From genetical genomics to systems genetics: potential applications in quantitative genomics and animal breeding

This article reviews methods of integration of transcriptomics (and equally proteomics and metabolomics), genetics, and genomics in the form of systems genetics into existing genome analyses and their potential use in animal breeding and quantitative genomic modeling of complex traits. Genetical genomics or the expression quantitative trait loci (eQTL) mapping method and key findings in this research are reviewed. Various procedures and potential uses of eQTL mapping, global linkage clustering, and systems genetics are illustrated using actual analysis on recombinant inbred lines of mice with data on gene expression (for diabetes- and obesity-related genes), pathway, and single nucleotide polymorphism (SNP) linkage maps. Experimental and bioinformatics difficulties and possible solutions are discussed. The main uses of this systems genetics approach in quantitative genomics were shown to be in refinement of the identified QTL, candidate gene and SNP discovery, understanding gene-environment and gene-gene interactions, detection of candidate regulator genes/eQTL, discriminating multiple QTL/eQTL, and detection of pleiotropic QTL/eQTL, in addition to its use in reconstructing regulatory networks. The potential uses in animal breeding are direct selection on heritable gene expression measures, termed "expression assisted selection,” and genetical genomic selection of both QTL and eQTL based on breeding values of the respective genes, termed "expression-assisted evaluation.

Genetical Genomics Reveals Large Scale Genotype-By-Environment Interactions in Arabidopsis thaliana

One of the major goals of quantitative genetics is to unravel the complex interactions between molecular genetic factors and the environment. The effects of these genotype-by-environment interactions also affect and cause variation in gene expression. The regulatory loci responsible for this variation can be found by genetical genomics that involves the mapping of quantitative trait loci (QTLs) for gene expression traits also called expression-QTL (eQTLs). Most genetical genomics experiments published so far, are performed in a single environment and hence do not allow investigation of the role of genotype-by-environment interactions. Furthermore, most studies have been done in a steady state environment leading to acclimated expression patterns. However a response to the environment or change therein can be highly plastic and possibly lead to more and larger differences between genotypes. Here we present a genetical genomics study on 120 Arabidopsis thaliana, Landsberg erecta × Cape Verde Islands, recombinant inbred lines (RILs) in active response to the environment by treating them with 3 h of shade. The results of this experiment are compared to a previous study on seedlings of the same RILs from a steady state environment. The combination of two highly different conditions but exactly the same RILs with a fixed genetic variation showed the large role of genotype-by-environment interactions on gene expression levels. We found environment-dependent hotspots of transcript regulation. The major hotspot was confirmed by the expression profile of a near isogenic line. Our combined analysis leads us to propose CSN5A, a COP9 signalosome component, as a candidate regulator for the gene expression response to shade

Functional constraints on the constitutive androstane receptor inferred from human sequence variation and cross-species comparisons

<p>Abstract</p> <p>Members of the NR1I subfamily of nuclear receptors play a role in the transcriptional activation of genes involved in drug metabolism and transport. NR1I3, the constitutive androstane receptor (CAR), mediates the induction of several genes involved in drug response, including members of the <it>CYP3A</it>, <it>CYP2B </it>and <it>UGT1A </it>subfamilies. Large inter-individual variation in drug clearance has been reported for many drug metabolising enzyme genes. Sequence variation at the <it>CAR </it>locus could potentially contribute to variation in downstream targets, as well as to the substantial variation in expression level reported. We used a comparative genomics-based approach to select resequencing segments in 70 subjects from three populations. We identified 21 polymorphic sites, one of which results in an amino acid substitution. Our study reveals a common haplotype shared by all three populations which is remarkably similar to the ancestral sequence, confirming that CAR is under strong functional constraints. The level and pattern of sequence variation is approximately similar across populations, suggesting that interethnic differences in drug metabolism are not likely to be due to genetic variation at the <it>CAR </it>locus. We also identify several common non-coding variants that occur at highly conserved sites across four major branches of the mammalian phylogeny, suggesting that they may affect <it>CAR </it>expression and, ultimately, the activity of its downstream targets.</p

Linkage mapping of putative regulator genes of barley grain development characterized by expression profiling

