Quantitative genomics: analyzing intraspecific variation using global gene expression polymorphisms or eQTLs

A systems genomics and genetics approach to identify the genetic regulatory network for lignin content in Brassica napus seeds

Seed quality traits of oilseed rape, Brassica napus (B. napus), exhibit quantitative inheritance determined by its genetic makeup and the environment via the mediation of a complex genetic architecture of hundreds to thousands of genes. Thus, instead of single gene analysis, network-based systems genomics and genetics approaches that combine genotype, phenotype, and molecular phenotypes offer a promising alternative to uncover this complex genetic architecture. In the current study, systems genetics approaches were used to explore the genetic regulation of lignin traits in B. napus seeds. Four QTL (qLignin_A09_1, qLignin_A09_2, qLignin_A09_3, and qLignin_C08) distributed on two chromosomes were identified for lignin content. The qLignin_A09_2 and qLignin_C08 loci were homologous QTL from the A and C subgenomes, respectively. Genome-wide gene regulatory network analysis identified eighty-three subnetworks (or modules); and three modules with 910 genes in total, were associated with lignin content, which was confirmed by network QTL analysis. eQTL (expression quantitative trait loci) analysis revealed four cis-eQTL genes including lignin and flavonoid pathway genes, cinnamoyl-CoA-reductase (CCR1), and TRANSPARENT TESTA genes TT4, TT6, TT8, as causal genes. The findings validated the power of systems genetics to identify causal regulatory networks and genes underlying complex traits. Moreover, this information may enable the research community to explore new breeding strategies, such as network selection or gene engineering, to rewire networks to develop climate resilience crops with better seed quality.

Systems genomics of salinity stress response in rice

Populations can adapt to stressful environments through changes in gene expression. However, the role of gene regulation in mediating stress response and adaptation remains largely unexplored. Here, we use an integrative field dataset obtained from 780 plants of Oryza sativa ssp. indica (rice) grown in a field experiment under normal or moderate salt stress conditions to examine selection and evolution of gene expression variation under salinity stress conditions. We find that salinity stress induces increased selective pressure on gene expression. Further, we show that trans-eQTLs rather than cis-eQTLs are primarily associated with rice's gene expression under salinity stress, potentially via a few master-regulators. Importantly, and contrary to the expectations, we find that cis-trans reinforcement is more common than cis-trans compensation which may be reflective of rice diversification subsequent to domestication. We further identify genetic fixation as the likely mechanism underlying this compensation/reinforcement. Additionally, we show that cis- and trans-eQTLs are under different selection regimes, giving us insights into the evolutionary dynamics of gene expression variation. By examining genomic, transcriptomic, and phenotypic variation across a rice population, we gain insights into the molecular and genetic landscape underlying adaptive salinity stress responses, which is relevant for other crops and other stresses.

Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach

Expression of quantitative disease resistance in many host-pathogen systems is controlled by genes at multiple loci, each contributing a small effect to the overall response. We used a systems genomics approach to study the molecular underpinnings of quantitative disease resistance in the soybean-Phytophthora sojae pathosystem, incorporating expression quantitative trait loci (eQTL) mapping and gene co-expression network analysis to identify the genes putatively regulating transcriptional changes in response to inoculation. These findings were compared to previously mapped phenotypic (phQTL) to identify the molecular mechanisms contributing to the expression of this resistance. A subset of 93 recombinant inbred lines (RILs) from a Conrad × Sloan population were inoculated with P. sojae isolate 1.S.1.1 using the tray-test method; RNA was extracted, sequenced, and the normalized read counts were genetically mapped from tissue collected at the inoculation site 24 h after inoculation from both mock and inoculated samples. In total, more than 100,000 eQTLs were mapped. There was a switch from predominantly cis-eQTLs in the mock treatment to an almost entirely nonoverlapping set of predominantly trans-eQTLs in the inoculated treatment, where greater than 100-fold more eQTLs were mapped relative to mock, indicating vast transcriptional reprogramming due to P. sojae infection occurred. The eQTLs were organized into 36 hotspots, with the four largest hotspots from the inoculated treatment corresponding to more than 70% of the eQTLs, each enriched for genes within plant-pathogen interaction pathways. Genetic regulation of trans-eQTLs in response to the pathogen was predicted to occur through transcription factors and signaling molecules involved in plant-pathogen interactions, plant hormone signal transduction, and MAPK pathways. Network analysis identified three co-expression modules that were correlated with susceptibility to P. sojae and associated with three eQTL hotspots. Among the eQTLs co-localized with phQTLs, two cis-eQTLs with putative functions in the regulation of root architecture or jasmonic acid, as well as the putative master regulators of an eQTL hotspot nearby a phQTL, represent candidates potentially underpinning the molecular control of these phQTLs for resistance.

From Classical to Modern Computational Approaches to Identify Key Genetic Regulatory Components in Plant Biology

The selection of plant genotypes with improved productivity and tolerance to environmental constraints has always been a major concern in plant breeding. Classical approaches based on the generation of variability and selection of better phenotypes from large variant collections have improved their efficacy and processivity due to the implementation of molecular biology techniques, particularly genomics, Next Generation Sequencing and other omics such as proteomics and metabolomics. In this regard, the identification of interesting variants before they develop the phenotype trait of interest with molecular markers has advanced the breeding process of new varieties. Moreover, the correlation of phenotype or biochemical traits with gene expression or protein abundance has boosted the identification of potential new regulators of the traits of interest, using a relatively low number of variants. These important breakthrough technologies, built on top of classical approaches, will be improved in the future by including the spatial variable, allowing the identification of gene(s) involved in key processes at the tissue and cell levels.

eQTLs play critical roles in regulating gene expression and identifying key regulators in rice

The regulation of gene expression plays an essential role in both the phenotype and adaptation of plants. Transcriptome sequencing enables simultaneous identification of exonic variants and quantification of gene expression. Here, we sequenced the leaf transcriptomes of 287 rice accessions from around the world and obtained a total of 177 853 high-quality single nucleotide polymorphisms after filtering. Genome-wide association study identified 44 354 expression quantitative trait loci (eQTLs), which regulate the expression of 13 201 genes, as well as 17 local eQTL hotspots and 96 distant eQTL hotspots. Furthermore, a transcriptome-wide association study screened 21 candidate genes for starch content in the flag leaves at the heading stage. HS002 was identified as a significant distant eQTL hotspot with five downstream genes enriched for diterpene antitoxin synthesis. Co-expression analysis, eQTL analysis, and linkage mapping together demonstrated that bHLH026 acts as a key regulator to activate the expression of downstream genes. The transgenic assay revealed that bHLH026 is an important regulator of diterpenoid antitoxin synthesis and enhances the disease resistance of rice. These findings improve our knowledge of the regulatory mechanisms of gene expression variation and complex regulatory networks of the rice genome and will facilitate genetic improvement of cultivated rice varieties.

