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The Wilhelmine E. Key 1987 invitational lecture. Genetic changes associated with the evolution of adaptedness in cultivated plants and their wild progenitors.

The results of long-term studies of changes in adaptedness in a number of experimental populations of annual plants are summarized. Measurements made of quantitative traits showed that cumulative increases in reproductive capacity continued in these experimental populations for more than 50 generations. Highly significant allelic frequency changes also occurred for marker loci governing morphological variants, disease resistance, allozymes, and rDNA restriction fragments. Individual effects of the marker loci on quantitative traits were determined by extensive progeny testing of selfed families descended from single plants isolated from various generations of the experimental populations. Comparisons between homozygotes and heterozygotes of marker loci for quantitative trait expression revealed that all the marker loci studied had statistically significant additive effects on several to many quantitative traits; thus, each Mendelian locus, in addition to being a locus for its discrete descriptive effect, was also a locus for several quantitative traits. Consistent associations were found between superior reproductive capacity (e.g., larger numbers of kernels per plant) and the alleles of marker loci that increased in frequency over generations; no other quantitative traits measured were clearly and consistently associated with alleles that increased in frequency. Multilocus analyses based on canonical correlation, log linear, and cluster analysis procedures showed that highly significant associations developed in early generations among alleles of different loci in all the predominantly selfing populations studied. Dynamic changes featuring amalgamations of alleles into fewer clusters involving larger numbers of loci continued into the late generations. Patterns of ecogenetic differentiation that developed under predominant selfing were found to be fine-scaled overlays of environmental heterogeneity. The picture of evolutionary change that emerges is one in which the incorporation of increasing numbers of favorably interacting alleles into large synergistic complexes was accompanied in inbreeding populations by increases in adaptedness to the local environment and also by striking ecogenetic differentiation among local populations that occupy unlike habitats, including differentiation between cultivated plants and their wild progenitors. Selfing appears to promote the development and maintenance of adaptedness within populations and at the same time to facilitate the development of spatial differentiation by retarding gene flow between populations.(ABSTRACT TRUNCATED AT 400 WORDS)

Adaptation, Physiological↗

PubMed1998

Identifying candidate genes for blood pressure quantitative trait loci using differential gene expression and a panel of congenic strains.

The most difficult step in dissecting the molecular basis of a quantitative trait is proceeding from chromosomal locations associated with this trait (i.e., quantitative trait locus, QTL) to determining what gene(s) in the QTL region is causative. Using standard positional cloning methodology to identify candidate genes for a particular QTL has three drawbacks: 1) it is labor intensive; 2) defining variants in genes causing quantitative variation from sequence information alone is difficult or impossible; and 3) many (or most) genes in a particular chromosomal interval will not be relevant for a specific disease/trait because they are not expressed in critical candidate organs. Instead of positional cloning, we propose using a panel of congenic strains, where each carries an allele for a different QTL on a similar genetic background, in conjunction with identification of differentially-expressed genes in target organs of inbred strains of contrasting phenotype. This will identify genes having altered expression in organs critical to regulating blood pressure and the development of hypertension. Radiation hybrid mapping of such genes will result in a transcription map of differentially-expressed genes in a target organ of a rat model of genetic hypertension. This approach could rapidly identify genes mapping to genomic regions near QTL, which will be strong candidates to explain, in part, the observed strain differences in blood pressure. This novel approach, which uses a panel of congenic strains to facilitate the mapping and subsequent identification of differentially-expressed and QTL-associated genes, should be applicable to any genetic model for identifying candidate genes located near QTL, given the availability of a panel of congenic strains.

Animals↗

PubMed2005

Weighting by heritability for detection of quantitative trait loci with microarray estimates of gene expression.

Heritable differences in transcribed RNA levels can be mapped as quantitative trait loci (QTLs). Transcribed RNA levels are often measured by hybridization to microarrays of oligonucleotide probes, in which each transcript is represented by multiple probes. The use of recombinant inbred lines allows an estimate of the heritability of expression measured by individual probes. This heritability varies greatly. We have tested heritability-weighted averages to define expression of a transcript and found that these allow detection of more QTLs than previously described methods.

Animals↗

PubMed2025

LungGENIE: the lung gene-expression and network imputation engine.

