QTL mapping for yield components in a tropical maize population using microsatellite markers

QTL mapping provides usefull information for breeding programs since it allows the estimation of genomic locations and genetic effects of chromossomal regions related to the expression of quantitative traits. The objective of this study was to map QTL related to several agronomic important traits associated with grain yield: ear weight (EW), prolificacy (PROL), ear number (NE), ear length (EL) and diameter (ED), number of rows on the ear (NRE) and number of kernels per row on the ear (NKPR). Four hundred F-2:3 tropical maize progenies were evaluated in five environments in Piracicaba, Sao Paulo, Brazil. The genetic map was previously estimated and had 117 microssatelite loci with average distance of 14 cM. Data was analysed using Composite Interval Mapping for each trait. Thirty six QTL were mapped and related to the expression of EW (2), PROL (3), NE (2), EL (5), ED (5), NRE (10), NKPR (5). Few QTL were mapped since there was high GxE interaction. Traits EW, PROL and EN showed high genetic correlation with grain yield and several QTL mapped to similar genomic regions, which could cause the observed correlation. However, further analysis using apropriate statistical models are required to separate linked versus pleiotropic QTL. Five QTL (named Ew1, Ne1, Ed3, Nre3 and Nre10) had high genetic effects, explaining from 10.8% (Nre3) to 16.9% (Nre10) of the phenotypic variance, and could be considered in further studies.

QTL mapping for reaction to Phaeosphaeria leaf spot in a tropical maize population

Phaeosphaeria leaf spot (PLS) is an important disease in tropical and subtropical maize (Zea mays, L.) growing areas, but there is limited information on its inheritance. Thus, this research was conducted to study the inheritance of the PLS disease in tropical maize by using QTL mapping and to assess the feasibility of using marker-assisted selection aimed to develop genotypes resistance to this disease. Highly susceptible L14-04B and highly resistant L08-05F inbred lines were crossed to develop an F(2) population. Two-hundred and fifty six F(2) plants were genotyped with 143 microsatellite markers and their F(2:3) progenies were evaluated at seven environments. Ten plants per plot were evaluated 30 days after silk emergence following a rating scale, and the plot means were used for analyses. The heritability coefficient on a progeny mean basis was high (91.37%), and six QTL were mapped, with one QTL on chromosomes 1, 3, 4, and 6, and two QTL on chromosome 8. The gene action of the QTL ranged from additive to partial dominance, and the average level of dominance was partial dominance; also a dominance x dominance epistatic effect was detected between the QTL mapped on chromosome 8. The phenotypic variance explained by each QTL ranged from 2.91 to 11.86%, and the joint QTL effects explained 41.62% of the phenotypic variance. The alleles conditioning resistance to PLS disease of all mapped QTL were in the resistant parental inbred L08-05F. Thus, these alleles could be transferred to other elite maize inbreds by marker-assisted backcross selection to develop hybrids resistant to PLS disease.

Mapeo de QTL para Mal de Río Cuarto en maíz. QTL mapping for tolerance to Mal de Río Cuarto disease in maize.