Mapping responsive genomic elements to heat stress in a maize diversity panel

BACKGROUND

Many plant species exhibit genetic variation for coping with environmental stress. However, there are still limited approaches to effectively uncover the genomic region that regulates distinct responsive patterns of the gene across multiple varieties within the same species under abiotic stress.

RESULTS

By analyzing the transcriptomes of more than 100 maize inbreds, we reveal many cis- and trans-acting eQTLs that influence the expression response to heat stress. The cis-acting eQTLs in response to heat stress are identified in genes with differential responses to heat stress between genotypes as well as genes that are only expressed under heat stress. The cis-acting variants for heat stress-responsive expression likely result from distinct promoter activities, and the differential heat responses of the alleles are confirmed for selected genes using transient expression assays. Global footprinting of transcription factor binding is performed in control and heat stress conditions to document regions with heat-enriched transcription factor binding occupancies.

CONCLUSIONS

Footprints enriched near proximal regions of characterized heat-responsive genes in a large association panel can be utilized for prioritizing functional genomic regions that regulate genotype-specific responses under heat stress.

Large-scale translatome profiling annotates the functional genome and reveals the key role of genic 3' untranslated regions in translatomic variation in plants

The translatome, a profile of the translational status of genetic information within cells, provides a new perspective on gene expression. Although many plant genomes have been sequenced, comprehensive translatomic annotations are not available for plants due to a lack of efficient translatome profiling techniques. Here, we developed a new technique termed 3' ribosome-profiling sequencing (3'Ribo-seq) for reliable, robust translatomic profiling. 3'Ribo-seq combines polysome profiling and 3' selection with a barcoding and pooling strategy. Systematic translatome profiling of different tissues of Arabidopsis, rice, and maize using conventional ribosome profiling (Ribo-seq) and 3'Ribo-seq revealed many novel translational genomic loci, thereby complementing functional genome annotation in plants. Using the low-cost, efficient 3'Ribo-seq technique and genome-wide association mapping of translatome expression (eGWAS), we performed a population-level dissection of the translatomes of 159 diverse maize inbred lines and identified 1,777 translational expression quantitative trait loci (eQTLs). Notably, local eQTLs are significantly enriched in the 3' untranslated regions of genes. Detailed eQTL analysis suggested that sequence variation around the polyadenylation (polyA) signal motif plays a key role in translatomic variation. Our study provides a comprehensive translatome annotation of plant functional genomes and introduces 3'Ribo-seq, which paves the way for deep translatomic analysis at the population level.

MP3RNA-seq: Massively parallel 3' end RNA sequencing for high-throughput gene expression profiling and genotyping

Transcriptome deep sequencing (RNA-seq) has become a routine method for global gene expression profiling. However, its application to large-scale experiments remains limited by cost and labor constraints. Here we describe a massively parallel 3' end RNA-seq (MP3RNA-seq) method that introduces unique sample barcodes during reverse transcription to permit sample pooling immediately following this initial step. MP3RNA-seq allows for handling of hundreds of samples in a single experiment, at a cost of about $6 per sample for library construction and sequencing. MP3RNA-seq is effective for not only high-throughput gene expression profiling, but also genotyping. To demonstrate its utility, we applied MP3RNA-seq to 477 double haploid lines of maize. We identified 19,429 genes expressed in at least 50% of the lines and 35,836 high-quality single nucleotide polymorphisms for genotyping analysis. Armed with these data, we performed expression and agronomic trait quantitative trait locus (QTL) mapping and identified 25,797 expression QTLs for 15,335 genes and 21 QTLs for plant height, ear height, and relative ear height. We conclude that MP3RNA-seq is highly reproducible, accurate, and sensitive for high-throughput gene expression profiling and genotyping, and should be generally applicable to most eukaryotic species.

Molecular and evolutionary processes generating variation in gene expression

Heritable variation in gene expression is common within and between species. This variation arises from mutations that alter the form or function of molecular gene regulatory networks that are then filtered by natural selection. High-throughput methods for introducing mutations and characterizing their cis- and trans-regulatory effects on gene expression (particularly, transcription) are revealing how different molecular mechanisms generate regulatory variation, and studies comparing these mutational effects with variation seen in the wild are teasing apart the role of neutral and non-neutral evolutionary processes. This integration of molecular and evolutionary biology allows us to understand how the variation in gene expression we see today came to be and to predict how it is most likely to evolve in the future.

Host-specialized transcriptome of plant-associated organisms

Living organisms respond to their immediate environment by modulating their genetic programme to perform adapted functions. Eukaryotic organisms that associate with plants (fungi, oomycetes, insects, …) alter their transcriptome in a host-specific manner. Recent comparative transcriptomic studies revealed that host-specialized transcriptomes consist of a limited set of genes. Such a set typically encodes proteins that modulate host structures and functions (predicted effectors and other secreted proteins), control nutrient assimilation (proteases, transporters), and maintain cellular homeostasis (oxidoreductases, detoxification enzymes). We conclude by discussing open mechanistic and evolutionary questions and integrated approaches to move beyond descriptive studies.

