Mapping gene expression quantitative trait loci by singular value decomposition and independent component analysis

Background  

The combination of gene expression profiling with linkage analysis has become a powerful paradigm for mapping gene expression quantitative trait loci (eQTL). To date, most studies have searched for eQTL by analyzing gene expression traits one at a time. As thousands of expression traits are typically analyzed, this can reduce power because of the need to correct for the number of hypothesis tests performed. In addition, gene expression traits exhibit a complex correlation structure, which is ignored when analyzing traits individually.     

A general and efficient method for estimating continuous IBD functions for use in genome scans for QTL

Background  

Identity by descent (IBD) matrix estimation is a central component in mapping of Quantitative Trait Loci (QTL) using variance component models. A large number of algorithms have been developed for estimation of IBD between individuals in populations at discrete locations in the genome for use in genome scans to detect QTL affecting various traits of interest in experimental animal, human and agricultural pedigrees. Here, we propose a new approach to estimate IBD as continuous functions rather than as discrete values.     

Transmission ratio distortion results in asymmetric introgression in Louisiana Iris

Background  

Linkage maps are useful tools for examining both the genetic architecture of quantitative traits and the evolution of reproductive incompatibilities. We describe the generation of two genetic maps using reciprocal interspecific backcross 1 (BC₁) mapping populations from crosses between Iris brevicaulis and Iris fulva. These maps were constructed using expressed sequence tag (EST)- derived codominant microsatellite markers. Such a codominant marker system allowed for the ability to link the two reciprocal maps, and compare patterns of transmission ratio distortion observed between the two.     

Variations in genome-wide gene expression in identical twins – a study of primary osteoblast-like culture from female twins discordant for osteoporosis

Background  

Monozygotic twin pairs who are genetically identical would be potentially useful in gene expression study for specific traits as cases and controls, because there would be much less gene expression variation within pairs compared to two unrelated individuals. However the twin pair has to be discordant for the particular trait or phenotype excluding those resulting from known confounders. Such discordant monozygotic twin pairs are rare and very few studies have explored the potential usefulness of this approach.     

Comparative analysis of haplotype association mapping algorithms

Background  

Finding the genetic causes of quantitative traits is a complex and difficult task. Classical methods for mapping quantitative trail loci (QTL) in miceuse an F2 cross between two strains with substantially different phenotype and an interval mapping method to compute confidence intervals at each position in the genome. This process requires significant resources for breeding and genotyping, and the data generated are usually only applicable to one phenotype of interest. Recently, we reported the application of a haplotype association mapping method which utilizes dense genotyping data across a diverse panel of inbred mouse strains and a marker association algorithm that is independent of any specific phenotype. As the availability of genotyping data grows in size and density, analysis of these haplotype association mapping methods should be of increasing value to the statistical genetics community.     

HaploRec: efficient and accurate large-scale reconstruction of haplotypes

Background  

Haplotypes extracted from human DNA can be used for gene mapping and other analysis of genetic patterns within and across populations. A fundamental problem is, however, that current practical laboratory methods do not give haplotype information. Estimation of phased haplotypes of unrelated individuals given their unphased genotypes is known as the haplotype reconstruction or phasing problem.     

DNA polymorphisms and haplotype patterns of transcription factors involved in barley endosperm development are associated with key agronomic traits

Background  

Association mapping is receiving considerable attention in plant genetics for its potential to fine map quantitative trait loci (QTL), validate candidate genes, and identify alleles of interest. In the present study association mapping in barley (Hordeum vulgare L.) is investigated by associating DNA polymorphisms with variation in grain quality traits, plant height, and flowering time to gain further understanding of gene functions involved in the control of these traits. We focused on the four loci BLZ1, BLZ2, BPBF and HvGAMYB that play a role in the regulation of B-hordein expression, the major fraction of the barley storage protein. The association was tested in a collection of 224 spring barley accessions using a two-stage mixed model approach.     

