Genetical genomics: combining gene expression with marker genotypes in poultry

Modification of Keratin Integrations and the Associated Morphogenesis in Frizzling Chicken Feathers

The morphological and compositional complexities of keratinized components make feathers ingenious skin appendages adapted to diverse ecological needs. Frizzling feathers, characterized by their distinct curling phenotypes, offer a unique model to explore the intricate morphogenesis in developing a keratin-based bioarchitecture over a wide range of morphospace. Here, we investigated the heterogeneous allocation of α- and β-keratins in flight feather shafts of homozygous and heterozygous frizzle chickens by analyzing the medulla-cortex integrations using quantitative morphology characterizations across scales. Our results reveal the intriguing construction of the frizzling feather shaft through the modified medulla development, leading to a perturbed balance of the internal biomechanics and, therefore, introducing the inherent natural frizzling compared to those from wild-type chickens. We elucidate how the localized developmental suppression of the α-keratin in the medulla interferes with the growth of the hierarchical keratin organization by changing the internal stress in the frizzling feather shaft. This research not only offers insights into the morphogenetic origin of the inherent bending of frizzling feathers but also facilitates our in-depth understanding of the developmental strategies toward the diverse integuments adapted for ecological needs.

An expression QTL of closely linked candidate genes affects pH of meat in chickens

Genetical genomics has been suggested as a powerful approach to study the genotype-phenotype gap. However, the relatively low power of these experiments (usually related to the high cost) has hindered fulfillment of its promise, especially for loci (QTL) of moderate effects.One strategy with which to overcome the issue is to use a targeted approach. It has two clear advantages: (i) it reduces the problem to a simple comparison between different genotypic groups at the QTL and (ii) it is a good starting point from which to investigate downstream effects of the QTL. In this study, from 698 F2 birds used for QTL mapping, gene expression profiles of 24 birds with divergent homozygous QTL genotypes were investigated. The targeted QTL was on chromosome 1 and affected initial pH of breast muscle. The biological mechanisms controlling this trait can be similar to those affecting malignant hyperthermia or muscle fatigue in humans. The gene expression study identified 10 strong local signals that were markedly more significant compared to any genes on the rest of the genome. The differentially expressed genes all mapped to a region <1 Mb, suggesting a remarkable reduction of the QTL interval. These results, combined with analysis of downstream effect of the QTL using gene network analysis, suggest that the QTL is controlling pH by governing oxidative stress. The results were reproducible with use of as few as four microarrays on pooled samples (with lower significance level). The results demonstrate that this cost-effective approach is promising for characterization of QTL.

Microarray resources for genetic and genomic studies in chicken: a review

Advent of microarray technologies revolutionized the nature and scope of genetic and genomic research in human and other species by allowing massively parallel analysis of thousands of genomic sites. They have been used for diverse purposes such as for transcriptome analysis, CNV detection, SNP and CNV genotyping, studying DNA-protein interaction, and detection of genome methylation. Microarrays have also made invaluable contributions to research in chicken which is an important model organism for studying embryology, immunology, oncology, virology, evolution, genetics, and genomics and also for other avian species. Despite their huge contributions in life science research, the future of microarrays is now being questioned with the advent of massively parallel next generation sequencing (NGS) technologies, which promise to overcome some of the limitations of microarray platforms. In this article we review the various microarray resources developed for chicken and their past and potential future applications. We also discuss about the future of microarrays in the NGS era particularly in the context of livestock genetics. We argue that even though NGS promises some major advantages-in particular, offers the opportunity to discover novel elements in the genome-microarrays will continue to be major tools for research and practice in the field of livestock genetics/genomics due to their affordability, high throughput nature, mature established technologies and ease of application. Moreover, with advent of new microarray technologies like capture arrays, the NGS and microarrays are expected to complement each other in future research in life science.