BACKGROUND: Few cohorts have study populations large enough to conduct molecular analysis of ex vivo lung tissue for genomic analyses. Transcriptome imputation is a non-invasive alternative with many potential applications. We present a novel transcriptome-imputation method called the Lung Gene Expression and Network Imputation Engine (LungGENIE) that uses principal components from blood gene-expression levels in a linear regression model to predict lung tissue-specific gene-expression. METHODS: We use paired blood and lung RNA sequencing data from the Genotype-Tissue Expression (GTEx) project to train LungGENIE models. We replicate model performance in a unique dataset, where we generated RNA sequencing data from paired lung and blood samples available through the SUNY Upstate Biorepository (SUBR). We further demonstrate proof-of-concept application of LungGENIE models in an independent blood RNA sequencing data from the Genetic Epidemiology of COPD (COPDGene) study. RESULTS: We show that LungGENIE prediction accuracies have higher correlation to measured lung tissue expression compared to existing cis-expression quantitative trait loci-based methods (median Pearson's r = 0.25, IQR 0.19-0.32), with close to half of the reliably predicted transcripts being replicated in the testing dataset. Finally, we demonstrate significant correlation of differential expression results in chronic obstructive pulmonary disease (COPD) from imputed lung tissue gene-expression and differential expression results experimentally determined from lung tissue. CONCLUSION: Our results demonstrate that LungGENIE provides complementary results to existing expression quantitative trait loci-based methods and outperforms direct blood to lung results across internal cross-validation, external replication, and proof-of-concept in an independent dataset. Taken together, we establish LungGENIE as a tool with many potential applications in the study of lung diseases.

Humans↗

PubMed2003

Quantitative trait loci that influence the expression of guarding and stinging behaviors of individual honey bees.

This study was conducted to test for the effect of three stinging behaviors QTLs (sting-1, sting-2 and sting-3) on the expression of guarding and stinging behavior of individual honey bees, and to determine if results of defensive behavior QTLs found in studies with Africanized honey bees could be extended to other populations of bees. Samples of guards, stingers, foragers and nurse bees were taken from two backcross colonies derived from a defensive colony and a gentle colony. The genotype of each bee for both types of colonies was determined for two sequence tagged site (STS) markers linked to sting-1 and for another two STSs, one linked to sting-2 and one linked to sting-3. Results showed that sting-1 had an effect on the expression of both stinging and guarding behaviors, sting-2 and sting-3 influenced the expression of guarding behavior. These results indicate that division of labor is influenced by specific QTLs. Results also show that QTLs mapped in a population of Africanized honey bees using colony level phenotypes also influenced the expression of guarding and stinging behavior of individual bees of other populations.

Aggression↗

PubMed2025

Saturating the eQTL map in Drosophila: Genome-wide patterns of cis and trans regulation of transcriptional variation in outbred populations.

Most genetic polymorphisms associated with complex traits are found in non-coding regions of the genome. Characterizing their effect presents a formidable challenge, and expression quantitative trait locus (eQTLs) mapping has been a key approach to do so. As comprehensive eQTL maps are available only for a few species, here we developed the Drosophila outbred synthetic population (Dros-OSP) and used it to characterize the landscape of transcriptional regulation in Drosophila melanogaster. We collected head and body transcriptomes and genomes from 1,286 outbred flies and mapped local and distant eQTLs for 98% of the genes. We characterized the network organization of the transcriptome across tissues and described the properties of local and distal eQTLs in terms of genetic diversity, heritability, connectivity, and pleiotropy. These results provide new insights into the genetic basis of transcriptional regulation in the fruit fly and offer a new mapping resource that will expand the possibilities currently available for the Drosophila community.

Animals↗

PubMed2000

Mapping of quantitative trait loci (QTL) of differential stress gene expression in rat recombinant inbred strains.

