Genetic Mapping Methods Research Articles

Mapping and Omics Integration: Towards Precise Rice Disease Resistance Breeding.

Rice (Oryza sativa), as a staple crop feeding a significant portion of the global population, particularly in Asian countries, faces constant threats from various diseases jeopardizing global food security. A precise understanding of disease resistance mechanisms is crucial for developing resilient rice varieties. Traditional genetic mapping methods, such as QTL mapping, provide valuable insights into the genetic basis of diseases. However, the complex nature of rice diseases demands a holistic approach to gain an accurate knowledge of it. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, enable a comprehensive analysis of biological molecules, uncovering intricate molecular interactions within the rice plant. The integration of various mapping techniques using multi-omics data has revolutionized our understanding of rice disease resistance. By overlaying genetic maps with high-throughput omics datasets, researchers can pinpoint specific genes, proteins, or metabolites associated with disease resistance. This integration enhances the precision of disease-related biomarkers with a better understanding of their functional roles in disease resistance. The improvement of rice breeding for disease resistance through this integration represents a significant stride in agricultural science because a better understanding of the molecular intricacies and interactions underlying disease resistance architecture leads to a more precise and efficient development of resilient and productive rice varieties. In this review, we explore how the integration of mapping and omics data can result in a transformative impact on rice breeding for enhancing disease resistance.

Identification and validation of seed dormancy loci and candidate genes and construction of regulatory networks by WGCNA in maize introgression lines.

Seventeen PHS-QTLs and candidate genes were obtained, including eleven major loci, three under multiple environments and two with co-localization by the other mapping methods; The functions of three candidate genes were validated using mutants; nine target proteins and five networks were filtered by joint analysis of GWAS and WGCNA. Seed dormancy (SD) and pre-harvest sprouting (PHS) affect yield, as well as grain and hybrid quality in seed production. Therefore, identification of genetic and regulatory pathways underlying PHS and SD is key to gene function analysis, allelic variation mining and genetic improvement. In this study, 78,360 SNPs by SLAF-seq of 230 maize chromosome segment introgression lines (ILs), PHS under five environments were used to conduct GWAS (genome wide association study) (a threshold of 1/n), and seventeen unreported PHS QTLs were obtained, including eleven QTLs with PVE > 10% and three QTLs under multiple environments. Two QTL loci were co-located between the other two genetic mapping methods. Using differential gene expression analyses at two stages of grain development, gene functional analysis of Arabidopsis mutants, and gene functional analysis in the QTL region, seventeen PHS QTL-linked candidate genes were identified, and their five molecular regulatory networks constructed. Based on the Arabidopsis T-DNA mutations, three candidate genes were shown to regulate for SD and PHS. Meanwhile, using RNA-seq of grain development, the weighted correlation network analysis (WGCNA) was performed, deducing five regulatory pathways and target genes that regulate PHS and SD. Based on the conjoint analysis of GWAS and WGCNA, four pathways, nine target proteins and target genes were revealed, most of which regulate cell wall metabolism, cell proliferation and seed dehydration tolerance. This has important theoretical and practical significance for elucidating the genetic basis of maize PHS and SD, as well as mining of genetic resources and genetic improvement of traits.

Genetic structure and molecular mechanism underlying the stalk lodging traits in maize (Zea mays L.)

Stalk lodging seriously affects yield and quality of crops, and it can be caused by several factors, such as environments, developmental stages, and internal chemical components of plant stalks. Breeding of stalk lodging-resistant varieties is thus an important task for maize breeders. To better understand the genetic basis underlying stalk lodging resistance, several methods such as quantitative trait locus (QTL) mapping and genome-wide association study (GWAS) have been used to mine potential gene resources. Based on different types of genetic populations and mapping methods, many significant loci associated with stalk lodging resistance have been identified so far. However, few work has been performed to compare and integrate these reported genetic loci. In this study, we first collected hundreds of QTLs and quantitative trait nucleotides (QTNs) related to stalk lodging traits in maize. Then we mapped and integrated the QTLs and QTNs in maize genome to identify overlapped hotspot regions. Based on the genomic confidence intervals harboring these overlapped hotspot regions, we predicted candidate genes related to stalk lodging traits. Meanwhile, we mapped reported genes to these hotspot regions. Finally, we constructed molecular regulatory networks underlying stalk lodging resistance in maize. Collectively, this study provides not only useful genetic loci for deeply exploring molecular mechanisms of stalk lodging resistance traits, but also potential candidate genes and targeted strategies for improving stalk lodging resistance to increase crop yields in future.

