PROC QTL—A SAS Procedure for Mapping Quantitative Trait Loci

Statistical analysis system (SAS) is the most comprehensive statistical analysis software package in the world. It offers data analysis for almost all experiments under various statistical models. Each analysis is performed using a particular subroutine, called a procedure (PROC). For example, PROC ANOVA performs analysis of variances. PROC QTL is a user-defined SAS procedure for mapping quantitative trait loci (QTL). It allows users to perform QTL mapping for continuous and discrete traits within the SAS platform. Users of PROC QTL are able to take advantage of all existing features offered by the general SAS software, for example, data management and graphical treatment. The current version of PROC QTL can perform QTL mapping for all line crossing experiments using maximum likelihood (ML), least square (LS), iteratively reweighted least square (IRLS), Fisher scoring (FISHER), Bayesian (BAYES), and empirical Bayes (EBAYES) methods

Genetic architecture of a key reproductive isolation trait differs between sympatric and non-sympatric sister species of Lake Victoria cichlids

One hallmark of the East African cichlid radiations is the rapid evolution of reproductive isolation that is robust to full sympatry of many closely related species. Theory predicts that species persistence and speciation in sympatry with gene flow are facilitated if loci of large effect or physical linkage (or pleiotropy) underlie traits involved in reproductive isolation. Here, we investigate the genetic architecture of a key trait involved in behavioural isolation, male nuptial coloration, by crossing two sister species pairs of Lake Victoria cichlids of the genus Pundamilia and mapping nuptial coloration in the F2 hybrids. One is a young sympatric species pair, representative of an axis of colour motif differentiation, red-dorsum versus blue, that is highly recurrent in closely related sympatric species. The other is a species pair representative of colour motifs, red-chest versus blue, that are common in allopatric but uncommon in sympatric closely related species. We find significant quantitative trait loci (QTLs) with moderate to large effects (some overlapping) for red and yellowin the sympatric red-dorsum× blue cross, whereas we find no significant QTLs in the non-sympatric red-chest × blue cross. These findings are consistent with theory predicting that large effect loci or linkage/pleiotropy underlying mating trait differentiation could facilitate speciation and species persistence with gene flow in sympatry

Two QTLs govern the resistance to Sclerotinia minor in an interspecific peanut RIL population

Sclerotinia blight is a soilborne disease caused by Sclerotinia minor Jagger and can produce severe decrease in yield. Cultural management strategies and chemical treatment are not completely effective; therefore, growing peanut-resistant varieties is likely to be the most effective control method for this disease. Sclerotinia blight resistance has been identified in wild Arachis species and further transferred to peanut elite cultivars. To identify the genome regions conferring Sclerotinia blight resistance within a tetraploid genetic background, this study evaluated a population of recombinant inbred lines (RIL) with introgressed genes from three wild diploid species: A. cardenasii, A. correntina, and A. batizocoi. Two consistent quantitative trait loci (QTLs), qSbIA04 and qSbIB04 located on chromosomes A04 and B04, respectively, were identified. The QTL qSbIA04 was mapped at 56.39 cM explaining 29% of the phenotypic variance and qSbIB04 was mapped at 13.38 cM explaining 22% of the overall phenotypic variance

WormQTL-public archive and analysis web portal for natural variation data in Caenorhabditis spp

Here, we present WormQTL (http://www.wormqtl.org), an easily accessible database enabling search, comparative analysis and meta-analysis of all data on variation in Caenorhabditis spp. Over the past decade, Caenorhabditis elegans has become instrumental for molecular quantitative genetics and the systems biology of natural variation. These efforts have resulted in a valuable amount of phenotypic, high-throughput molecular and genotypic data across different developmental worm stages and environments in hundreds of C. elegans strains. WormQTL provides a workbench of analysis tools for genotype-phenotype linkage and association mapping based on but not limited to R/qtl (http://www.rqtl.org). All data can be uploaded and downloaded using simple delimited text or Excel formats and are accessible via a public web user interface for biologists and R statistic and web service interfaces for bioinformaticians, based on open source MOLGENIS and xQTL workbench software. WormQTL welcomes data submissions from other worm researcher

A Logistic Model Tree Solution

Beretta, S., Castelli, M., Gonçalves, I., Kel, I., Giansanti, V., & Merelli, I. (2018). Improving eQTL Analysis Using a Machine Learning Approach for Data Integration: A Logistic Model Tree Solution. Journal of Computational Biology, 25(10), 1091-1105. DOI: 10.1089/cmb.2017.0167Expression quantitative trait loci (eQTL) analysis is an emerging method for establishing the impact of genetic variations (such as single nucleotide polymorphisms) on the expression levels of genes. Although different methods for evaluating the impact of these variations are proposed in the literature, the results obtained are mostly in disagreement, entailing a considerable number of false-positive predictions. For this reason, we propose an approach based on Logistic Model Trees that integrates the predictions of different eQTL mapping tools to produce more reliable results. More precisely, we employ a machine learning-based method using logistic functions to perform a linear regression able to classify the predictions of three eQTL analysis tools (namely, R/qtl, MatrixEQTL, and mRMR). Given the lack of a reference dataset and that computational predictions are not so easy to test experimentally, the performance of our approach is assessed using data from the DREAM5 challenge. The results show the quality of the aggregated prediction is better than that obtained by each single tool in terms of both precision and recall. We also performed a test on real data, employing genotypes and microRNA expression profiles from Caenorhabditis elegans, which proved that we were able to correctly classify all the experimentally validated eQTLs. These good results come both from the integration of the different predictions, and from the ability of this machine learning algorithm to find the best cutoff thresholds for each tool. This combination makes our integration approach suitable for improving eQTL predictions for testing in a laboratory, reducing the number of false-positive results.authorsversionpublishe