OBJECTIVE: Stress has been shown to be a major environmental contributor to cardiovascular diseases through its effects on blood pressure variability and cardiac function. The cellular stress response is characterized by the expression of specific heat stress genes (hsps), under the transcriptional control of heat shock transcription factors (HSTFs). The levels of hsp mRNA depend on the severity of the stress, with hstf1 acting as a stress sensor. The aim of this work was to evaluate the genetic contribution of the variability in hsp expression, and to identify its putative quantitative trait loci (QTL). METHODS: Twenty recombinant inbred rat strains (RIS) were studied. The animals underwent a standardized, identical 1 h immobilization stress in restraint cages, followed by 1 h of rest before sacrifice. Total RNA was extracted from the heart kidneys and adrenals, and the mRNA levels of hsp27, hsp70, hsp84, hsp86 and hsp105 were measured. The strain distribution pattern (SDP) of hsp expression was correlated with that of 475 polymorphic markers distributed throughout the RIS genome. A polymorphism of rat hstf1 in RIS was used for its mapping in RIS. RESULTS: Despite an identical stress being applied to all strains, hsp expression showed up to a 1 2-fold gradient with little intra-strain variability, indicative of a strong genetic contribution to the trait Heritability ranged from 50 to 77% for most hsp genes in the three target organs. The continuous SDP of stress gene expression indicated the polygenic nature of the trait A common locus on chromosome 7 (at D7Cebrp187s3 marker) was consistently associated with all hsp expression in most of the organs [with a likelihood of odds (LOD) score of 3.0 for hsp27 expression]. We have mapped rat hstf1 on chromosome 7 at the same locus. Finally, the D4Mit19 marker was significantly associated with hsp84 expression in the heart (LOD score of 3.1). CONCLUSION: Two loci were linked with the differential expression of HSPs in response to immobilization stress in target organs of RIS. The chromosome 7 locus unveiled for all HSPs could explain up to 42% of the observed inter-strain variability of hsp levels in response to stress. We propose hstf1 as a positional candidate at this locus.

Adrenal Glands↗

PubMed2006

A statistical framework for genome-wide scanning and testing of imprinted quantitative trait loci.

Non-equivalent expression of alleles at a locus results in genomic imprinting. In this article, a statistical framework for genome-wide scanning and testing of imprinted quantitative trait loci (iQTL) underlying complex traits is developed based on experimental crosses of inbred line species in backcross populations. The joint likelihood function is composed of four component likelihood functions with each of them derived from one of four backcross families. The proposed approach models genomic imprinting effect as a probability measure with which one can test the degree of imprinting. Simulation results show that the model is robust for identifying iQTL with various degree of imprinting ranging from no imprinting, partial imprinting to complete imprinting. Under various simulation scenarios, the proposed model shows consistent parameter estimation with reasonable precision and high power in testing iQTL. When a QTL shows Mendelian effect, the proposed model also outperforms traditional Mendelian model. Extension to incorporate maternal effect is also given. The developed model, built within the maximum likelihood framework and implemented with the EM algorithm, provides a quantitative framework for testing and estimating iQTL involved in the genetic control of complex traits.

Algorithms↗

PubMed1997

Assessment of locomotor activity, acoustic and tactile startle, and prepulse inhibition of startle in inbred mouse strains and F1 hybrids: implications of genetic background for single gene and quantitative trait loci analyses.

As the use of transgenic and null mutation techniques in the development of animal models of disorders increases, the importance of selecting the appropriate genetic background also increases. The genetic background of the mouse strains used as models for various disorders is critical because of the potential for epistatic effects on the expression of transgenes and null mutations. Twelve strains of inbred mice and seven F1 hybrids were tested in multiple behavioural tasks including open-field locomotor activity, Y-maze activity, auditory and tactile startle and prepulse inhibition of startle response. Differences across genotypes were found for all variables measured. The range of variability among genotypes was dependent on the specific measure so careful consideration must be made in selecting a strain for testing a particular behaviour. Because of the polygenic nature of each of the behavioural phenotypes, the impact of a single gene manipulation may vary depending on the genetic background on which it is expressed. Moreover, quantitative trait loci methods could be applied to these behaviours.

Acoustic Stimulation↗

PubMed2026

Role of IFIT1 and IFIT3 in systemic lupus erythematosus: modeling a diagnosis and exploring immune regulation.

Systemic lupus erythematosus (SLE) is a complex autoimmune disorder characterized by multi-organ involvement and a protracted clinical course. Current diagnostic strategies, which rely heavily on clinical symptoms and serology, are often insufficient for early detection. Therefore, highly accurate diagnostic biomarkers are urgently needed to facilitate early intervention and optimize personalized treatment strategies. D atasets GSE61635 and GSE135779 were integrated to identify differentially expressed genes. Weighted gene co-expression network analysis (WGCNA) was performed to isolate the module with the strongest clinical relevance. Mendelian randomization and single‑cell RNA‑seq were used to identify key disease‑relevant genes. A diagnostic model was then constructed, and gene set variation analysis (GSVA), along with gene set enrichment analysis (GSEA), was conducted to elucidate the underlying molecular pathways. IFIT1 and IFIT3 were identified as 2 core genes highly expressed in monocytes and T cells of SLE patients. Functional enrichment analysis revealed that these genes were enriched in immune-related pathways, metabolic pathways related to inflammation and genomic stability. The diagnostic model showed good accuracy, with an area under the curve (AUC) of 0.974 on the training set and 0.912 on the validation set. IFIT1 and IFIT3 represent promising biomarkers for diagnosing SLE and appear to mediate key immune and metabolic disturbances. Furthermore, the developed model serves as an accurate and reliable instrument for early diagnosis and personalized therapy. Large-scale clinical studies are warranted to further validate these findings and evaluate their clinical application.