Trait mapping in diverse arthropods by bulked segregant analysis.

Bulked segregant analysis (BSA) is a cross-based method for genetic mapping in sexually reproducing organisms. The method's use of bulked (pooled) samples markedly reduces the genotyping effort associated with traditional linkage mapping studies. Further, it can be applied to species with life histories or physical attributes (as for micro-insects) that render genetic mapping with other methods impractical. Recent studies in both insects and mites have revealed that advanced BSA experimental designs can resolve causal loci to narrow genomic intervals, facilitating follow-up investigations. As high-quality genomes become more widely available, BSA methods are poised to become an increasingly important tool for the rapid mapping of both monogenic and polygenic traits in diverse arthropod species.

Development of an Improved Method for Genetic Fate Mapping of Brain Microglia

As the resident macrophage cells of the brain, microglia are crucial for the phagocytosis of infectious agents, apoptotic cells and synapses. Developmentally, microglia originate from the embryonic yolk sac and serve important roles in the sculpting of neonatal neural circuits. In the context of severe brain injury or infection, bone‐marrow derived macrophages invade neural tissue, making it difficult to distinguish between invading macrophages and resident microglia. Although bone‐marrow derived macrophages can adopt some features of endogenous microglia, they are not able to fully recapitulate all of their properties, suggesting that there may be important functional differences between these two populations of cells. To distinguish between resident microglia and circulating myelogenous macrophages, we generated a P2ry12‐CreER mouse line. P2RY12 is a microglial‐specific nucleotide sensing GPCR that is important for microglial response to tissue damage. The P2ry12‐CreER line was generated by CRISPR‐facilitated homologous recombination and insertion of a 2A‐CreER sequence into the 3’ end of the P2RY12 coding sequence. Using immunofluorescent labeling and flow cytometry, we determined whether this recombination was specific to parenchymal microglia, as compared to meningeal, choroid plexus or perivascular macrophages. We also describe preliminary experiments that involve transcriptional profiling of P2ry12‐CreER recombined cells, using a Cre‐dependent Rpl22‐HA mouse line. Finally, using mouse models of neonatal and adult stroke, we used the P2ry12‐CreER line to fate map true brain microglia in the context of brain injury. Altogether, these results demonstrate the utility of this novel mouse line for genetic recombination, gene expression and fate‐mapping studies of brain microglia.Support or Funding InformationNIH K08NS096192This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Defining the genetic profile of endometriosis.

Endometriosis is a pathological condition which has been extensively studied, since its pathophysiology stems from a broad spectrum of environmental influences and genetic factors. Familial studies aim at defining inheritance trends, while linkage analysis studies focus on the identification of genetic sites related to endometriosis susceptibility. Genetic association studies take into account candidate genes and single nucleotide polymorphisms, and hence target at unraveling the association between disease severity and genetic variation. The common goal of various types of studies is, through genetic mapping methods, the timely identification of therapeutic strategies for disease symptoms, including pelvic pain and infertility, as well as efficient counselling. While genome-wide association studies (GWAS) play a primary role in depicting genetic contributions to disease development, they entail a certain bias as regards the case-control nature of their design and the reproducibility of the results. Nevertheless, genetic-oriented studies and the implementation of the results through clinical tests, hold a considerable advantage in proper disease management. In this review article, we present information about gene-gene and gene-environment interactions involved in endometriosis and discuss the effectiveness of GWAS in identitying novel potential therapeutic targets in an attempt to develop novel therapeutic strategies for a better management and treatment of patients with endometriosis.

What triggers organ transplant rejection?