Morphological Variability Identification of Harumanis Mango (Mangifera indica L.) Harvested from Different Location and Tree Age

Harumanis is one of the main signatures of Perlis with regards to its delightful taste, pleasant aroma and expensive price. Harumanis authenticity and productivity had become the remarks among the farmers, entrepreneurs, consumers and plant breeders due to the existence of morphological characteristics variation among the fruits and high production cost. Assessment of Harumanis morphological characteristics of natural population and different tree ages may represent a possible source of important characteristics for development and breeding purposes of Harumanis. The aim of this study is to evaluate the morphological variation of Harumanis collected from different location in Perlis and tree age. A total of 150 Harumanis fruits from 50 trees with three different stages of development (young, middle-aged and old) were characterised using 11 traits; 10 quantitative and one qualitative morphological trait. The ANOVA analyses in combination with Dunn's pairwise and Kruskal-Wallis multiple comparison test able to point out the existence of environmental factor and age influence towards the significant different of identified morphological traits except for Total Soluble Solid (TSS) and pulp percentage. Five clusters of 50 Harumanis accessions reflect a grouping pattern which not according to neither geographical region nor age. The result of Principal Component Analysis (PCA) using the first two principal components (PCs) provided a good approximation of the data explaining 84.09% of the total variance which majorly contributed by parameters of weight, fruit dimensional characteristics, peel percentage and hue angle, h. Preliminary screening of important morphological characteristics which contribute to the phenotypic diversity of Harumanis is successfully achieved. The findings can be employed by the plant breeders and farmers for the establishment of standard grading of Harumanis and advancement of breeding crop of Harumanis in future.

Genome-wide expression quantitative trait locus studies facilitate isolation of causal genes controlling panicle structure

The morphology of rice (Oryza sativa L.) panicles is an important determinant of grain yield, and elucidation of the genetic control of panicle structure is very important for fulfilling the demand for high yield in breeding programs. In a quantitative trait locus (QTL) study using 82 backcross inbred lines (BILs) derived from Koshihikari and Habataki, 68 QTLs for 25 panicle morphological traits were identified. Gene expression profiling from inflorescence meristems of BILs was obtained. A combination of phenotypic QTL (pQTL) and expression QTL (eQTL) analysis revealed co-localization between pQTLs and eQTLs, consistent with significant correlations between phenotypic traits and gene expression levels. By combining pQTL and eQTL data, two genes were identified as controlling panicle structure: OsMADS18 modulates the average length of the primary rachis and OsFTL1 has pleiotropic effects on the total number of secondary rachides, number of grains per panicle, plant height and the length of flag leaves. Phenotypes were confirmed in RNA interference knocked-down plants and overexpressor lines. The combination of pQTL and eQTL analysis could facilitate identification of genes involved in rice panicle formation.

The Evolutionary Forces Shaping Cis- and Trans-Regulation of Gene Expression within a Population of Outcrossing Plants

Understanding the persistence of genetic variation within populations has long been a goal of evolutionary biology. One promising route toward achieving this goal is using population genetic approaches to describe how selection acts on the loci associated with trait variation. Gene expression provides a model trait for addressing the challenge of the maintenance of variation because it can be measured genome-wide without information about how gene expression affects traits. Previous work has shown that loci affecting the expression of nearby genes (local or cis-eQTLs) are under negative selection, but we lack a clear understanding of the selective forces acting on variants that affect the expression of genes in trans. Here, we identify loci that affect gene expression in trans using genomic and transcriptomic data from one population of the obligately outcrossing plant, Capsella grandiflora. The allele frequencies of trans-eQTLs are consistent with stronger negative selection acting on trans-eQTLs than cis-eQTLs, and stronger negative selection acting on trans-eQTLs associated with the expression of multiple genes. However, despite this general pattern, we still observe the presence of a trans-eQTL at intermediate frequency that affects the expression of a large number of genes in the same coexpression module. Overall, our work highlights the different selective pressures shaping variation in cis- and trans-regulation.

Genome-wide expression quantitative trait locus analysis in a recombinant inbred line population for trait dissection in peanut

The transcriptome connects genome to the gene function and ultimate phenome in biology. So far, transcriptomic approach was not used in peanut for performing trait mapping in bi-parental populations. In this research, we sequenced the whole transcriptome in immature seeds in a peanut recombinant inbred line (RIL) population and explored thoroughly the landscape of transcriptomic variations and its genetic basis. The comprehensive analysis identified total 49 691 genes in RIL population, of which 92 genes followed a paramutation-like expression pattern. Expression quantitative trait locus (eQTL) analysis identified 1207 local eQTLs and 15 837 distant eQTLs contributing to the whole-genome transcriptomic variation in peanut. There were 94 eQTL hot spot regions detected across the genome with the dominance of distant eQTL. By integrating transcriptomic profile and annotation analyses, we unveiled a putative candidate gene and developed a linked marker InDel02 underlying a major QTL responsible for purple testa colour in peanut. Our result provided a first understanding of genetic basis of whole-genome transcriptomic variation in peanut and illustrates the potential of the transcriptome-aid approach in dissecting important traits in non-model plants.

Quantitative Trait Loci (QTL) Mapping

Quantitative trait loci (QTL) are genetic regions that influence phenotypic variation of a complex trait, often through genetic interactions with each other and the environment. These are commonly identified through a statistical genetic analysis known as QTL mapping. Here, I present a step-by-step, practical approach to QTL mapping along with a sample data file. I focus on methods commonly used and discoveries that have been made in fishes, and utilize a multiple QTL mapping (MQM) approach in the free software package R/qtl.

Challenges of Translating Gene Regulatory Information into Agronomic Improvements

Improvement of agricultural species has exploited the genetic variation responsible for complex quantitative traits. Much of the functional variation is regulatory, in cis-regulatory elements and trans-acting factors that ultimately contribute to gene expression differences. However, the identification of gene regulatory network components that, when modulated, will increase plant productivity or resilience, is challenging, yet essential to provide increased predictive power for genome engineering approaches that are likely to benefit useful traits. Here, we discuss the opportunities and limitations of using data obtained from gene coexpression, transcription factor binding, and genome-wide association mapping analyses to predict regulatory interactions that impact crop improvement. It is apparent that a combination of information from these data types is necessary for the reliable identification and utilization of important regulatory interactions that underlie complex agronomic traits.