Functional mapping imprinted quantitative trait loci underlying developmental characteristics

Background

Genomic imprinting, a phenomenon referring to nonequivalent expression of alleles depending on their parental origins, has been widely observed in nature. It has been shown recently that the epigenetic modification of an imprinted gene can be detected through a genetic mapping approach. Such an approach is developed based on traditional quantitative trait loci (QTL) mapping focusing on single trait analysis. Recent studies have shown that most imprinted genes in mammals play an important role in controlling embryonic growth and post-natal development. For a developmental character such as growth, current approach is less efficient in dissecting the dynamic genetic effect of imprinted genes during individual ontology.

Results

Functional mapping has been emerging as a powerful framework for mapping quantitative trait loci underlying complex traits showing developmental characteristics. To understand the genetic architecture of dynamic imprinted traits, we propose a mapping strategy by integrating the functional mapping approach with genomic imprinting. We demonstrate the approach through mapping imprinted QTL controlling growth trajectories in an inbred F₂ population. The statistical behavior of the approach is shown through simulation studies, in which the parameters can be estimated with reasonable precision under different simulation scenarios. The utility of the approach is illustrated through real data analysis in an F₂ family derived from LG/J and SM/J mouse stains. Three maternally imprinted QTLs are identified as regulating the growth trajectory of mouse body weight.

Conclusion

The functional iQTL mapping approach developed here provides a quantitative and testable framework for assessing the interplay between imprinted genes and a developmental process, and will have important implications for elucidating the genetic architecture of imprinted traits.     

Combinatorial Conflicting Homozygosity (CCH) analysis enables the rapid identification of shared genomic regions in the presence of multiple phenocopies

Background

The ability to identify regions of the genome inherited with a dominant trait in one or more families has become increasingly valuable with the wide availability of high throughput sequencing technology. While a number of methods exist for mapping of homozygous variants segregating with recessive traits in consanguineous families, dominant conditions are conventionally analysed by linkage analysis, which requires computationally demanding haplotype reconstruction from marker genotypes and, even using advanced parallel approximation implementations, can take substantial time, particularly for large pedigrees. In addition, linkage analysis lacks sensitivity in the presence of phenocopies (individuals sharing the trait but not the genetic variant responsible). Combinatorial Conflicting Homozygosity (CCH) analysis uses high density biallelic single nucleotide polymorphism (SNP) marker genotypes to identify genetic loci within which consecutive markers are not homozygous for different alleles. This allows inference of identical by descent (IBD) inheritance of a haplotype among a set or subsets of related or unrelated individuals.

Results

A single genome-wide conflicting homozygosity analysis takes <3 seconds and parallelisation permits multiple combinations of subsets of individuals to be analysed quickly. Analysis of unrelated individuals demonstrated that in the absence of IBD inheritance, runs of no CH exceeding 4 cM are not observed. At this threshold, CCH is >97% sensitive and specific for IBD regions within a pedigree exceeding this length and was able to identify the locus responsible for a dominantly inherited kidney disease in a Turkish Cypriot family in which six out 17 affected individuals were phenocopies. It also revealed shared ancestry at the disease-linked locus among affected individuals from two different Cypriot populations.

Conclusions

CCH does not require computationally demanding haplotype reconstruction and can detect regions of shared inheritance of a haplotype among subsets of related or unrelated individuals directly from SNP genotype data. In contrast to parametric linkage allowing for phenocopies, CCH directly provides the exact number and identity of individuals sharing each locus. CCH can also identify regions of shared ancestry among ostensibly unrelated individuals who share a trait. CCH is implemented in Python and is freely available (as source code) from http://sourceforge.net/projects/cchsnp/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1360-4) contains supplementary material, which is available to authorized users.     

A comprehensive and precise set of intervarietal substitution lines to identify candidate genes and quantitative trait loci in oilseed rape (<Emphasis Type="Italic">Brassica napus</Emphasis> L.)