<p>Abstract</p> <p>Background</p> <p>Barley (<it>Hordeum vulgare </it>L.) seed development is a highly regulated process with fine-tuned interaction of various tissues controlling distinct physiological events during prestorage, storage and dessication phase. As potential regulators involved within this process we studied 172 transcription factors and 204 kinases for their expression behaviour and anchored a subset of them to the barley linkage map to promote marker-assisted studies on barley grains.</p> <p>Results</p> <p>By a hierachical clustering of the expression profiles of 376 potential regulatory genes expressed in 37 different tissues, we found 50 regulators preferentially expressed in one of the three grain tissue fractions pericarp, endosperm and embryo during seed development. In addition, 27 regulators found to be expressed during both seed development and germination and 32 additional regulators are characteristically expressed in multiple tissues undergoing cell differentiation events during barley plant ontogeny. Another 96 regulators were, beside in the developing seed, ubiquitously expressed among all tissues of germinating seedlings as well as in reproductive tissues. SNP-marker development for those regulators resulted in anchoring 61 markers on the genetic linkage map of barley and the chromosomal assignment of another 12 loci by using wheat-barley addition lines. The SNP frequency ranged from 0.5 to 1.0 SNP/kb in the parents of the various mapping populations and was 2.3 SNP/kb over all eight lines tested. Exploration of macrosynteny to rice revealed that the chromosomal orders of the mapped putative regulatory factors were predominantly conserved during evolution.</p> <p>Conclusion</p> <p>We identified expression patterns of major transcription factors and signaling related genes expressed during barley ontogeny and further assigned possible functions based on likely orthologs functionally well characterized in model plant species. The combined linkage map and reference expression map of regulators defined in the present study offers the possibility of further directed research of the functional role of regulators during seed development in barley.</p

A cross-species transcriptomics approach to identify genes involved in leaf development

<p>Abstract</p> <p>Background</p> <p>We have made use of publicly available gene expression data to identify transcription factors and transcriptional modules (regulons) associated with leaf development in <it>Populus</it>. Different tissue types were compared to identify genes informative in the discrimination of leaf and non-leaf tissues. Transcriptional modules within this set of genes were identified in a much wider set of microarray data collected from leaves in a number of developmental, biotic, abiotic and transgenic experiments.</p> <p>Results</p> <p>Transcription factors that were over represented in leaf EST libraries and that were useful for discriminating leaves from other tissues were identified, revealing that the C2C2-YABBY, CCAAT-HAP3 and 5, MYB, and ZF-HD families are particularly important in leaves. The expression of transcriptional modules and transcription factors was examined across a number of experiments to select those that were particularly active during the early stages of leaf development. Two transcription factors were found to collocate to previously published Quantitative Trait Loci (QTL) for leaf length. We also found that miRNA family 396 may be important in the control of leaf development, with three members of the family collocating with clusters of leaf development QTL.</p> <p>Conclusion</p> <p>This work provides a set of candidate genes involved in the control and processes of leaf development. This resource can be used for a wide variety of purposes such as informing the selection of candidate genes for association mapping or for the selection of targets for reverse genetics studies to further understanding of the genetic control of leaf size and shape.</p

Bioinformatics tools for the genetic dissection of complex traits in chickens

This thesis explores the genetic characterization of the mechanisms underlying complex traits in chicken through the use and development of bioinformatics tools. The characterization of quantitative trait loci controlling complex traits has proven to be very challenging. This thesis comprises the study of experimental designs, annotation procedures and functional analyses. These represent some of the main ‘bottlenecks’ involved in the integration of QTLs with the biological interpretation of high-throughput technologies. The thesis begins with an investigation of the bioinformatics tools and procedures available for genome research, briefly reviewing microarray technology and commonly applied experimental designs. A targeted experimental design based on the concept of genetical genomics is then presented and applied in order to study a known functional QTL responsible for chicken body weight. This approach contrasts the gene expression levels of two alternative QTL genotypes, hence narrowing the QTL-phenotype gap, and, giving a direct quantification of the link between the genotypes and the genetic responses. Potential candidate genes responsible for the chicken body weight QTL are identified by using the location of the genes, their expression and biological significance. In order to deal with the multiple sources of information and exploit the data effectively, a systematic approach and a relational database were developed to improve the annotation of the probes of the ARK-Genomics G. gallus 13K v4.0 cDNA array utilized on the experiment. To follow up the investigation of the targeted genetical genomics study, a detailed functional analysis is performed on the dataset. The aim is to identify the downstream effects through the identification of functional variation found in pathways, and secondly to achieve a further characterization of potential candidate genes by using comparative genomics and sequence analyses. Finally the investigation of the body weight QTL syntenic regions and their reported QTLs are presented

Using Network Component Analysis to Dissect Regulatory Networks Mediated by Transcription Factors in Yeast

Understanding the relationship between genetic variation and gene expression is a central question in genetics. With the availability of data from high-throughput technologies such as ChIP-Chip, expression, and genotyping arrays, we can begin to not only identify associations but to understand how genetic variations perturb the underlying transcription regulatory networks to induce differential gene expression. In this study, we describe a simple model of transcription regulation where the expression of a gene is completely characterized by two properties: the concentrations and promoter affinities of active transcription factors. We devise a method that extends Network Component Analysis (NCA) to determine how genetic variations in the form of single nucleotide polymorphisms (SNPs) perturb these two properties. Applying our method to a segregating population of Saccharomyces cerevisiae, we found statistically significant examples of trans-acting SNPs located in regulatory hotspots that perturb transcription factor concentrations and affinities for target promoters to cause global differential expression and cis-acting genetic variations that perturb the promoter affinities of transcription factors on a single gene to cause local differential expression. Although many genetic variations linked to gene expressions have been identified, it is not clear how they perturb the underlying regulatory networks that govern gene expression. Our work begins to fill this void by showing that many genetic variations affect the concentrations of active transcription factors in a cell and their affinities for target promoters. Understanding the effects of these perturbations can help us to paint a more complete picture of the complex landscape of transcription regulation. The software package implementing the algorithms discussed in this work is available as a MATLAB package upon request