About half of all transplanted organs get rejected by the body within 10 years. To improve this acceptance rate, researchers want to figure out what triggers the rejection process. Scientists already know that the adaptive immune system, made up of specialized cells such as B cells, is responsible for recognizing and attacking foreign tissue and invaders. But this system is activated by the less-specialized innate immune system, which is less well understood. A team led by Fadi G. Lakkis of the University of Pittsburgh and Jayne S. Danska of the University of Toronto has now identified a key cell receptor in the innate immune response to tissue grafts (Sci. Immunol. 2017, DOI: 10.1126/sciimmunol.aam6202). To find the receptor protein, the researchers studied mice genetically engineered to lack an adaptive immune system. By using a genetic mapping method called positional cloning, the team found that the animals’ innate immune response to a

A New Genetic Method for Subpixel Mapping Using Hyperspectral Images

Subpixel mapping techniques aim to obtain the spatial location and distribution of subpixels by transforming the information coming from a set of input abundance maps into a classification result with higher spatial resolution. However, traditional subpixel mapping algorithms generally ignore the possible errors that are due to abundance estimation inaccuracies by spectral unmixing techniques. In this paper, we propose a new genetic algorithm-based subpixel mapping technique that solves the subpixel mapping problem by correcting the potential errors in the estimated abundance fractions used as input to the subpixel mapping process. The proposed algorithm has been compared with other two genetic subpixel mapping methods, using both synthetic and real hyperspectral images. Our experimental results demonstrate that the proposed approach outperforms traditional subpixel mapping algorithms, thus providing an effective option to improve the accuracy of subpixel mapping for remotely sensed hyperspectral images.

Exploiting Single-Cell Quantitative Data to Map Genetic Variants Having Probabilistic Effects.

Despite the recent progress in sequencing technologies, genome-wide association studies (GWAS) remain limited by a statistical-power issue: many polymorphisms contribute little to common trait variation and therefore escape detection. The small contribution sometimes corresponds to incomplete penetrance, which may result from probabilistic effects on molecular regulations. In such cases, genetic mapping may benefit from the wealth of data produced by single-cell technologies. We present here the development of a novel genetic mapping method that allows to scan genomes for single-cell Probabilistic Trait Loci that modify the statistical properties of cellular-level quantitative traits. Phenotypic values are acquired on thousands of individual cells, and genetic association is obtained from a multivariate analysis of a matrix of Kantorovich distances. No prior assumption is required on the mode of action of the genetic loci involved and, by exploiting all single-cell values, the method can reveal non-deterministic effects. Using both simulations and yeast experimental datasets, we show that it can detect linkages that are missed by classical genetic mapping. A probabilistic effect of a single SNP on cell shape was detected and validated. The method also detected a novel locus associated with elevated gene expression noise of the yeast galactose regulon. Our results illustrate how single-cell technologies can be exploited to improve the genetic dissection of certain common traits. The method is available as an open source R package called ptlmapper.

Construction of a sequence-based bin map and mapping of QTLs for downy mildew resistance at four developmental stages in Chinese cabbage (Brassica rapa L. ssp. pekinensis)

Specific-locus amplified fragment sequencing is a high-resolution method for genetic mapping, genotyping, and single nucleotide polymorphism (SNP) marker discovery. Previously, a major QTL for downy mildew resistance, BraDM, was mapped to linkage group A08 in a doubled-haploid population derived from Chinese cabbage lines 91–112 and T12–19. The aim of the present study was to improve the linkage map and identify the genetic factors involved in downy mildew resistance. We detected 53,692 high quality SLAFs, of which 7230 were polymorphic, and 3482 of the polymorphic markers were used in genetic map construction. The final map included 1064 bins on ten linkage groups and was 858.98 cM in length, with an average inter-locus distance of 0.81 cM. We identified six QTLs that are involved in downy mildew resistance. The four major QTLs, sBrDM8, yBrDM8, rBrDM8, and hBrDM8, for resistance at the seedling, young plant, rosette, and heading stages were mapped to A08, and are identical to BraDM. The two minor resistance QTLs, rBrDM6 (A06) and hBrDM4 (A04), were active at the rosette and heading stages. The major QTL sBrDM8 defined a physical interval of ~228 Kb on A08, and a serine/threonine kinase family gene, Bra016457, was identified as the possible candidate gene. We report here the first high-density bin map for Chinese cabbage, which will facilitate mapping QTLs for economically important traits and SNP marker development. Our results also expand knowledge of downy mildew resistance in Chinese cabbage and provide three SNP markers (A08-709, A08-028, and A08-018) that we showed to be effective when used in MAS to breed for downy mildew resistance in B. rapa.