The chicken frizzle feather is due to an α-keratin (KRT75) mutation that causes a defective rachis

Feathers have complex forms and are an excellent model to study the development and evolution of morphologies. Existing chicken feather mutants are especially useful for identifying genetic determinants of feather formation. This study focused on the gene F, underlying the frizzle feather trait that has a characteristic curled feather rachis and barbs in domestic chickens. Our developmental biology studies identified defects in feather medulla formation, and physical studies revealed that the frizzle feather curls in a stepwise manner. The frizzle gene is transmitted in an autosomal incomplete dominant mode. A whole-genome linkage scan of five pedigrees with 2678 SNPs revealed association of the frizzle locus with a keratin gene-enriched region within the linkage group E22C19W28_E50C23. Sequence analyses of the keratin gene cluster identified a 69 bp in-frame deletion in a conserved region of KRT75, an α-keratin gene. Retroviral-mediated expression of the mutated F cDNA in the wild-type rectrix qualitatively changed the bending of the rachis with some features of frizzle feathers including irregular kinks, severe bending near their distal ends, and substantially higher variations among samples in comparison to normal feathers. These results confirmed KRT75 as the F gene. This study demonstrates the potential of our approach for identifying genetic determinants of feather forms.

With the availability of a sequenced chicken genome, the reservoir of variant plumage genes found in domestic chickens can provide insight into the molecular mechanisms underlying the diversity of feather forms. In this paper, we identify the molecular basis of the distinctive frizzle (F) feather phenotype that is caused by a single autosomal incomplete dominant gene in which heterozygous individuals show less severe phenotypes than homozygous individuals. Feathers in frizzle chickens curve backward. We used computer-assisted analysis to establish that the rachis of the frizzle feather was irregularly kinked and more severely bent than normal. Moreover, microscopic evaluation of regenerating feathers found reduced proliferating cells that give rise to the frizzle rachis. Analysis of a pedigree of frizzle chickens showed that the phenotype is linked to two single-nucleotide polymorphisms in a cluster of keratin genes within the linkage group E22C19W28_E50C23. Sequencing of the gene cluster identified a 69-base pair in-frame deletion of the protein coding sequence of the α-keratin-75 gene. Forced expression of the mutated gene in normal chickens produced a twisted rachis. Although chicken feathers are primarily composed of beta-keratins, our findings indicate that alpha-keratins have an important role in establishing the structure of feathers.

Complex traits analysis of chicken growth using targeted genetical genomics

Dissecting the genetic control of complex trait variation remains very challenging, despite many advances in technology. The aim of this study was to use a major growth quantitative trait locus (QTL) in chickens mapped to chromosome 4 as a model for a targeted approach to dissect the QTL. We applied a variant of the genetical genomics approach to investigate genome-wide gene expression differences between two contrasting genotypes of a marked QTL. This targeted approach allows the direct quantification of the link between the genotypes and the genetic responses, thus narrowing the QTL-phenotype gap using fewer samples (i.e. microarrays) compared with the genome-wide genetical genomics studies. Four differentially expressed genes were localized under the region of the QTL. One of these genes is a potential positional candidate gene (AADAT) that affects lysine and tryptophan metabolism and has alternative splicing variants between the two genotypes. In addition, the lysine and glycolysis metabolism pathways were significantly enriched for differentially expressed genes across the genome. The targeted approach provided a complementary route to fine mapping of QTL by characterizing the local and the global downstream effects of the QTL and thus generating further hypotheses about the action of that QTL.

Genetic dissection of behavioral flexibility: reversal learning in mice

BACKGROUND

Behavioral inflexibility is a feature of schizophrenia, attention-deficit/hyperactivity disorder, and behavior addictions that likely results from heritable deficits in the inhibitory control over behavior. Here, we investigate the genetic basis of individual differences in flexibility, measured using an operant reversal learning task.

METHODS

We quantified discrimination acquisition and subsequent reversal learning in a cohort of 51 BXD strains of mice (2-5 mice/strain, n = 176) for which we have matched data on sequence, gene expression in key central nervous system regions, and neuroreceptor levels.

RESULTS

Strain variation in trials to criterion on acquisition and reversal was high, with moderate heritability (∼.3). Acquisition and reversal learning phenotypes did not covary at the strain level, suggesting that these traits are effectively under independent genetic control. Reversal performance did covary with dopamine D2 receptor levels in the ventral midbrain, consistent with a similar observed relationship between impulsivity and D2 receptors in humans. Reversal, but not acquisition, is linked to a locus on mouse chromosome 10 with a peak likelihood ratio statistic at 86.2 megabase (p < .05 genome-wide). Variance in messenger RNA levels of select transcripts expressed in neocortex, hippocampus, and striatum correlated with the reversal learning phenotype, including Syn3, Nt5dc3, and Hcfc2.

CONCLUSIONS

This work demonstrates the clear trait independence between, and genetic control of, discrimination acquisition and reversal and illustrates how globally coherent data sets for a single panel of highly related strains can be interrogated and integrated to uncover genetic sources and molecular and neuropharmacological candidates of complex behavioral traits relevant to human psychopathology.