Humans↗

PubMed2026

Mitochondria-Related Pathogenic Genes in Paediatric Asthma: A Multi-Omics Mendelian Randomization Study.

Mitochondrial dysfunction is implicated in asthma pathogenesis, but causal roles of mitochondrial-related genes in paediatric asthma remain unclear. We performed a multi-omics Mendelian randomization study integrating GWAS data from paediatric asthma cohorts with blood-based methylation quantitative trait loci (mQTLs), expression QTLs (eQTLs) and protein QTLs (pQTLs) datasets. Causal inference was assessed using Summary-data-based Mendelian Randomization (SMR) and HEIDI testing, complemented by colocalization analysis. Findings were validated in independent cohorts and evaluated for tissue specificity using GTEx. Functional enrichment and protein-protein interaction (PPI) network analyses were conducted. SMR analysis identified 80 methylation sites spanning 54 genes, 26 gene expressions, and three proteins significantly associated with paediatric asthma. Colocalization analysis confirmed strong evidence for 10 methylation sites (7 genes), the STX17 eQTL (PP.H4 = 0.98) and the UNG pQTL (PP.H4 = 0.84). Tissue-specific eQTL validation replicated the STX17 association. Multi-omics integration associated ALAS1 (cg13241645, cg15698299) and TXNRD1 (cg09884423) with asthma at both methylation and expression levels, with colocalization supporting both ALAS1 associations. Furthermore, integrated mQTL-eQTL analysis suggests that DNA methylation potentially regulates ALAS1 and TXNRD1 expression. Functional enrichment and network analyses revealed that these candidate genes converge on mitochondrial metabolic pathways and identified seven hub genes with potential regulatory significance (SDHB, MFN2, GLDC, PHB2, TXNRD1, ATP5MC1 and PHB). This study provides multi-omics evidence supporting a causal role for mitochondrial-related genes, particularly ALAS1 and TXNRD1, in paediatric asthma, offering new insights into pathogenesis and potential therapeutic targets.

Humans↗

PubMed2026

CHCHD10 Mitigates Alzheimer's Disease-Related Phenotypes in Association With Epigenetic Remodeling in Directly Reprogrammed Neurons.

Mitochondrial dysfunction and chromatin dysregulation are interconnected contributors to neuronal vulnerability in Alzheimer's disease (AD), yet the molecular mechanisms linking these processes remain poorly understood. CHCHD10, a mitochondrial intermembrane space protein, has been implicated in neurodegenerative disorders, but its role in AD has not been defined. Here, we identify CHCHD10 as a previously unrecognized modulator of neuronal epigenomic stability in AD. Using direct fibroblast-to-neuron reprogramming, which preserves patient-specific epigenetic signatures, we show that AD neurons recapitulate genome-wide hypomethylation patterns observed in postmortem AD cortex. CHCHD10 expression is significantly reduced in AD neurons and across multiple human brain datasets, including single-cell and bulk RNA sequencing, proteomics, and human cortical tissue analyses. Restoration of CHCHD10 in AD neurons reduces amyloid-β and insoluble tau accumulation while reversing AD-associated differentially methylated regions across CpG islands, promoters, and regulatory elements. CHCHD10-responsive methylation changes overlap with those observed in human AD brain regions and colocalize with significant AD loci and cortex-specific eQTL loci, including MAPT and ABCA7. Finally, we identify KATNAL2 as a CHCHD10-responsive effector whose loss enhances tau phosphorylation and seeding, whereas its restoration mitigates tau pathology. Together, these findings support a CHCHD10-associated neuroprotective pathway linking mitochondrial dysfunction, epigenomic instability, and tau pathology in AD.

Humans↗

PubMed2025

Dynamic neuro-immune regulation of psychiatric risk loci in human neurons.