Association mapping by pooled sequencing identifies TOLL 11 as a protective factor against Plasmodium falciparum in Anopheles gambiae.

BackgroundThe genome-wide association study (GWAS) techniques that have been used for genetic mapping in other organisms have not been successfully applied to mosquitoes, which have genetic characteristics of high nucleotide diversity, low linkage disequilibrium, and complex population stratification that render population-based GWAS essentially unfeasible at realistic sample size and marker density.MethodsWe designed a novel mapping strategy for the mosquito system that combines the power of linkage mapping with the resolution afforded by genetic association. We established founder colonies from West Africa, controlled for diversity, linkage disequilibrium and population stratification. Colonies were challenged by feeding on the infectious stage of the human malaria parasite, Plasmodium falciparum, mosquitoes were phenotyped for parasite load, and DNA pools for phenotypically similar mosquitoes were Illumina sequenced. Phenotype-genotype mapping was carried out in two stages, coarse and fine.ResultsIn the first mapping stage, pooled sequences were analysed genome-wide for intervals displaying relativereduction in diversity between phenotype pools, and candidate genomic loci were identified for influence upon parasite infection levels. In the second mapping stage, focused genotyping of SNPs from the first mapping stage was carried out in unpooled individual mosquitoes and replicates. The second stage confirmed significant SNPs in a locus encoding two Toll-family proteins. RNAi-mediated gene silencing and infection challenge revealed that TOLL 11 protects mosquitoes against P. falciparum infection.ConclusionsWe present an efficient and cost-effective method for genetic mapping using natural variation segregating in defined recent Anopheles founder colonies, and demonstrate its applicability for mapping in a complex non-model genome. This approach is a practical and preferred alternative to population-based GWAS for first-pass mapping of phenotypes in Anopheles. This design should facilitate mapping of other traits involved in physiology, epidemiology, and behaviour.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2009-z) contains supplementary material, which is available to authorized users.

Biallelic and Genome Wide Association Mapping of Germanium Tolerant Loci in Rice (Oryza sativa L.).

Rice plants accumulate high concentrations of silicon. Silicon has been shown to be involved in plant growth, high yield, and mitigating biotic and abiotic stresses. However, it has been demonstrated that inorganic arsenic is taken up by rice through silicon transporters under anaerobic conditions, thus the ability to efficiently take up silicon may be considered either a positive or a negative trait in rice. Germanium is an analogue of silicon that produces brown lesions in shoots and leaves, and germanium toxicity has been used to identify mutants in silicon and arsenic transport. In this study, two different genetic mapping methods were performed to determine the loci involved in germanium sensitivity in rice. Genetic mapping in the biparental cross of Bala × Azucena (an F6 population) and a genome wide association (GWA) study with 350 accessions from the Rice Diversity Panel 1 were conducted using 15 μM of germanic acid. This identified a number of germanium sensitive loci: some co-localised with previously identified quantitative trait loci (QTL) for tissue silicon or arsenic concentration, none co-localised with Lsi1 or Lsi6, while one single nucleotide polymorphism (SNP) was detected within 200 kb of Lsi2 (these are genes known to transport silicon, whose identity was discovered using germanium toxicity). However, examining candidate genes that are within the genomic region of the loci detected above reveals genes homologous to both Lsi1 and Lsi2, as well as a number of other candidate genes, which are discussed.

A novel targeted learning method for quantitative trait loci mapping.

We present a novel semiparametric method for quantitative trait loci (QTL) mapping in experimental crosses. Conventional genetic mapping methods typically assume parametric models with Gaussian errors and obtain parameter estimates through maximum-likelihood estimation. In contrast with univariate regression and interval-mapping methods, our model requires fewer assumptions and also accommodates various machine-learning algorithms. Estimation is performed with targeted maximum-likelihood learning methods. We demonstrate our semiparametric targeted learning approach in a simulation study and a well-studied barley data set.