Key message

A set of intervarietal substitution lines were developed in rapeseed by recurrent backcrossing and marker-assisted selection and employed for mapping both qualitative and quantitative traits.

Abstract

Intervarietal substitution lines (ISLs) may be assembled into advanced secondary mapping populations that have remarkable potential for resolving trait loci and mapping candidate genes. To facilitate the identification of important genes in oilseed rape (canola, Brassica napus), we developed 89 ISLs using an elite cultivar ‘Zhongyou 821’ (ZY821) as the recipient and a re-synthesized line ‘No.2127’ as the donor. In the whole process of ISLs development, the target chromosome segments were selected based on the genotypes of 300 microsatellite markers evenly distributed across the genome. Eighty-nine ISLs fixed at BC₅F₄ were genotyped by sequencing using double digestion to survey the lengths of target substitution segments from the donor parent and the background segments from the recurrent parent. The total length of the substituted chromosome segments was 3030.27 Mb, representing 3.56?×?of the Darmor-bzh reference genome sequence (version 4.1). Gene mapping was conducted for two qualitative traits, flower colour and seed-coat colour, and nine quantitative traits including yield- and quality-related traits, with 19 QTLs identified for the latter. Overlapping substitution segments were identified for flower colour and seed-coat colour loci, as well as for QTLs consistently detected in 2 or 3 years. These results demonstrate the value of these ISLs for locus resolution and subsequent cloning, targeted mutation or editing of genes controlling important traits in oilseed rape.

     

Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies

Background  

Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS.     

The bovine QTL viewer: a web accessible database of bovine Quantitative Trait Loci

Background  

Many important agricultural traits such as weight gain, milk fat content and intramuscular fat (marbling) in cattle are quantitative traits. Most of the information on these traits has not previously been integrated into a genomic context. Without such integration application of these data to agricultural enterprises will remain slow and inefficient. Our goal was to populate a genomic database with data mined from the bovine quantitative trait literature and to make these data available in a genomic context to researchers via a user friendly query interface.     

Multipoint-likelihood maximization mapping on 4 segregating populations to achieve an integrated framework map for QTL analysis in pot azalea (Rhododendron simsii hybrids)

Background  

Azalea (Rhododendron simsii hybrids) is the most important flowering pot plant produced in Belgium, being exported world-wide. In the breeding program, flower color is the main feature for selection, only in later stages cultivation related plant quality traits are evaluated. As a result, plants with attractive flowering are kept too long in the breeding cycle. The inheritance of flower color has been well studied; information on the heritability of cultivation related quality traits is lacking. For this purpose, QTL mapping in diverse genetic backgrounds appeared to be a must and therefore 4 mapping populations were made and analyzed.     

solQTL: a tool for QTL analysis,visualization and linking to genomes at SGN database

Background  

A common approach to understanding the genetic basis of complex traits is through identification of associated quantitative trait loci (QTL). Fine mapping QTLs requires several generations of backcrosses and analysis of large populations, which is time-consuming and costly effort. Furthermore, as entire genomes are being sequenced and an increasing amount of genetic and expression data are being generated, a challenge remains: linking phenotypic variation to the underlying genomic variation. To identify candidate genes and understand the molecular basis underlying the phenotypic variation of traits, bioinformatic approaches are needed to exploit information such as genetic map, expression and whole genome sequence data of organisms in biological databases.     

Empirically derived phenotypic subgroups – qualitative and quantitative trait analyses

Background

The Framingham Heart Study has contributed a great deal to advances in medicine. Most of the phenotypes investigated have been univariate traits (quantitative or qualitative). The aims of this study are to derive multivariate traits by identifying homogeneous groups of people and assigning both qualitative and quantitative trait scores; to assess the heritability of the derived traits; and to conduct both qualitative and quantitative linkage analysis on one of the heritable traits.

