than chimpanzees. Bulk segregant analysis (BSA) provides an attractive alternative approach because (i) large numbers of uncloned recombinant progeny can be analyzed, increasing statistical power (ii) phenotyping is not required, because we identify QTLs by treatment of progeny bulks, and identifying genome regions that show skews in allele frequency after treatment (iii) genome sequencing of bulk samples provides a rapid, accurate readout of genome-wide allele frequencies. This approach has been effectively leveraged in yeast, rodent malaria and several model organisms. Added value of this studyHere we validate and optimize this approach for P. falciparum genetic crosses, focusing on resistance to dihydroartemisin (DHA) a central component of the first-line antimalarial combination. Mutations in kelch13 are known to confer resistance to DHA, but several additional candidate loci have also been suggested to contribute. Our results confirm involvement of kelch13, but did not identify linkage with other putative candidate loci. We optimized methodology, showing that synchronization is critical, and that BSA can be successfully applied to cryopreserved progeny pools. Implications of all the available evidenceBSA combined with recent advances in rapidly generating genetic crosses provides a powerful approach to investigate the genetic basis of drug resistance in P. falciparum. C_TEXTBOX

genomics↗

bioRxiv2022

Genetic diversity varies with species traits and latitude in predatory soil arthropods (Myriapoda: Chilopoda)

AimTo investigate the drivers of intra-specific genetic diversity in centipedes, a group of ancient predatory soil arthropods. LocationGlobal Time periodPresent Major taxa studiedCentipedes (Class: Chilopoda) MethodsWe assembled a database of over 1200 mitochondrial cytochrome c oxidase subunit I sequences representing 120 centipede species from all five orders of Chilopoda. We used this sequence dataset to estimate genetic diversity for centipede species and compared its distribution with estimates from other arthropod groups. We studied the variation in centipede genetic diversity with species traits and biogeography using a beta regression framework, controlling for the effect of shared evolutionary history within a family. ResultsWe observed a wide variation in genetic diversity across centipede species (0 to 0.1713), which falls towards the higher end of values among arthropods. Overall, 21.51% of the variation in mitochondrial COI genetic diversity in centipedes was explained by a combination of predictors related to life history and biogeography. Genetic diversity decreased with body size and latitudinal position of sampled localities, was greater in species showing maternal care and increased with geographic distance among conspecifics. Main conclusionsCentipedes fall towards the higher end of genetic diversity among arthropods, which may be related to their long evolutionary history and low dispersal ability. In centipedes, the negative association of body size with genetic diversity may be mediated by its influence on local abundance or the influence of ecological strategy on long-term population history. Species with maternal care had higher genetic diversity, which goes against our expectations and needs further scrutiny. Hemispheric differences in genetic diversity can be due to historic climatic stability and lower seasonality in the southern hemisphere. Overall, we find that despite the differences in mean genetic diversity among animals, similar processes related to life history strategy and biogeography shape the variation within them.

evolutionary biology↗

bioRxiv2023

Identifying widespread and recurrent variants of genetic parts to improve annotation of engineered DNA sequences

Engineered plasmids have been workhorses of recombinant DNA technology for nearly half a century. Plasmids are used to clone DNA sequences encoding new genetic parts and to reprogram cells by combining these parts in new ways. Historically, many genetic parts on plasmids were copied and reused without routinely checking their DNA sequences. With the widespread use of high-throughput DNA sequencing technologies, we now know that plasmids often contain variants of common genetic parts that differ slightly from their canonical sequences. Because the exact provenance of a genetic part on a particular plasmid is usually unknown, it is difficult to determine whether these differences arose due to mutations during plasmid construction and propagation or due to intentional editing by researchers. In either case, it is important to understand how the sequence changes alter the properties of the genetic part. We analyzed the sequences of over 50,000 engineered plasmids using depositor metadata and a metric inspired by the natural language processing field. We detected 217 uncatalogued genetic part variants that were especially widespread or were likely the result of convergent evolution or engineering. Several of these uncatalogued variants are known mutants of plasmid origins of replication or antibiotic resistance genes that are missing from current annotation databases. However, most are uncharacterized, and 3/5 of the plasmids we analyzed contained at least one of the uncatalogued variants. Our results include a list of genetic parts to prioritize for refining engineered plasmid annotation pipelines, highlight widespread variants of parts that warrant further investigation to see whether they have altered characteristics, and suggest cases where unintentional evolution of plasmid parts may be affecting the reliability and reproducibility of science. Author SummaryPlasmids are used in molecular biology and biotechnology for a wide variety of tasks such as cloning DNA, expressing recombinant proteins, and creating vaccines. One challenge in working with plasmids is that there has been a long, and often lost history of pieces of plasmids being copied and remixed by researchers to create new plasmids. Current databases used for annotating key genetic parts in plasmids are incomplete, especially with respect to cataloguing closely related versions of parts that can have very different characteristics. Some genetic part variants have arisen due to purposeful editing while others are the result of unplanned mutations and evolution. When a researcher finds differences between a database sequence and a genetic part in their newly constructed plasmid, it is often unclear how and when it arose and whether it will affect their experiments. We identified 217 genetic part variants that are either widespread or have likely arisen independently more than once on plasmids due to convergent evolution or engineering. We propose that these variants should be prioritized for inclusion in curated databases of engineered DNA sequences and for functional characterization to improve the reliability and reproducibility of science.