The prenatal environment influences neurodevelopment and subsequent clinical trajectories for psychiatric outcomes in childhood and adolescence. Yet it remains unclear if the impact of maternal and fetal immune activation varies with distinct polygenic risk profiles. Therefore, here we catalogue genotype and environment (GxE) interactions, contrasting allele-specific regulatory activity between inflammatory contexts. We report a cue-specific neuronal massively parallel reporter assay (MPRA) of 220 loci from genome-wide association study (GWAS) linked to ten brain traits/disorders, empirically dissecting the impact of interleukin-6 (IL-6) and interferon-alpha (IFNα) on transcriptional activity. Of 1,469 active candidate regulatory risk elements (MPRA-active CRSs) across three conditions, we identify 316 with dynamic variant-specific effects (MPRA-QTLs) in human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons. Broadly, across hundreds of variants, neuronal immune-mediated regulatory activity is driven by differences in transcription factor binding and chromatin accessibility, the gene targets of which show pleiotropic enrichments for brain, metabolic, and immune disorders. Dynamic genetic regulation mediates immune effects, informing our understanding of mechanisms governing pleiotropy and variable penetrance. Understanding neurodevelopmental GxE interactions will inform mental health trajectories and resolve mechanisms mediating prenatal risk.

dynamic expression quantitative trait loci↗

PubMed2025

How to analyze and understand the human immune system.

To enhance our understanding of the pathogenesis of diseases, including rheumatic diseases, and to improve disease control, it is essential to attain a thorough understanding of the human immune system, alongside mouse immunology. Historically, the investigation of the human immune system has posed significant challenges due to methodological limitations. Nonetheless, recent advancements in genomic studies of multifactorial diseases have elucidated that numerous risk-associated genetic variants affecting quantitative differences in cell-specific gene expression. In light of these findings, we are currently examining individual genetic variations in both healthy individuals and patients, as well as categorizing cells into distinct subsets in order to construct a comprehensive dataset concerning the human immune system. This is accomplished by combining data on gene expression, factors influencing the expression mechanisms, protein expression, metabolomics, and environmental variables pertinent to immune functionality-such as gut microbiota. These datasets will facilitate the comprehensive characterization of the human immune system. Using these datasets and through the integrative analyses of data related to risk genetic variations and gene expression profiles of each disease and individual, we anticipate uncovering novel insights into the human immune system, the heterogeneity of diseases, immune function mechanisms, and their regulatory strategies that may not be achievable through murine models.

Humans↗

PubMed2026

Retinal Transcriptome-Wide Association Study Identifies Novel Alzheimer's Disease Risk Genes.

INTRODUCTION: Alzheimer's disease (AD) is the leading cause of dementia worldwide. The retina shares molecular pathways with the brain, yet no study has systematically linked retinal gene expression to AD risk. METHODS: We performed transcriptome-wide association studies (TWAS) using two independent retinal eQTL panels (Strunz et al., n = 311; EyeGEx, n = 406) and a large meta-analyzed AD genome-wide association study (GWAS) (Bellenguez et al., 111,326 cases, 677,663 controls). Genes were further validated with GWAS in the independent Alzheimer's Disease Sequencing Project (ADSP) using a matched eQTL-panel strategy. RESULTS: We identified 62 AD-associated genes across the two eQTL panels using Bellenguez et al. as the discovery cohort. Of these, 31 were replicated in the ADSP cohort. The findings highlight shared complement-mediated immune dysregulation (CD55, CD46, TREM2) and provide functional transcriptomic evidence to prioritize novel causal drivers of AD pathogenesis, including STYX and the LRRC37 gene family. DISCUSSION: Retinal data capture core AD genetic architecture and reveal novel risk genes, highlighting the retina as a molecularly informative tissue for dementia research.

Alzheimer’s disease↗

PubMed2026

Mapping the causal chain from genetic risk variants to lipid dysmetabolism in Parkinson's disease.