Genome-wide linkage analysis of global gene expression in loin muscle tissue identifies candidate genes in pigs

BACKGROUND

Nearly 6,000 QTL have been reported for 588 different traits in pigs, more than in any other livestock species. However, this effort has translated into only a few confirmed causative variants. A powerful strategy for revealing candidate genes involves expression QTL (eQTL) mapping, where the mRNA abundance of a set of transcripts is used as the response variable for a QTL scan.

METHODOLOGY/PRINCIPAL FINDINGS

We utilized a whole genome expression microarray and an F(2) pig resource population to conduct a global eQTL analysis in loin muscle tissue, and compared results to previously inferred phenotypic QTL (pQTL) from the same experimental cross. We found 62 unique eQTL (FDR <10%) and identified 3 gene networks enriched with genes subject to genetic control involved in lipid metabolism, DNA replication, and cell cycle regulation. We observed strong evidence of local regulation (40 out of 59 eQTL with known genomic position) and compared these eQTL to pQTL to help identify potential candidate genes. Among the interesting associations, we found aldo-keto reductase 7A2 (AKR7A2) and thioredoxin domain containing 12 (TXNDC12) eQTL that are part of a network associated with lipid metabolism and in turn overlap with pQTL regions for marbling, % intramuscular fat (% fat) and loin muscle area on Sus scrofa (SSC) chromosome 6. Additionally, we report 13 genomic regions with overlapping eQTL and pQTL involving 14 local eQTL.

CONCLUSIONS/SIGNIFICANCE

Results of this analysis provide novel candidate genes for important complex pig phenotypes.

Functional genomics and genetical genomics approaches towards elucidating networks of genes affecting meat performance in pigs

The benefit of functional genomics is to identify key pathways and functional networks of genes and candidate genes underlying the genetic control of phenotypes. Genetical genomics, i.e. the integration of genetic analysis and expression phenotypes, has the potential to uncover regulatory networks controlling the coordinated expression of genes and to map variation on the level of DNA affecting the mRNA expression. Here we illustrate our own attempts to apply functional genomics and genetical genomics approaches in order to identify functional networks of genes relevant to traits related to meat performance. Expression data of 74 M longissimus dorsi samples obtained using Affymetrix GeneChips were correlated with drip loss and principal components (PCs) with high loadings of meat quality traits. Functional annotation analyses revealed that differences in water holding capacity, early pH decline and ultimate pH were related to the ubiquitin-proteasome system, mitochondrial metabolic pathways and muscle structural aspects. In particular, 1279 genes were correlated with drip loss (P <or= 0.001; q <or= 0.004). Negatively correlated transcripts were enriched in functional categories like extracellular matrix receptor interaction and Ca-signalling. Transcripts with a positive correlation represented oxidative phosphorylation, mitochondrial pathways and transporter activity. A linkage analysis revealed 897 expression QTL (eQTL) with 104 eQTL mapping in QTL regions for water holding capacity including 8 cis eQTL. The reduction of the multi-dimensional data sets of meat performance traits into lower dimensions of PC and the genetical genomics approach of eQTL analysis proved to be appropriate means to detect relevant biological pathways and to experimentally prioritize candidate genes.

Expression quantitative trait loci analysis of genes in porcine muscle by quantitative real-time RT-PCR compared to microarray data

Genetic analysis of transcriptional profiling is a promising approach for identifying biological pathways and dissecting the genetics of complex traits. Here, we report on expression quantitative trait loci (eQTL) that were estimated from the quantitative real-time RT-PCR data of 276 F(2) animals and compared with eQTL identified using 74 microarrays. In total, 13 genes were selected that showed trait-dependent expression in microarray experiments and exhibited 21 eQTL. Real-time RT-PCR and microarray data revealed seven cis eQTL in total, of which one was only detected by real-time RT-PCR, one was only detected by microarray analysis, three were consistently found in overlapping intervals and two were in neighbouring intervals on the same chromosome; whereas no trans eQTL was confirmed. We demonstrate that cis regulation is a stable characteristic of individual transcripts. Consequently, a global microarray eQTL analysis of a limited number of samples can be used for exploring functional and regulatory gene networks and scanning for cis eQTL, whereas the subsequent analysis of a subset of likely cis-regulated genes by real-time RT-PCR in a larger number of samples is relevant to narrow down a QTL region by targeting these positional candidate genes. In fact, when modelling SNPs of six genes as fixed effects in the eQTL analysis, eQTL peaks were shifted downwards, experimentally confirming the impact of the respective polymorphic genes, although these SNPs were not located in the regulatory sequence and these shifts occur as a result of linkage disequilibrium in the F(2) population.