タイ国における選抜育種に向けたアカマダラハタとタマカイの 雑種ハタF1集団を用いた成長関連形質のQTL解析

東京海洋大学博士学位論文 平成29年度(2017) 応用生命科学 課程博士 甲第440号指導教員: 坂本崇全文公表年月日: 2018-01-05東京海洋大学201

Identification of quantitative trait loci controlling cortical motor evoked potentials in experimental autoimmune encephalomyelitis: correlation with incidence, onset and severity of disease

Experimental autoimmune encephalomyelitis (EAE) is a polygenic chronic inflammatory demyelinating disease of the nervous system, commonly used as an animal model of multiple sclerosis. Previous studies have identified multiple quantitative trait loci (QTLs) controlling different aspects of disease pathogenesis. However, direct genetic control of cortical motor evoked potentials (cMEPs) as a straightforward measure of extent of demyelination or synaptic block has not been investigated earlier. Here, we examined the genetic control of different traits of EAE in a F2 intercross population generated from the EAE susceptible SJL/J (SJL) and the EAE resistant C57BL/10.S (B10.S) mouse strains involving 400 animals. The genotypes of 150 microsatellite markers were determined in each animal and correlated to phenotypic data of onset and severity of disease, cell infiltration and cMEPs. Nine QTLs were identified. Three sex-linked QTLs mapped to chromosomes 2, 10 and 18 linked to disease severity in females, whereas QTLs on chromosomes 1, 8 and 15 linked to the latency of the cMEPs. QTLs affecting T-lymphocyte, B-lymphocyte and microglia infiltration mapped on chromosomes 8 and 15. The cMEP-associated QTLs correlated with incidence, onset or severity of disease, e.g. QTL on chromosome 8, 32-48 cM (EAE 31) (LOD 6.9, P<0.001), associated to cMEP latencies in non-immunized mice and correlated with disease onset and EAE 32 on chromosome 15 linked to cMEP latencies 15 days post-immunization and correlated with disease severity. Additionally, applying tissue microarray technology, we identified QTLs associated to microglia and lymphocytes infiltration on chromosomes 8 and 15, which are different from the QTLs controlling cMEP latencies. There were no alterations in the morphological appearance of the myelin sheaths. Our findings suggest a possible role of myelin composition and/or synaptic transmission in susceptibility to EA

Varying Coefficient Models for Mapping Quantitative Trait Loci Using Recombinant Inbred Intercrosses

There has been a great deal of interest in the development of methodologies to map quantitative trait loci (QTL) using experimental crosses in the last 2 decades. Experimental crosses in animal and plant sciences provide important data sources for mapping QTL through linkage analysis. The Collaborative Cross (CC) is a renewable mouse resource that is generated from eight genetically diverse founder strains to mimic the genetic diversity in humans. The recombinant inbred intercrosses (RIX) generated from CC recombinant inbred (RI) lines share similar genetic structures of F2 individuals but with up to eight alleles segregating at any one locus. In contrast to F2 mice, genotypes of RIX can be inferred from the genotypes of their RI parents and can be produced repeatedly. Also, RIX mice typically do not share the same degree of relatedness. This unbalanced genetic relatedness requires careful statistical modeling to avoid false-positive findings. Many quantitative traits are inherently complex with genetic effects varying with other covariates, such as age. For such complex traits, if phenotype data can be collected over a wide range of ages across study subjects, their dynamic genetic patterns can be investigated. Parametric functions, such as sigmoidal or logistic functions, have been used for such purpose. In this article, we propose a flexible nonparametric time-varying coefficient QTL mapping method for RIX data. Our method allows the QTL effects to evolve with time and naturally extends classical parametric QTL mapping methods. We model the varying genetic effects nonparametrically with the B-spline bases. Our model investigates gene-by-time interactions for RIX data in a very flexible nonparametric fashion. Simulation results indicate that the varying coefficient QTL mapping has higher power and mapping precision compared to parametric models when the assumption of constant genetic effects fails. We also apply a modified permutation procedure to control overall significance level

Mapping QTLs for tolerance to salt stress at the early seedling stage in rice (Oryza sativa L.) using a newly identified donor ‘Madina Koyo’

Open Access Article; Published online: 13 Sep 2020Salt stress is a menace to rice production and a threat to food security worldwide. We evaluated 308 F4 families from Sahel 317/Madina Koyo for tolerance to salt stress at the early seedling stage. To better understand genomic regions controlling tolerance in the population, we genotyped the progenies and the two parents using single nucleotide polymorphism (SNP) markers and regressed the genotypic data on their phenotype to detect QTLs. An average reduction of 63.4% was observed for all fitness-related traits among the F4 families. A total of 46 progenies recorded an average salt injury score (SIS) between 1–3 and were rated as tolerant to salt stress at the early seedling stage. A high-density genetic map was constructed for the 12 rice chromosomes using 3698 SNP markers. Multiple interval mapping identified 13 QTLs for SIS, shoot length, shoot dry weight and root length on chromosomes 2, 3, 4, 6, 7, 10 and 12, with trait increasing alleles coming from both parents. Two (qSDW2 and qRL2.2) and three (qSL2, qRL2.1 and qSIS2) QTLs at different regions on chromosome 2 and another two on chromosome 7 (qSDW7 and qSL7) were tightly linked. These QTLs could facilitate breeding for salt tolerance at the early seedling stage as direct selection for one, would mean indirectly selecting for the other. Fine mapping of these novel QTLs in a different genetic background is necessary to confirm their stability and usefulness in breeding for tolerance to salinity in rice