DNA N6-Methyladenosine modification role in transmitted variations from genomic DNA to RNA in Herrania umbratica

Background

DNA methylation is an important epigenetic modification. Recently the developed single-molecule real-time (SMRT) sequencing technology provided an efficient way to detect DNA N6-methyladenine (6mA) modification that played an important role in epigenetic and positively regulated gene expression. In addition, the gene expression was also regulated by genetic variation. However, the relationship between DNA 6mA modification and variation is still unknown.

Results

We collected the SMRT long-reads DNA, Illumina short reads DNA and RNA datasets from the young leaves of Herrania umbratica, and used them to detect 35,654 6mA modification sites, 829,894 DNA variations and 60,672 RNA variations respectively, among which, there are 303 DNA variations and 19 RNA variations with 6mA modification, and 57,468 transmitted genetic variations from DNA to RNA. The results illustrated that the genes with 6mA modification were significant disadvantage to mutate than those genes without modification (p-value< 4.9e-08). And result from the linear regression model showed the 6mA densities of genes were associated with the transmitted variations type 0/1 to 1/1 (p-value < 0.001).

Conclusions

The variations of DNA and RNA in genes with 6mA modification were significant less than those in unmodified genes. Furthermore, the variations in 6mA modified genes were easily transmitted from DNA to RNA, especially the transmitted variation from DNA heterozygote to RNA homozygote.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5776-0) contains supplementary material, which is available to authorized users.

Kernel size-related genes revealed by an integrated eQTL analysis during early maize kernel development

In maize, kernel traits strongly impact overall grain yields, and it is known that sophisticated spatiotemporal programs of gene expression coordinate kernel development, so advancing our knowledge of kernel development can help efforts to improve grain yields. Here, using phenotype, genotype and transcriptomics data of maize kernels at 5 and 15 days after pollination (DAP) for a large association mapping panel, we employed multiple quantitative genetics approaches-genome-wide association studies (GWAS) as well as expression quantitative trait loci (eQTL) and quantitative trait transcript (QTT) analyses-to gain insights about molecular genetic basis of kernel development in maize. This resulted in the identification of 137 putative kernel length-related genes at 5 DAP, of which 43 are located in previously reported QTL regions. Strikingly, we identified an eQTL that overlaps the locus encoding a maize homolog of the recently described m⁶ A methylation reader protein ECT2 from Arabidopsis; this putative ^epi eQTL is associated with 53 genes and may represent a master epi-transcriptomic regulator of kernel development. Notably, among the genes associated with this ^epi eQTL, 10 are for the main storage proteins in the maize endosperm (zeins) and two are known regulators of zein expression or endosperm development (Opaque2 and ZmICE1). Collectively, beyond cataloging and characterizing genomic attributes of a large number of eQTL associated with kernel development in maize, our study highlights how an eQTL approach can bolster the impact of both GWAS and QTT studies and can drive insights about the basic biology of plants.

Regulation of Root Angle and Gravitropism

Regulation of plant root angle is critical for obtaining nutrients and water and is an important trait for plant breeding. A plant’s final, long-term root angle is the net result of a complex series of decisions made by a root tip in response to changes in nutrient availability, impediments, the gravity vector and other stimuli. When a root tip is displaced from the gravity vector, the short-term process of gravitropism results in rapid reorientation of the root toward the vertical. Here, we explore both short- and long-term regulation of root growth angle, using natural variation in tomato to identify shared and separate genetic features of the two responses. Mapping of expression quantitative trait loci mapping and leveraging natural variation between and within species including Arabidopsis suggest a role for PURPLE ACID PHOSPHATASE 27 and CELL DIVISION CYCLE 73 in determining root angle.

Improvement of Drought Tolerance in Rice (Oryza sativa L.): Genetics, Genomic Tools, and the WRKY Gene Family

Drought tolerance is an important quantitative trait with multipart phenotypes that are often further complicated by plant phenology. Different types of environmental stresses, such as high irradiance, high temperatures, nutrient deficiencies, and toxicities, may challenge crops simultaneously; therefore, breeding for drought tolerance is very complicated. Interdisciplinary researchers have been attempting to dissect and comprehend the mechanisms of plant tolerance to drought stress using various methods; however, the limited success of molecular breeding and physiological approaches suggests that we rethink our strategies. Recent genetic techniques and genomics tools coupled with advances in breeding methodologies and precise phenotyping will likely reveal candidate genes and metabolic pathways underlying drought tolerance in crops. The WRKY transcription factors are involved in different biological processes in plant development. This zinc (Zn) finger protein family, particularly members that respond to and mediate stress responses, is exclusively found in plants. A total of 89 WRKY genes in japonica and 97 WRKY genes in O. nivara (OnWRKY) have been identified and mapped onto individual chromosomes. To increase the drought tolerance of rice (Oryza sativa L.), research programs should address the problem using a multidisciplinary strategy, including the interaction of plant phenology and multiple stresses, and the combination of drought tolerance traits with different genetic and genomics approaches, such as microarrays, quantitative trait loci (QTLs), WRKY gene family members with roles in drought tolerance, and transgenic crops. This review discusses the newest advances in plant physiology for the exact phenotyping of plant responses to drought to update methods of analysing drought tolerance in rice. Finally, based on the physiological/morphological and molecular mechanisms found in resistant parent lines, a strategy is suggested to select a particular environment and adapt suitable germplasm to that environment.