Exploiting natural and induced genetic variation to study hematopoiesis

PUZZLING WITH DNA Blood cell formation can be studied by making use of natural genetic variation across mouse strains. There are, for example, two mouse strains that do not only differ in fur color, but also in average life span and more specifically in the number of blood-forming stem cells in their bone marrow. The cause of these differences can be found in the DNA of these mice. This DNA differs slightly between the two mouse strains, making some genes in one strain just a bit more or less active compared to those same genes in the other strain. The aim of part I of this thesis was to study the influence of genetic variation on gene expression and how this might explain the specific characteristics of the mouse strains. One of the findings in this study was that the influence of genetic variation on gene expression is strongly cell-type-dependent. Additionally, blood cell formation can be studied by introducing genetic variation into the system. In part II of this thesis genetic variation was introduced into mouse blood-forming stem cells by letting random DNA sequences or “barcodes” integrate into the DNA of these cells. Thereby, these cells were provided with a unique and identifiable label that was heritable from mother- to daughter cell. In this manner the fate of blood-forming stem cells and their progeny could be tracked following transplantation in mice. This technique is very promising for monitoring blood cell formation in future clinical gene therapy studies in humans. PUZZELEN MET DNA Bloedvorming kan bestudeerd worden door gebruik te maken van natuurlijke genetische variatie tussen muizenstammen. Zo bestaan er bijvoorbeeld twee muizenstammen die niet alleen verschillen in vachtkleur, maar ook in gemiddelde levensduur en meer specifiek in het aantal bloedvormende stamcellen dat zich in hun beenmerg bevindt. De oorzaak van deze verschillen kan gevonden worden in het DNA van deze muizen. Dat DNA verschilt net iets tussen de twee muizenstammen, waardoor sommige genen in de ene stam actiever of juist minder actief zijn dan diezelfde genen in de andere stam. In deel I van dit proefschrift is onderzocht hoe genetische variatie de expressie van genen beïnvloedt en hoe dit de specifieke eigenschappen van de muizenstammen zou kunnen verklaren. Er is onder andere gevonden dat de invloed van genetische variatie op de expressie van genen sterk celtype-afhankelijk is. Daarnaast kan bloedvorming bestudeerd worden door genetische variatie te introduceren in het systeem. In deel II van dit proefschrift is genetische variatie in bloedvormende stamcellen van muizen geïntroduceerd door random DNA volgordes of “barcodes” te laten integreren in het DNA van deze cellen. Dit resulteert erin dat elke cel voorzien wordt van een uniek label dat overgegeven wordt van moeder- op dochtercel. De DNA volgorde van het label kan gelezen worden met behulp van een zogenaamde sequencing techniek. Op deze manier kan het lot van bloedvormende stamcellen en hun nakomelingen gevolgd worden na transplantatie in muizen. Deze techniek is zeer veelbelovend voor het monitoren van bloedvorming in toekomstige klinische gentherapie studies in de mens.

The fate of Arabidopsis thaliana homeologous CNSs and their motifs in the Paleohexaploid Brassica rapa.

Following polyploidy, duplicate genes are often deleted, and if they are not, then duplicate regulatory regions are sometimes lost. By what mechanism is this loss and what is the chance that such a loss removes function? To explore these questions, we followed individual Arabidopsis thaliana-A. thaliana conserved noncoding sequences (CNSs) into the Brassica ancestor, through a paleohexaploidy and into Brassica rapa. Thus, a single Brassicaceae CNS has six potential orthologous positions in B. rapa; a single Arabidopsis CNS has three potential homeologous positions. We reasoned that a CNS, if present on a singlet Brassica gene, would be unlikely to lose function compared with a more redundant CNS, and this is the case. Redundant CNSs go nondetectable often. Using this logic, each mechanism of CNS loss was assigned a metric of functionality. By definition, proved deletions do not function as sequence. Our results indicated that CNSs that go nondetectable by base substitution or large insertion are almost certainly still functional (redundancy does not matter much to their detectability frequency), whereas those lost by inferred deletion or indels are approximately 75% likely to be nonfunctional. Overall, an average nondetectable, once-redundant CNS more than 30 bp in length has a 72% chance of being nonfunctional, and that makes sense because 97% of them sort to a molecular mechanism with deletion in its description, but base substitutions do cause loss. Similarly, proved-functional G-boxes go undetectable by deletion 82% of the time. Fractionation mutagenesis is a procedure that uses polyploidy as a mutagenic agent to genetically alter RNA expression profiles, and then to construct testable hypotheses as to the function of the lost regulatory site. We show fractionation mutagenesis to be a deletion machine in the Brassica lineage