El Mal de Río Cuarto (MRC) es una enfermedad del maíz (Zea mays L.), endémica de ciertas zonas de la Argentina y constituye la patología más importante de este cultivo por la severidad de los daños y por la creciente difusión del área geográfica afectada. El empleo de la resistencia genética bajo un manejo integrado de la enfermedad, constituye la estrategia más económica y ambientalmente sustentable para lograr el incremento y la estabilidad en la producción de los cultivos de maíz, reduciendo el uso nocivo de agroquímicos. La reacción a la enfermedad MRC se encuentra influida por una fuerte interacción genotipo-ambiente que dificulta el mejoramiento genético. En los ensayos multiambientales la inconsistencia de la respuesta y la inestabilidad de los genotipos ensayados hace dificultoso llevar a cabo una buena selección basada en los síntomas de la enfermedad. Para contribuir a aumentar la eficacia de los métodos de mejoramiento es posible implementar programas en los que se incluyan herramientas biotecnológicas como los marcadores moleculares, que permiten reducir el efecto ambiental y contribuyen a soslayar, al menos en parte, los inconvenientes planteados por los efectos de la interacción genotipo-ambiente facilitando la identificación de los genotipos buscados. La selección fenotípica realizada convencionalmente, puede ser complementada con la selección asistida por marcadores (marker-assisted selection MAS) consistente en utilizar la información genética que brindan marcadores moleculares de ADN, tales como los SSR, asociados a loci o segmentos cromosómicos (quantitative trait loci QTL) que confieran resistencia a MRC. Si bien los resultados preliminares obtenidos por nuestro grupo de trabajo señalan la presencia de posibles QTLs e informan que la reacción frente a la enfermedad tiene una moderada heredabilidad y una substancial variación debida a la interacción genotipo-ambiente, es necesario confirmar los resultados relativos a los parámetros poblacionales y obtener una mejor delimitación de las regiones genómicas identificadas. Con la finalidad de aumentar la eficiencia de los programas de mejoramiento en el desarrollo de genotipos tolerantes mediante la selección asistida por marcadores utilizando una población de mapeo F2 con un fondo genético diferente y líneas endocriadas recombinantes evaluadas en ensayos multiambientales, se proponen los siguientes objetivos (i) estudiar la forma de herencia de la reacción frente a MRC, (ii) identificar nuevos QTLs asociados a este carácter y (iii) verificar la consistencia de los QTLs identificados previamente.

QTL mapping for protein content in soybean cultivated in two tropical environments

The objectives of this study were to detect quantitative trait loci (QTL) for protein content in soybean grown in two distinct tropical environments and to build a genetic map for protein content. One hundred eighteen soybean recombinant inbred lines (RIL), obtained from a cross between cultivars BARC 8 and Garimpo, were used. The RIL were cultivated in two distinct Brazilian tropical environments: Cascavel county, in Paraná, and Viçosa county, in Minas Gerais (24º57'S, 53º27'W and 20º45'S, 42º52'W, respectively). Sixty-six SSR primer pairs and 65 RAPD primers were polymorphic and segregated at a 1:1 proportion. Thirty poorly saturated linkage groups were obtained, with 90 markers and 41 nonlinked markers. For the lines cultivated in Cascavel, three QTL were mapped in C2, E and N linkage groups, which explained 14.37, 10.31 and 7.34% of the phenotypic variation of protein content, respectively. For the lines cultivated in Viçosa, two QTL were mapped in linkage groups G and #1, which explained 9.51 and 7.34% of the phenotypic variation of protein content. Based on the mean of the two environments, two QTL were identified: one in the linkage group E (9.90%) and other in the group L (7.11%). In order for future studies to consistently detect QTL effects of different environments, genotypes with greater stability should be used.

qtl.outbred: Interfacing outbred line cross data with the R/qtl mapping software

Background qtl.outbred is an extendible interface in the statistical environment, R, for combining quantitative trait loci (QTL) mapping tools. It is built as an umbrella package that enables outbred genotype probabilities to be calculated and/or imported into the software package R/qtl. Findings Using qtl.outbred, the genotype probabilities from outbred line cross data can be calculated by interfacing with a new and efficient algorithm developed for analyzing arbitrarily large datasets (included in the package) or imported from other sources such as the web-based tool, GridQTL. Conclusion qtl.outbred will improve the speed for calculating probabilities and the ability to analyse large future datasets. This package enables the user to analyse outbred line cross data accurately, but with similar effort than inbred line cross data.

Genetic parameters for body weight, carcass chemical composition and yield in a broiler-layer cross developed for QTL mapping

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic analysis of kernel oil content in tropical maize with design III and QTL mapping

Oil content and grain yield in maize are negatively correlated, and so far the development of high-oil high-yielding hybrids has not been accomplished. Then a fully understand of the inheritance of the kernel oil content is necessary to implement a breeding program to improve both traits simultaneously. Conventional and molecular marker analyses of the design III were carried out from a reference population developed from two tropical inbred lines divergent for kernel oil content. The results showed that additive variance was quite larger than the dominance variance, and the heritability coefficient was very high. Sixteen QTL were mapped, they were not evenly distributed along the chromosomes, and accounted for 30.91% of the genetic variance. The average level of dominance computed from both conventional and QTL analysis was partial dominance. The overall results indicated that the additive effects were more important than the dominance effects, the latter were not unidirectional and then heterosis could not be exploited in crosses. Most of the favorable alleles of the QTL were in the high-oil parental inbred, which could be transferred to other inbreds via marker-assisted backcross selection. Our results coupled with reported information indicated that the development of high-oil hybrids with acceptable yields could be accomplished by using marker-assisted selection involving oil content, grain yield and its components. Finally, to exploit the xenia effect to increase even more the oil content, these hybrids should be used in the Top Cross((TM)) procedure.