synthetic biology↗

bioRxiv2023

Multi-Scale Cortical Bone Traits Vary in Two Mouse Models of Genetic Diversity

Understanding the genetic basis of cortical bone traits can allow for the discovery of novel genes or biological pathways regulating bone health. Mice are the most widely used mammalian model for skeletal biology and allow for the quantification of traits that cant easily be evaluated in humans, such as osteocyte lacunar morphology. The goal of our study was to investigate the effect of genetic diversity on multi-scale cortical bone traits of three long bones in skeletally-mature mice. We measured bone morphology, mechanical properties, material properties, lacunar morphology, and mineral composition of mouse bones from two populations of genetic diversity. Additionally, we compared how intra-bone relationships varied in the two populations. Our first population of genetic diversity included 72 females and 72 males from the eight Inbred Founder strains used to create the Diversity Outbred (DO) population. These eight strains together span almost 90% of the genetic diversity found in mice (Mus musculus). Our second population of genetic diversity included 25 genetically unique, outbred females and 25 males from the DO population. We show that multi-scale cortical bone traits vary significantly with genetic background; heritability values range from 21% to 99% indicating genetic control of bone traits across length scales. We show for the first time that lacunar shape and number are highly heritable. Comparing the two populations of genetic diversity, we show each DO mouse does not resemble a single Inbred Founder but instead the outbred mice display hybrid phenotypes with the elimination of extreme values. Additionally, intra-bone relationships (e.g., ultimate force vs. cortical area) were mainly conserved in our two populations. Overall, this work supports future use of these genetically diverse populations to discover novel genes contributing to cortical bone traits, especially at the lacunar length scale. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=176 SRC="FIGDIR/small/543484v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@1e61c1org.highwire.dtl.DTLVardef@a3f941org.highwire.dtl.DTLVardef@1411dceorg.highwire.dtl.DTLVardef@bfc8c_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2023

Genetic background influences the 5XFAD Alzheimer's disease mouse model brain proteome

There is a pressing need to improve the translational validity of Alzheimers disease (AD) mouse models. Introducing genetic background diversity in AD mouse models has been proposed as a way to increase validity and enable discovery of previously uncharacterized genetic contributions to AD susceptibility or resilience. However, the extent to which genetic background influences the mouse brain proteome and its perturbation in AD mouse models is unknown. Here we crossed the 5XFAD AD mouse model on a C57BL/6J (B6) inbred background with the DBA/2J (D2) inbred background and analyzed the effects of genetic background variation on the brain proteome in F1 progeny. Both genetic background and 5XFAD transgene insertion strongly affected protein variance in hippocampus and cortex (n=3,368 proteins). Protein co-expression network analysis identified 16 modules of highly co-expressed proteins common across hippocampus and cortex in 5XFAD and non-transgenic mice. Among the modules strongly influenced by genetic background were those related to small molecule metabolism and ion transport. Modules strongly influenced by the 5XFAD transgene were related to lysosome/stress response and neuronal synapse/signaling. The modules with the strongest relationship to human disease--neuronal synapse/signaling and lysosome/stress response--were not significantly influenced by genetic background. However, other modules in 5XFAD that were related to human disease, such as GABA synaptic signaling and mitochondrial membrane modules, were influenced by genetic background. Most disease-related modules were more strongly correlated to AD genotype in hippocampus compared to cortex. Our findings suggest that genetic diversity introduced by crossing B6 and D2 inbred backgrounds influences proteomic changes related to disease in the 5XFAD model, and that proteomic analysis of other genetic backgrounds in transgenic and knock-in AD mouse models is warranted to capture the full range of molecular heterogeneity in genetically diverse models of AD.

neuroscience↗

bioRxiv2024

Genetic architecture of heritable leaf microbes

AbstractHost-associated microbiomes are shaped by both their environment and host genetics, and often impact host performance. The scale of host genetic variation important to microbes is largely unknown, yet fundamental to the community assembly of host-associated microbiomes, and with implications for the eco-evolutionary dynamics of microbes and hosts. Using Ipomoea hederacea, Ivy-leaved morning glory, we generated matrilines differing in quantitative genetic variation and leaf shape, which is controlled by a single Mendelian locus. We then investigated the relative roles of Mendelian and quantitative genetic variation in structuring the leaf microbiome, and how these two sources of genetic variation contributed to microbe heritability. We found that despite large effects of the environment, both Mendelian and quantitative genetic host variation contribute to microbe heritability, and that the cumulative small effect genomic differences due to matriline explained as much or more microbial variation than a single large effect locus. Furthermore, our results are the first to suggest that leaf shape itself contributes to variation in the abundances of some phyllosphere microbes. ImportanceWe investigated how host genetic variation affected the assembly of Ipomoea hederaceas natural microbiome. We found that the genetic architecture of leaf-associated microbiomes involves both quantitative genetic variation and Mendelian traits, with similar contributions to microbe heritability. The existence of Mendelian and quantitative genetic variation for host-associated microbes means that plant evolution at the leaf shape locus or other quantitative genetic loci has the potential to shape microbial abundance, and community composition.

ecology↗