GPD1 and ADH3 Natural Variants Underlie Glycerol Yield Differences in Wine Fermentation

Glycerol is one of the most important by-products of alcohol fermentation, and depending on its concentration it can contribute to wine flavor intensity and aroma volatility. Here, we evaluated the potential of utilizing the natural genetic variation of non-coding regions in budding yeast to identify allelic variants that could modulate glycerol phenotype during wine fermentation. For this we utilized four Saccharomyces cerevisiae strains (WE - Wine/European, SA – Sake, NA – North American, and WA – West African), which were previously profiled for genome-wide Allele Specific Expression (ASE) levels. The glycerol yields under Synthetic Wine Must (SWM) fermentations differed significantly between strains; WA produced the highest glycerol yields while SA produced the lowest yields. Subsequently, from our ASE database, we identified two candidate genes involved in alcoholic fermentation pathways, ADH3 and GPD1, exhibiting significant expression differences between strains. A reciprocal hemizygosity assay demonstrated that hemizygotes expressing GPD1^WA, GPD1^SA, ADH3^WA and ADH3^SA alleles had significantly greater glycerol yields compared to GPD1^WE and ADH3^WE. We further analyzed the gene expression profiles for each GPD1 variant under SWM, demonstrating that the expression of GPD1^WE occurred earlier and was greater compared to the other alleles. This result indicates that the level, timing, and condition of expression differ between regulatory regions in the various genetic backgrounds. Furthermore, promoter allele swapping demonstrated that these allele expression patterns were transposable across genetic backgrounds; however, glycerol yields did not differ between wild type and modified strains, suggesting a strong trans effect on GPD1 gene expression. In this line, Gpd1 protein levels in parental strains, particularly Gpd1p^WE, did not necessarily correlate with gene expression differences, but rather with glycerol yield where low Gpd1p^WE levels were detected. This suggests that GPD1^WE is influenced by recessive negative post-transcriptional regulation which is absent in the other genetic backgrounds. This dissection of regulatory mechanisms in GPD1 allelic variants demonstrates the potential to exploit natural alleles to improve glycerol production in wine fermentation and highlights the difficulties of trait improvement due to alternative trans-regulation and gene-gene interactions in the different genetic background.

Deciphering genetic factors that determine melon fruit-quality traits using RNA-Seq-based high-resolution QTL and eQTL mapping

Combined quantitative trait loci (QTL) and expression-QTL (eQTL) mapping analysis was performed to identify genetic factors affecting melon (Cucumis melo) fruit quality, by linking genotypic, metabolic and transcriptomic data from a melon recombinant inbred line (RIL) population. RNA sequencing (RNA-Seq) of fruit from 96 RILs yielded a highly saturated collection of > 58 000 single-nucleotide polymorphisms, identifying 6636 recombination events that separated the genome into 3663 genomic bins. Bin-based QTL analysis of 79 RILs and 129 fruit-quality traits affecting taste, aroma and color resulted in the mapping of 241 QTL. Thiol acyltransferase (CmThAT1) gene was identified within the QTL interval of its product, S-methyl-thioacetate, a key component of melon fruit aroma. Metabolic activity of CmThAT1-encoded protein was validated in bacteria and in vitro. QTL analysis of flesh color intensity identified a candidate white-flesh gene (CmPPR1), one of two major loci determining fruit flesh color in melon. CmPPR1 encodes a member of the pentatricopeptide protein family, involved in processing of RNA in plastids, where carotenoid and chlorophyll pigments accumulate. Network analysis of > 12 000 eQTL mapped for > 8000 differentially expressed fruit genes supported the role of CmPPR1 in determining the expression level of plastid targeted genes. We highlight the potential of RNA-Seq-based QTL analysis of small to moderate size, advanced RIL populations for precise marker-assisted breeding and gene discovery. We provide the following resources: a RIL population genotyped with a unique set of SNP markers, confined genomic segments that harbor QTL governing 129 traits and a saturated set of melon eQTLs.

Genome-wide Analysis of Transcriptional Variability in a Large Maize-Teosinte Population

Gene expression regulation plays an important role in controlling plant phenotypes and adaptation. Here, we report a comprehensive assessment of gene expression variation through the transcriptome analyses of a large maize-teosinte experimental population. Genome-wide mapping identified 25 660 expression quantitative trait loci (eQTL) for 17 311 genes, capturing an unprecedented range of expression variation. We found that local eQTL were more frequently mapped to adjacent genes, displaying a mode of expression piggybacking, which consequently created co-regulated gene clusters. Genes within the co-regulated gene clusters tend to have relevant functions and shared chromatin modifications. Distant eQTL formed 125 significant distant eQTL hotspots with their targets significantly enriched in specific functional categories. By integrating different sources of information, we identified putative trans- regulators for a variety of metabolic pathways. We demonstrated that the bHLH transcription factor R1 and hexokinase HEX9 might act as crucial regulators for flavonoid biosynthesis and glycolysis, respectively. Moreover, we showed that domestication or improvement has significantly affected global gene expression, with many genes targeted by selection. Of particular interest, the Bx genes for benzoxazinoid biosynthesis may have undergone coordinated cis-regulatory divergence between maize and teosinte, and a transposon insertion that inactivates Bx12 was under strong selection as maize spread into temperate environments with a distinct herbivore community.

Quantitative Trait Transcripts Mapping Coupled with Expression Quantitative Trait Loci Mapping Reveal the Molecular Network Regulating the Apetalous Characteristic in Brassica napus L