Gene by environment QTL mapping through multiple trait analyses in blood pressure salt-sensitivity: identification of a novel QTL in rat chromosome 5

Background The genetic mechanisms underlying interindividual blood pressure variation reflect the complex interplay of both genetic and environmental variables. The current standard statistical methods for detecting genes involved in the regulation mechanisms of complex traits are based on univariate analysis. Few studies have focused on the search for and understanding of quantitative trait loci responsible for gene × environmental interactions or multiple trait analysis. Composite interval mapping has been extended to multiple traits and may be an interesting approach to such a problem. Methods We used multiple-trait analysis for quantitative trait locus mapping of loci having different effects on systolic blood pressure with NaCl exposure. Animals studied were 188 rats, the progenies of an F2 rat intercross between the hypertensive and normotensive strain, genotyped in 179 polymorphic markers across the rat genome. To accommodate the correlational structure from measurements taken in the same animals, we applied univariate and multivariate strategies for analyzing the data. Results We detected a new quantitative train locus on a region close to marker R589 in chromosome 5 of the rat genome, not previously identified through serial analysis of individual traits. In addition, we were able to justify analytically the parametric restrictions in terms of regression coefficients responsible for the gain in precision with the adopted analytical approach. Conclusion Future work should focus on fine mapping and the identification of the causative variant responsible for this quantitative trait locus signal. The multivariable strategy might be valuable in the study of genetic determinants of interindividual variation of antihypertensive drug effectiveness.

USE OF HIDDEN MARKOV MODELS FOR QTL MAPPING

An important aspect of the QTL mapping problem is the treatment of missing genotype data. If complete genotype data were available, QTL mapping would reduce to the problem of model selection in linear regression. However, in the consideration of loci in the intervals between the available genetic markers, genotype data is inherently missing. Even at the typed genetic markers, genotype data is seldom complete, as a result of failures in the genotyping assays or for the sake of economy (for example, in the case of selective genotyping, where only individuals with extreme phenotypes are genotyped). We discuss the use of algorithms developed for hidden Markov models (HMMs) to deal with the missing genotype data problem.

Copulas in QTL mapping

The standard variance components method for mapping quantitative trait loci is derived on the assumption of normality. Unsurprisingly, statistical tests based on this method do not perform so well if this assumption is not satisfied. We use the statistical concept of copulas to relax the assumption of normality and derive a test that can perform well under any distribution of the continuous trait. In particular, we discuss bivariate normal copulas in the context of sib-pair studies. Our approach is illustrated by a linkage analysis of lipoprotein(a) levels, whose distribution is highly skewed. We demonstrate that the asymptotic critical levels of the test can still be calculated using the interval mapping approach. The new method can be extended to more general pedigrees and multivariate phenotypes in a similar way as the original variance components method.

QTL mapping identifies novel major loci for ear fasciation, ear prolificacy and tillering in maize (ZEA MAYS L.)

Maize ear fasciation originates from excessive or abnormal proliferation of the ear meristem and usually manifests as multiple-tipped ear, ear flatness and/or disordered kernel arrangement. Ear prolificacy expresses as multiple ears per node. Both traits can affect grain yield. In this study, the genetic control of the two traits was analyzed using two recombinant inbred lines (RIL) populations (B73 × Lo1016 and Lo964 × Lo1016) with Lo1016 and Lo964 as donors of ear fasciation and prolificacy, respectively. Four ear fasciation-related traits (ear fasciation, kernel distribution and ear ovality indexes and ratio of ear diameters), number of kernel rows, ear prolificacy and number of tillers were phenotyped in multi-year field experiments. Ear fasciation traits and number of kernel rows showed relatively high heritability (h2 > 0.5) except ratio of ear diameters, and showed correlation. Prolificacy and tillering h2 ranged 0.41 - 0.78 and did not correlate. QTL mapping identified four QTL for ear fasciation, on chr. 1 (two QTLs), 5 and 7, the latter two overlapping with QTLs for number of kernel rows. However, the strongest effect QTL for number of kernel rows mapped on chr. 2 independently from ear fasciation. Four and five non-overlapping QTLs were mapped for ear prolificacy and tillering, respectively. Two ear fasciation QTLs from this study, qFas1.2 and qFas7, overlapped with formerly known fasciation QTLs and spanned candidate genes expressed in ear meristems namely compact plant2 and ramosa1. Our study identified novel ear fasciation, ear prolificacy and tillering loci which are unexpectedly still segregating in elite maize materials, and provides foundation for genomics-assisted breeding for yield components