Quantitative trait loci for growth and body size in the nine‐spined sticklebackPungitius pungitiusL.

Body size is an ecologically important trait shown to be genetically variable both within and among different animal populations as revealed by quantitative genetic studies. However, few studies have looked into underlying genetic architecture of body size variability in the wild using genetic mapping methods. With the aid of quantitative trait loci (QTL) analyses based on 226 microsatellite markers, we mapped body size and growth rate traits in the nine-spined stickleback (Pungitius pungitius) using an F2 -intercross (n=283 offspring) between size-divergent populations. In total, 17 QTL locations were detected. The proportion of phenotypic variation explained by individual body size-related QTL ranged from 3% to 12% and those related to growth parameters and increments from 3% to 10%. Several of the detected QTL affected either early or late growth. These results provide a solid starting point for more in depth investigations of structure and function of genomic regions involved in determination of body size in this popular model of ecological and evolutionary research.

Genetic analysis of structural proteins in the adsorption apparatus of bacteriophage epsilon 15

To probe the organizational structure of the adsorption apparatus of bacteriophage epsilon 15 (E15) using genetic and biochemical methodology Hydroxylamine was used to create nonsense mutants of bacteriophage E15. The mutants were then screened for defects in their adsorption apparatus proteins, initially by measuring the concentrations of free tail spike proteins in lysates of cells that had been infected by the phage mutants under non-permissive growth conditions. Phage strains whose infected cell lysates contained above-average levels of free tail spike protein under non-permissive growth conditions were assumed to contain nonsense mutations in genes coding for adsorption apparatus proteins. These mutants were characterized by classical genetic mapping methods as well as automated sequencing of several of their genes. Finally, sodium dodecyl sulfate-polyacrylamide gel electrophoresis and autoradiography were used to examine the protein compositions of the radioactive particles produced when the various mutants were grown on a non-permissive host cell in the presence of (35)S-methionine and co-purified along with E15wt phage on CsCl block gradients. Our results are consistent with gp4 forming the portal ring structure of E15. In addition, they show that proteins gp15 and gp17 likely comprise the central tube portion of the E15 adsorption apparatus, with gp17 being more distally positioned than gp15 and dependent upon both gp15 and gp16 for its attachment. Finally, our data indicates that tail spike proteins comprised of gp20 can assemble onto nascent virions that contain gp7, gp10, gp4 and packaged DNA, but which lack both gp15 and gp17, thereby forming particles that are of sufficient stability to survive CsCl buoyant density centrifugation. The portal ring (gp4) of E15 is bound to tail spikes (gp20) and the tail tube (gp15 and gp17); gp17's attachment requires both gp15 and gp16.

Hypertrophy and Unconventional Cell Division of Hepatocytes Underlie Liver Regeneration

The size of organs and tissues is basically determined by the number and size of their cells. However, little attention has been paid to this fundamental concept. The liver has a remarkable ability to regenerate after surgical resection (partial hepatectomy [PHx]), and hepatocytes account for about 80% of liver weight, so we investigate how the number and size of hepatocytes contribute to liver regeneration in mice. It has been generally accepted that hepatocytes undergo one or two rounds of cell division after 70% PHx. However, ploidy of hepatocytes is known to increase during regeneration, suggesting an unconventional cell cycle. We therefore examine cell cycle of hepatocytes in detail. By developing a method for genetic fate mapping and a high-throughput imaging system of individual hepatocytes, we show that cellular hypertrophy makes the first contribution to liver regeneration; i.e., regeneration after 30% PHx is achieved solely by hypertrophy without cell division, and hypertrophy precedes proliferation after 70% PHx. Proliferation and hypertrophy almost equally contribute to regeneration after 70% PHx. Furthermore, although most hepatocytes enter cell cycle after 70% PHx, not all hepatocytes undergo cell division. In addition, binuclear hepatocytes undergo reductive divisions to generate two mononuclear daughter hepatocytes in some cases. Our findings demonstrate the importance of hypertrophy and the unconventional cell division cycle of hepatocytes in regeneration, prompting a significant revision of the generally accepted model of liver regeneration.