The molecular pathways linking genetic variants to Parkinson's disease (PD) onset and progression remain incompletely defined; however, risk alleles in multiple genes, including GBA1, strongly implicate lipid metabolism. To systematically identify causal biomarker signatures, we analysed comprehensive metabolome profiles from blood plasma in 149 PD patients and 150 controls, along with complementary genetic, RNA-sequencing and metabolic data from other available clinical and pathologic cohorts. Using colocalization and summary-data-based Mendelian randomization, we tested whether expression and metabolic quantitative trait loci mediate the association between implicated genetic variants and PD risk. We further integrated differential metabolomics and proteomics from blood and brain to reveal pertinent mechanisms. We show that common PD risk variants at the serine palmitoyltransferase small subunit B (SPTSSB) locus, a key regulator of de novo sphingolipid biosynthesis, are associated with increased SPTSSB brain expression and elevated plasma ceramides. Additional analyses strongly support our hypothesis that a common SPTSSB causal variant is responsible for PD risk as well as the expression and metabolic quantitative trait loci. Multiple sphingolipids and fatty acid derivatives were perturbed in PD, and we identified both unique and shared features with the Alzheimer's disease metabolome. A PD acylcarnitine signature was further replicated in human post-mortem brain tissue, when comparing those with or without preclinical Lewy body pathology. Integrated analysis of complementary brain proteomic profiles revealed dysregulation of mitochondrial processes dependent on acylcarnitines, including fatty acid beta-oxidation, the tricarboxylic acid cycle and oxidative phosphorylation. Our results identify promising biomarkers and reveal a causal chain linking genetic variation to altered gene/protein expression, lipid dysmetabolism, and the manifestation of PD.

Humans↗

PubMed2003

Use of a panel of congenic strains to evaluate differentially expressed genes as candidate genes for blood pressure quantitative trait loci.

Candidate gene(s) for multiple blood pressure (BP) quantitative trait loci (QTL) were sought by analysis of differential gene expression patterns in the kidneys of a panel of eight congenic strains, each of which carries a different low-BP QTL allele with a genetic composition that is otherwise similar to that of the hypertensive Dahl salt-sensitive (S) rat strain. First, genes differentially expressed in the kidneys of one-month-old Dahl S and salt-resistant (R) rats were identified. Then, Northern filter hybridization was used to examine the expression patterns of these genes in a panel of congenic strains. Finally, their chromosomal location was determined by radiation hybrid (RH) mapping. Seven out of 37 differentially expressed genes were mapped to congenic regions carrying BP QTLs, but only one of these genes, L-2 hydroxy acid oxidase (Hao2), showed the congenic strain-specific pattern of differential kidney gene expression predicted by its chromosomal location. This data suggests that Hao2 should be examined as a candidate gene for the rat chromosome 2 (RNO2) BP QTL.

Alcohol Oxidoreductases↗

PubMed2006

Functional classification, genomic organization, putatively cis-acting regulatory elements, and relationship to quantitative trait loci, of sorghum genes with rhizome-enriched expression.

Rhizomes are organs of fundamental importance to plant competitiveness and invasiveness. We have identified genes expressed at substantially higher levels in rhizomes than other plant parts, and explored their functional categorization, genomic organization, regulatory motifs, and association with quantitative trait loci (QTLs) conferring rhizomatousness. The finding that genes with rhizome-enriched expression are distributed across a wide range of functional categories suggests some degree of specialization of individual members of many gene families in rhizomatous plants. A disproportionate share of genes with rhizome-enriched expression was implicated in secondary and hormone metabolism, and abiotic stimuli and development. A high frequency of unknown-function genes reflects our still limited knowledge of this plant organ. A putative oligosaccharyl transferase showed the highest degree of rhizome-specific expression, with several transcriptional or regulatory protein complex factors also showing high (but lesser) degrees of specificity. Inferred by the upstream sequences of their putative rice (Oryza sativa) homologs, sorghum (Sorghum bicolor) genes that were relatively highly expressed in rhizome tip tissues were enriched for cis-element motifs, including the pyrimidine box, TATCCA box, and CAREs box, implicating the gibberellins in regulation of many rhizome-specific genes. From cDNA clones showing rhizome-enriched expression, expressed sequence tags forming 455 contigs were plotted on the rice genome and aligned to QTL likelihood intervals for ratooning and rhizomatous traits in rice and sorghum. Highly expressed rhizome genes were somewhat enriched in QTL likelihood intervals for rhizomatousness or ratooning, with specific candidates including some of the most rhizome-specific genes. Some rhizomatousness and ratooning QTLs were shown to be potentially related to one another as a result of ancient duplication, suggesting long-term functional conservation of the underlying genes. Insight into genes and pathways that influence rhizome growth set the stage for genetic and/or exogenous manipulation of rhizomatousness, and for further dissection of the molecular evolution of rhizomatousness.

Chromosome Mapping↗