The apetalous trait of rapeseed (Brassica napus, AACC, 2n = 38) is important for breeding an ideal high-yield rapeseed with superior klendusity to Sclerotinia sclerotiorum. Currently, the molecular mechanism underlying the apetalous trait of rapeseed is unclear. In this study, 14 petal regulators genes were chosen as target genes (TGs), and the expression patterns of the 14 TGs in the AH population, containing 189 recombinant inbred lines derived from a cross between apetalous "APL01" and normal "Holly," were analyzed in two environments using qRT-PCR. Phenotypic data of petalous degree (PDgr) in the AH population were obtained from the two environments. Both quantitative trait transcript (QTT)-association mapping and expression QTL (eQTL) analyses of TGs expression levels were performed to reveal regulatory relationships among TGs and PDgr. QTT mapping for PDgr determined that PLURIPETALA (PLP) was the major negative QTT associated with PDgr in both environments, suggesting that PLP negatively regulates the petal development of line "APL01." The QTT mapping of PLP expression levels showed that CHROMATIN-REMODELING PROTEIN 11 (CHR11) was positively associated with PLP expression, indicating that CHR11 acts as a positive regulator of PLP expression. Similarly, QTT mapping for the remaining TGs identified 38 QTTs, associated with 13 TGs, and 31 QTTs, associated with 10 TGs, respectively, in the first and second environments. Additionally, eQTL analyses of TG expression levels showed that 12 and 11 unconditional eQTLs were detected in the first and second environment, respectively. Based on the QTTs and unconditional eQTLs detected, we presented a hypothetical molecular regulatory network in which 14 petal regulators potentially regulated the apetalous trait in "APL01" through the CHR11-PLP pathway. PLP acts directly as the terminal signal integrator negatively regulating petal development in the CHR11-PLP pathway. These findings will aid in the understanding the molecular mechanism underlying the apetalous trait of rapeseed.

Interchromosomal Transfer of Immune Regulation During Infection of Barley with the Powdery Mildew Pathogen

Powdery mildew pathogens colonize over 9500 plant species, causing critical yield loss. The Ascomycete fungus, Blumeria graminis f. sp. hordei (Bgh), causes powdery mildew disease in barley (Hordeum vulgare L.). Successful infection begins with penetration of host epidermal cells, culminating in haustorial feeding structures, facilitating delivery of fungal effectors to the plant and exchange of nutrients from host to pathogen. We used expression Quantitative Trait Locus (eQTL) analysis to dissect the temporal control of immunity-associated gene expression in a doubled haploid barley population challenged with Bgh. Two highly significant regions possessing trans eQTL were identified near the telomeric ends of chromosomes (Chr) 2HL and 1HS. Within these regions reside diverse resistance loci derived from barley landrace H. laevigatum (MlLa) and H. vulgare cv. Algerian (Mla1), which associate with the altered expression of 961 and 3296 genes during fungal penetration of the host and haustorial development, respectively. Regulatory control of transcript levels for 299 of the 961 genes is reprioritized from MlLa on 2HL to Mla1 on 1HS as infection progresses, with 292 of the 299 alternating the allele responsible for higher expression, including Adaptin Protein-2 subunit μ AP2M and Vesicle Associated Membrane Protein VAMP72 subfamily members VAMP721/722. AP2M mediates effector-triggered immunity (ETI) via endocytosis of plasma membrane receptor components. VAMP721/722 and SNAP33 form a Soluble N-ethylmaleimide-sensitive factor Attachment Protein REceptor (SNARE) complex with SYP121 (PEN1), which is engaged in pathogen associated molecular pattern (PAMP)-triggered immunity via exocytosis. We postulate that genes regulated by alternate chromosomal positions are repurposed as part of a conserved immune complex to respond to different pathogen attack scenarios.

Quantitative trait loci from identification to exploitation for crop improvement

Advancement in the field of genetics and genomics after the discovery of Mendel's laws of inheritance has led to map the genes controlling qualitative and quantitative traits in crop plant species. Mapping of genomic regions controlling the variation of quantitatively inherited traits has become routine after the advent of different types of molecular markers. Recently, the next generation sequencing methods have accelerated the research on QTL analysis. These efforts have led to the identification of more closely linked molecular markers with gene/QTLs and also identified markers even within gene/QTL controlling the trait of interest. Efforts have also been made towards cloning gene/QTLs or identification of potential candidate genes responsible for a trait. Further new concepts like crop QTLome and QTL prioritization have accelerated precise application of QTLs for genetic improvement of complex traits. In the past years, efforts have also been made in exploitation of a number of QTL for improving grain yield or other agronomic traits in various crops through markers assisted selection leading to cultivation of these improved varieties at farmers' field. In present article, we reviewed QTLs from their identification to exploitation in plant breeding programs and also reviewed that how improved cultivars developed through introgression of QTLs have improved the yield productivity in many crops.

In-depth genome characterization of a Brazilian common bean core collection using DArTseq high-density SNP genotyping

BACKGROUND

Common bean is a legume of social and nutritional importance as a food crop, cultivated worldwide especially in developing countries, accounting for an important source of income for small farmers. The availability of the complete sequences of the two common bean genomes has dramatically accelerated and has enabled new experimental strategies to be applied for genetic research. DArTseq has been widely used as a method of SNP genotyping allowing comprehensive genome coverage with genetic applications in common bean breeding programs.

RESULTS

Using this technology, 6286 SNPs (1 SNP/86.5 Kbp) were genotyped in genic (43.3%) and non-genic regions (56.7%). Genetic subdivision associated to the common bean gene pools (K = 2) and related to grain types (K = 3 and K = 5) were reported. A total of 83% and 91% of all SNPs were polymorphic within the Andean and Mesoamerican gene pools, respectively, and 26% were able to differentiate the gene pools. Genetic diversity analysis revealed an average H E of 0.442 for the whole collection, 0.102 for Andean and 0.168 for Mesoamerican gene pools (F ST  = 0.747 between gene pools), 0.440 for the group of cultivars and lines, and 0.448 for the group of landrace accessions (F ST  = 0.002 between cultivar/line and landrace groups). The SNP effects were predicted with predominance of impact on non-coding regions (77.8%). SNPs under selection were identified within gene pools comparing landrace and cultivar/line germplasm groups (Andean: 18; Mesoamerican: 69) and between the gene pools (59 SNPs), predominantly on chromosomes 1 and 9. The LD extension estimate corrected for population structure and relatedness (r2SV) was ~ 88 kbp, while for the Andean gene pool was ~ 395 kbp, and for the Mesoamerican was ~ 130 kbp.