A statistical method for genetic mapping of sterility genes that exhibit epistasis in remote hybridization of plants using molecular markers in an F2 population

Estimation of the position and effect of sterility genes is an important problem to be solved to understand the sterility mechanism in remote hybridization in plants. In this study, a maximum likelihood (ML) method was used for estimation of the position and effect of sterility genes that exhibit epistasis in an F2 population using the distorted segregation of markers. The ML solutions for recombination fraction and viability were obtained via an expectation-maximization algorithm. The results of Monte Carlo simulations showed that the estimates of recombination fraction and viability were consistent with their true values. The bias and standard deviation of parameters indicated that a larger sample size, closer linkage and lower viability of sterile genes led to better estimates of the parameters involved. A subset of marker data of the F2 population derived from a single cross between the rice japonica cultivar Nipponbare and the indica cultivar Kasalath was analyzed using this method. Eight sterility genes were identified on chromosomes 1, 3, 6, 8 and 10, and significant epistasis was detected among four pairs of sterility genes.

Synteny‐based mapping‐by‐sequencing enabled by targeted enrichment

Mapping-by-sequencing, as implemented in SHOREmap ('SHOREmapping'), is greatly accelerating the identification of causal mutations. The original SHOREmap approach based on resequencing of bulked segregants required a highly accurate and complete reference sequence. However, current whole-genome or transcriptome assemblies from next-generation sequencing data of non-model organisms do not produce chromosome-length scaffolds. We have therefore developed a method that exploits synteny with a related genome for genetic mapping. We first demonstrate how mapping-by-sequencing can be performed using a reduced number of markers, and how the associated decrease in the number of markers can be compensated for by enrichment of marker sequences. As proof of concept, we apply this method to Arabidopsis thaliana gene models ordered by synteny with the genome sequence of the distant relative Brassica rapa, whose genome has several large-scale rearrangements relative to A.thaliana. Our approach provides an alternative method for high-resolution genetic mapping in species that lack finished genome reference sequences or for which only RNA-seq assemblies are available. Finally, for improved identification of causal mutations by fine-mapping, we introduce a new likelihood ratio test statistic, transforming local allele frequency estimations into a confidence interval similar to conventional mapping intervals.

Mutation mapping and identification by whole-genome sequencing

Genetic mapping of mutations in model systems has facilitated the identification of genes contributing to fundamental biological processes including human diseases. However, this approach has historically required the prior characterization of informative markers. Here we report a fast and cost-effective method for genetic mapping using next-generation sequencing that combines single nucleotide polymorphism discovery, mutation localization, and potential identification of causal sequence variants. In contrast to prior approaches, we have developed a hidden Markov model to narrowly define the mutation area by inferring recombination breakpoints of chromosomes in the mutant pool. In addition, we created an interactive online software resource to facilitate automated analysis of sequencing data and demonstrate its utility in the zebrafish and mouse models. Our novel methodology and online tools will make next-generation sequencing an easily applicable resource for mutation mapping in all model systems.

High-resolution genetic mapping with pooled sequencing

BackgroundModern genetics has been transformed by high-throughput sequencing. New experimental designs in model organisms involve analyzing many individuals, pooled and sequenced in groups for increased efficiency. However, the uncertainty from pooling and the challenge of noisy sequencing data demand advanced computational methods.ResultsWe present MULTIPOOL, a computational method for genetic mapping in model organism crosses that are analyzed by pooled genotyping. Unlike other methods for the analysis of pooled sequence data, we simultaneously consider information from all linked chromosomal markers when estimating the location of a causal variant. Our use of informative sequencing reads is formulated as a discrete dynamic Bayesian network, which we extend with a continuous approximation that allows for rapid inference without a dependence on the pool size. MULTIPOOL generalizes to include biological replicates and case-only or case-control designs for binary and quantitative traits.ConclusionsOur increased information sharing and principled inclusion of relevant error sources improve resolution and accuracy when compared to existing methods, localizing associations to single genes in several cases. MULTIPOOL is freely available at http://cgs.csail.mit.edu/multipool/.