Trait correlated expression combined with expression QTL analysis reveals biological pathways and candidate genes affecting water holding capacity of muscle

Background

Leakage of water and ions and soluble proteins from muscle cells occurs during prolonged exercise due to ischemia causing muscle damage. Also post mortem anoxia during conversion of muscle to meat is marked by loss of water and soluble components from the muscle cell. There is considerable variation in the water holding capacity of meat affecting economy of meat production. Water holding capacity depends on numerous genetic and environmental factors relevant to structural and biochemical muscle fibre properties a well as ante and post slaughter metabolic processes.

Results

Expression microarray analysis of M. longissimus dorsi RNAs of 74 F2 animals of a resource population showed 1,279 transcripts with trait correlated expression to water holding capacity. Negatively correlated transcripts were enriched in functional categories and pathways like extracellular matrix receptor interaction and calcium signalling. Transcripts with positive correlation dominantly represented biochemical processes including oxidative phosphorylation, mitochondrial pathways, as well as transporter activity. A linkage analysis of abundance of trait correlated transcripts revealed 897 expression QTL (eQTL) with 104 eQTL coinciding with QTL regions for water holding capacity; 96 transcripts had trans acting and 8 had cis acting regulation.

Conclusion

The complex relationships between biological processes taking place in live skeletal muscle and meat quality are driven on the one hand by the energy reserves and their utilisation in the muscle and on the other hand by the muscle structure itself and calcium signalling. Holistic expression profiling was integrated with QTL analysis for the trait of interest and for gene expression levels for creation of a priority list of genes out of the orchestra of genes of biological networks relevant to the liability to develop elevated drip loss.

Functional genomics of the chicken--a model organism

Since the sequencing of the genome and the development of high-throughput tools for the exploration of functional elements of the genome, the chicken has reached model organism status. Functional genomics focuses on understanding the function and regulation of genes and gene products on a global or genome-wide scale. Systems biology attempts to integrate functional information derived from multiple high-content data sets into a holistic view of all biological processes within a cell or organism. Generation of a large collection ( approximately 600K) of chicken expressed sequence tags, representing most tissues and developmental stages, has enabled the construction of high-density microarrays for transcriptional profiling. Comprehensive analysis of this large expressed sequence tag collection and a set of approximately 20K full-length cDNA sequences indicate that the transcriptome of the chicken represents approximately 20,000 genes. Furthermore, comparative analyses of these sequences have facilitated functional annotation of the genome and the creation of several bioinformatic resources for the chicken. Recently, about 20 papers have been published on transcriptional profiling with DNA microarrays in chicken tissues under various conditions. Proteomics is another powerful high-throughput tool currently used for examining the dynamics of protein expression in chicken tissues and fluids. Computational analyses of the chicken genome are providing new insight into the evolution of gene families in birds and other organisms. Abundant functional genomic resources now support large-scale analyses in the chicken and will facilitate identification of transcriptional mechanisms, gene networks, and metabolic or regulatory pathways that will ultimately determine the phenotype of the bird. New technologies such as marker-assisted selection, transgenics, and RNA interference offer the opportunity to modify the phenotype of the chicken to fit defined production goals. This review focuses on functional genomics in the chicken and provides a road map for large-scale exploration of the chicken genome.

Candidate gene identification approach: progress and challenges

Although it has been widely applied in identification of genes responsible for biomedically, economically, or even evolutionarily important complex and quantitative traits, traditional candidate gene approach is largely limited by its reliance on the priori knowledge about the physiological, biochemical or functional aspects of possible candidates. Such limitation results in a fatal information bottleneck, which has apparently become an obstacle for further applications of traditional candidate gene approach on many occasions. While the identification of candidate genes involved in genetic traits of specific interest remains a challenge, significant progress in this subject has been achieved in the last few years. Several strategies have been developed, or being developed, to break the barrier of information bottleneck. Recently, being a new developing method of candidate gene approach, digital candidate gene approach (DigiCGA) has emerged and been primarily applied to identify potential candidate genes in some studies. This review summarizes the progress, application software, online tools, and challenges related to this approach.