Methods

Multiple correspondence analysis, a nonparametric analogue of principal components analysis, was used for data reduction. Two-stage clustering, using both k-means and agglomerative hierarchical clustering, was used to cluster individuals based upon axes (factor) scores obtained from the data reduction. Probability of cluster membership was calculated using binary logistic regression. Heritability was calculated using SOLAR, which was also used for the quantitative trait analysis. GENEHUNTER-PLUS was used for the qualitative trait analysis.

Results

We found four phenotypically distinct groups. Membership in the smallest group was heritable (38%, p < 1 × 10^-6) and had characteristics consistent with atherogenic dyslipidemia. We found both qualitative and quantitative LOD scores above 3 on chromosomes 11 and 14 (11q13, 14q23, 14q31). There were two Kong &; Cox LOD scores above 1.0 on chromosome 6 (6p21) and chromosome 11 (11q23).

Conclusion

This approach may be useful for the identification of genetic heterogeneity in complex phenotypes by clarifying the phenotype definition prior to linkage analysis. Some of our findings are in regions linked to elements of atherogenic dyslipidemia and related diagnoses, some may be novel, or may be false positives.

     

SNP-VISTA: An interactive SNP visualization tool

Background  

Recent advances in sequencing technologies promise to provide a better understanding of the genetics of human disease as well as the evolution of microbial populations. Single Nucleotide Polymorphisms (SNPs) are established genetic markers that aid in the identification of loci affecting quantitative traits and/or disease in a wide variety of eukaryotic species. With today's technological capabilities, it has become possible to re-sequence a large set of appropriate candidate genes in individuals with a given disease in an attempt to identify causative mutations. In addition, SNPs have been used extensively in efforts to study the evolution of microbial populations, and the recent application of random shotgun sequencing to environmental samples enables more extensive SNP analysis of co-occurring and co-evolving microbial populations. The program is available at [1].     

Sex dependent imprinting effects on complex traits in mice

Background  

Genomic imprinting is an epigenetic source of variation in quantitative traits that results from monoallelic gene expression, where commonly either only the paternally- or the maternally-derived allele is expressed. Imprinting has been shown to affect a diversity of complex traits in a variety of species. For several such quantitative traits sex-dependent genetic effects have been discovered, but whether imprinting effects also show such sex-dependence has yet to be explored. Moreover, theoretical work on the evolution of sex-dependent genomic imprinting effects makes specific predictions about the phenotypic patterns of such effects, which, however, have not been assessed empirically to date.     

QTL analysis of root traits as related to phosphorus efficiency in soybean

Background and Aims

Low phosphorus (P) availability is a major constraint to soybean growth and production, especially in tropical and subtropical areas. Root traits have been shown to play critical roles in P efficiency in crops. Identification of the quantitative trait loci (QTLs) conferring superior root systems could significantly enhance genetic improvement in soybean P efficiency.

Methods

A population of 106 F₉ recombinant inbred lines (RILs) derived from a cross between BD2 and BX10, which contrast in both P efficiency and root architecture, was used for mapping and QTL analysis. Twelve traits were examined in acid soils. A linkage map was constructed using 296 simple sequence repeat (SSR) markers with the Kosambi function, and the QTLs associated with these traits were detected by composite interval mapping and multiple-QTL mapping.

Key Results

The first soybean genetic map based on field data from parental genotypes contrasting both in P efficiency and root architecture was constructed. Thirty-one putative QTLs were detected on five linkage groups, with corresponding contribution ratios of 9·1–31·1 %. Thirteen putative QTLs were found for root traits, five for P content, five for biomass and five for yield traits. Three clusters of QTLs associated with the traits for root and P efficiency at low P were located on the B1 linkage group close to SSR markers Satt519 and Satt519-Sat_128, and on the D2 group close to Satt458; and one cluster was on the B1 linkage group close to Satt519 at high P.

Conclusions

Most root traits in soybean were conditioned by more than two minor QTLs. The region closer to Satt519 on the B1 linkage group might have great potential for future genetic improvement for soybean P efficiency through root selection.