CONCLUSIONS

For common bean, DArTseq provides an efficient and cost-effective strategy of generating SNPs for large-scale genome-wide studies. The DArTseq resulted in an operational panel of 560 polymorphic SNPs in linkage equilibrium, providing high genome coverage. This SNP set could be used in genotyping platforms with many applications, such as population genetics, phylogeny relation between common bean varieties and support to molecular breeding approaches.

eQTLs Regulating Transcript Variations Associated with Rapid Internode Elongation in Deepwater Rice

To avoid low oxygen, oxygen deficiency or oxygen deprivation, deepwater rice cultivated in flood planes can develop elongated internodes in response to submergence. Knowledge of the gene regulatory networks underlying rapid internode elongation is important for an understanding of the evolution and adaptation of major crops in response to flooding. To elucidate the genetic and molecular basis controlling their deepwater response we used microarrays and performed expression quantitative trait loci (eQTL) and phenotypic QTL (phQTL) analyses of internode samples of 85 recombinant inbred line (RIL) populations of non-deepwater (Taichung 65)- and deepwater rice (Bhadua). After evaluating the phenotypic response of the RILs exposed to submergence, confirming the genotypes of the populations, and generating 188 genetic markers, we identified 10,047 significant eQTLs comprised of 2,902 cis-eQTLs and 7,145 trans-eQTLs and three significant eQTL hotspots on chromosomes 1, 4, and 12 that affect the expression of many genes. The hotspots on chromosomes 1 and 4 located at different position from phQTLs detected in this study and other previous studies. We then regarded the eQTL hotspots as key regulatory points to infer causal regulatory networks of deepwater response including rapid internode elongation. Our results suggest that the downstream regulation of the eQTL hotspots on chromosomes 1 and 4 is independent, and that the target genes are partially regulated by SNORKEL1 and SNORKEL2 genes (SK1/2), key ethylene response factors. Subsequent bioinformatic analyses, including gene ontology-based annotation and functional enrichment analysis and promoter enrichment analysis, contribute to enhance our understanding of SK1/2-dependent and independent pathways. One remarkable observation is that the functional categories related to photosynthesis and light signaling are significantly over-represented in the candidate target genes of SK1/2. The combined results of these investigations together with genetical genomics approaches using structured populations with a deepwater response are also discussed in the context of current molecular models concerning the rapid internode elongation in deepwater rice. This study provides new insights into the underlying genetic architecture of gene expression regulating the response to flooding in deepwater rice and will be an important community resource for analyses on the genetic basis of deepwater responses.

Comparative Transcriptome Analysis Reveals a Preformed Defense System in Apple Root of a Resistant Genotype of G.935 in the Absence of Pathogen

Two apple rootstock genotypes G.935 and B.9 were recently demonstrated to exhibit distinct resistance responses following infection by Pythium ultimum. As part of an effort to elucidate the genetic regulation of apple root resistance to soilborne pathogens, preinoculation transcriptome variations in roots of these two apple rootstock genotypes are hypothesized to contribute to the observed disease resistance phenotypes. Results from current comparative transcriptome analysis demonstrated elevated transcript abundance for many genes which function in a system-wide defense response in the root tissue of the resistant genotype of G.935 in comparison with susceptible B.9. Based on the functional annotation, these differentially expressed genes encode proteins that function in several tiers of defense responses, such as pattern recognition receptors for pathogen detection and subsequent signal transduction, defense hormone biosynthesis and signaling, transcription factors with known roles in defense activation, enzymes of secondary metabolism, and various classes of resistance proteins. The data set suggested a more poised status, which is ready to defend pathogen infection, in the root tissues of resistant genotype of G.935, compared to the susceptible B.9. The significance of preformed defense in the absence of a pathogen toward overall resistance phenotypes in apple root and the potential fitness cost due to the overactivated defense system were discussed.

Natural gene expression variation studies in yeast

The rise of sequence information across different yeast species and strains is driving an increasing number of studies in the emerging field of genomics to associate polymorphic variants, mRNA abundance and phenotypic differences between individuals. Here, we gathered evidence from recent studies covering several layers that define the genotype-phenotype gap, such as mRNA abundance, allele-specific expression and translation efficiency to demonstrate how genetic variants co-evolve and define an individual's genome. Moreover, we exposed several antecedents where inter- and intra-specific studies led to opposite conclusions, probably owing to genetic divergence. Future studies in this area will benefit from the access to a massive array of well-annotated genomes and new sequencing technologies, which will allow the fine breakdown of the complex layers that delineate the genotype-phenotype map. Copyright © 2016 John Wiley & Sons, Ltd.

Natural variation in non-coding regions underlying phenotypic diversity in budding yeast

Linkage mapping studies in model organisms have typically focused their efforts in polymorphisms within coding regions, ignoring those within regulatory regions that may contribute to gene expression variation. In this context, differences in transcript abundance are frequently proposed as a source of phenotypic diversity between individuals, however, until now, little molecular evidence has been provided. Here, we examined Allele Specific Expression (ASE) in six F1 hybrids from Saccharomyces cerevisiae derived from crosses between representative strains of the four main lineages described in yeast. ASE varied between crosses with levels ranging between 28% and 60%. Part of the variation in expression levels could be explained by differences in transcription factors binding to polymorphic cis-regulations and to differences in trans-activation depending on the allelic form of the TF. Analysis on highly expressed alleles on each background suggested ASN1 as a candidate transcript underlying nitrogen consumption differences between two strains. Further promoter allele swap analysis under fermentation conditions confirmed that coding and non-coding regions explained aspartic and glutamic acid consumption differences, likely due to a polymorphism affecting Uga3 binding. Together, we provide a new catalogue of variants to bridge the gap between genotype and phenotype.

Expression profiling of genes involved in drought stress and leaf senescence in juvenile barley

BACKGROUND

Drought stress in juvenile stages of crop development and premature leaf senescence induced by drought stress have an impact on biomass production and yield formation of barley (Hordeum vulgare L.). Therefore, in order to get information of regulatory processes involved in the adaptation to drought stress and leaf senescence expression analyses of candidate genes were conducted on a set of 156 barley genotypes in early developmental stages, and expression quantitative trait loci (eQTL) were identified by a genome wide association study.