A multiparental cross population for mapping QTL for relevant agronomic traits in durum wheat (Triticum durum Desf.)

Multiparental cross designs for mapping quantitative trait loci (QTL) in crops are efficient alternatives to conventional biparental experimental populations because they exploit a broader genetic basis and higher mapping resolution. We describe the development and deployment of a multiparental recombinant inbred line (RIL) population in durum wheat (Triticum durum Desf.) obtained by crossing four elite cultivars characterized by different traits of agronomic value. A linkage map spanning 2,663 cM and including 7,594 single nucleotide polymorphisms (SNPs) was produced by genotyping 338 RILs with a wheat-dedicated 90k SNP chip. A cluster file was developed for correct allele calling in the framework of the tetraploid durum wheat genome. Based on phenotypic data collected over four field experiments, a multi-trait quantitative trait loci (QTL) analysis was carried out for 18 traits of agronomic relevance (including yield, yield-components, morpho-physiological and seed quality traits). Across environments, a total of 63 QTL were identified and characterized in terms of the four founder haplotypes. We mapped two QTL for grain yield across environments and 23 QTL for grain yield components. A novel major QTL for number of grain per spikelet/ear was mapped on chr 2A and shown to control up to 39% of phenotypic variance in this cross. Functionally different QTL alleles, in terms of direction and size of genetic effect, were distributed among the four parents. Based on the occurrence of QTL-clusters, we characterized the breeding values (in terms of effects on yield) of most of QTL for heading and maturity as well as yield component and quality QTL. This multiparental RIL population provides the wheat community with a highly informative QTL mapping resource enabling the dissection of the genetic architecture of multiple agronomic relevant traits in durum wheat.

Genetic parameters and mapping quantitative trait loci associated with tibia traits in broilers.

Abstract: Selection among broilers for performance traits is resulting in locomotion problems and bone disorders, once skeletal structure is not strong enough to support body weight in broilers with high growth rates. In this study, genetic parameters were estimated for body weight at 42 days of age (BW42), and tibia traits (length, width, and weight) in a population of broiler chickens. Quantitative trait loci (QTL) were identified for tibia traits to expand our knowledge of the genetic architecture of the broiler population. Genetic correlations ranged from 0.56 +/- 0.18 (between tibia length and BW42) to 0.89 +/- 0.06 (between tibia width and weight), suggesting that these traits are either controlled by pleiotropic genes or by genes that are in linkage disequilibrium. For QTL mapping, the genome was scanned with 127 microsatellites, representing a coverage of 2630 cM. Eight QTL were mapped on Gallus gallus chromosomes (GGA): GGA1, GGA4, GGA6, GGA13, and GGA24. The QTL regions for tibia length and weight were mapped on GGA1, between LEI0079 and MCW145 markers. The gene DACH1 is located in this region; this gene acts to form the apical ectodermal ridge, responsible for limb development. Body weight at 42 days of age was included in the model as a covariate for selection effect of bone traits. Two QTL were found for tibia weight on GGA2 and GGA4, and one for tibia width on GGA3. Information originating from these QTL will assist in the search for candidate genes for these bone traits in future studies.

Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation

This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

MAPfastR : quantitative trait loci mapping in outbred line crosses

MAPfastR is a software package developed to analyze QTL data from inbred and outbred line-crosses. The package includes a number of modules for fast and accurate QTL analyses. It has been developed in the R language for fast and comprehensive analyses of large datasets. MAPfastR is freely available at: http://www.computationalgenetics.se/?page_id=7.