RESULTS

Significant effects of genotype and treatment were detected for leaf colour measured at BBCH 25 as an indicator of leaf senescence and for the expression level of the genes analysed. Furthermore, significant correlations were detected within the group of genes involved in drought stress (r = 0.84) and those acting in leaf senescence (r = 0.64), as well as between leaf senescence genes and the leaf colour (r = 0.34). Based on these expression data and 3,212 polymorphic single nucleotide polymorphisms (SNP) with a minor allele frequency >5% derived from the Illumina 9 k iSelect SNP Chip, eight cis eQTL and seven trans eQTL were found. Out of these an eQTL located on chromosome 3H at 142.1 cM is of special interest harbouring two drought stress genes (GAD3 and P5CS2) and one leaf senescence gene (Contig7437), as well as an eQTL on chromosome 5H at 44.5 cM in which two genes (TRIUR3 and AVP1) were identified to be associated to drought stress tolerance in a previous study.

CONCLUSION

With respect to the expression of genes involved in drought stress and early leaf senescence, genotypic differences exist in barley. Major eQTL for the expression of these genes are located on barley chromosome 3H and 5H. Respective markers may be used in future barley breeding programmes for improving tolerance to drought stress and leaf senescence.

Learning from Co-expression Networks: Possibilities and Challenges

Plants are fascinating and complex organisms. A comprehensive understanding of the organization, function and evolution of plant genes is essential to disentangle important biological processes and to advance crop engineering and breeding strategies. The ultimate aim in deciphering complex biological processes is the discovery of causal genes and regulatory mechanisms controlling these processes. The recent surge of omics data has opened the door to a system-wide understanding of the flow of biological information underlying complex traits. However, dealing with the corresponding large data sets represents a challenging endeavor that calls for the development of powerful bioinformatics methods. A popular approach is the construction and analysis of gene networks. Such networks are often used for genome-wide representation of the complex functional organization of biological systems. Network based on similarity in gene expression are called (gene) co-expression networks. One of the major application of gene co-expression networks is the functional annotation of unknown genes. Constructing co-expression networks is generally straightforward. In contrast, the resulting network of connected genes can become very complex, which limits its biological interpretation. Several strategies can be employed to enhance the interpretation of the networks. A strategy in coherence with the biological question addressed needs to be established to infer reliable networks. Additional benefits can be gained from network-based strategies using prior knowledge and data integration to further enhance the elucidation of gene regulatory relationships. As a result, biological networks provide many more applications beyond the simple visualization of co-expressed genes. In this study we review the different approaches for co-expression network inference in plants. We analyse integrative genomics strategies used in recent studies that successfully identified candidate genes taking advantage of gene co-expression networks. Additionally, we discuss promising bioinformatics approaches that predict networks for specific purposes.

The quest for tolerant varieties: the importance of integrating "omics" techniques to phenotyping

The primary objective of crop breeding is to improve yield and/or harvest quality while minimizing inputs. Global climate change and the increase in world population are significant challenges for agriculture and call for further improvements to crops and the development of new tools for research. Significant progress has been made in the molecular and genetic analysis of model plants. However, is science generating false expectations? Are 'omic techniques generating valuable information that can be translated into the field? The exploration of crop biodiversity and the correlation of cellular responses to stress tolerance at the plant level is currently a challenge. This viewpoint reviews concisely the problems one encounters when working on a crop and provides an outline of possible workflows when initiating cellular phenotyping via "-omic" techniques (transcriptomics, proteomics, metabolomics).

Genetic basis of sRNA quantitative variation analyzed using an experimental population derived from an elite rice hybrid

We performed a genetic analysis of sRNA abundance in flag leaf from an immortalized F₂ (IMF2) population in rice. We identified 53,613,739 unique sRNAs and 165,797 sRNA expression traits (s-traits). A total of 66,649 s-traits mapped 40,049 local-sQTLs and 30,809 distant-sQTLs. By defining 80,362 sRNA clusters, 22,263 sRNA cluster QTLs (scQTLs) were recovered for 20,249 of all the 50,139 sRNA cluster expression traits (sc-traits). The expression levels for most of s-traits from the same genes or the same sRNA clusters were slightly positively correlated. While genetic co-regulation between sRNAs from the same mother genes and between sRNAs and their mother genes was observed for a portion of the sRNAs, most of the sRNAs and their mother genes showed little co-regulation. Some sRNA biogenesis genes were located in distant-sQTL hotspots and showed correspondence with specific length classes of sRNAs suggesting their important roles in the regulation and biogenesis of the sRNAs.

DOI:http://dx.doi.org/10.7554/eLife.03913.001

Genes within the DNA of a plant or animal contain instructions to make molecules called RNAs. Some RNA molecules can be decoded to make proteins, whereas others have different roles. A single gene often contains the instructions to make both protein-coding RNAs and non-coding RNAs.

Molecules called small RNAs (or sRNAs) do not code for proteins. Instead, sRNAs can control protein-coding RNA molecules or chemically alter the DNA itself; this allows them to perform many different roles in living organisms. In plants, for example, these molecules affect how the plant grows, the shapes and structures it forms, and how likely it is to survive challenges such as drought and diseases. Often different plants of the same species have different amounts of sRNAs, but the reasons for this remain unclear.

Now, Wang, Yao et al. have made use of a technique called ‘expression quantitative locus’ analysis to look at how sRNAs in rice plants are controlled by additional information encoded within DNA. The analysis identified over 53 million sRNA molecules from a population of rice plants. Many of these sRNAs varied in their abundance between different plants within the population. Wang, Yao et al. also found many thousands of individual instructions within the DNA of the rice that can either increase or reduce the abundance of their associated sRNA.

Some of the abundant sRNAs were influenced by instructions within their own genes; some were influenced by instructions from other genes; and some were influenced by both. Wang, Yao et al. also found that the control of protein-coding RNAs was not necessarily related to the control of sRNAs encoded by the same gene. Further work is now needed to identify which specific DNA sequences regulate the abundance of sRNA molecules in plants and other organisms.

DOI:http://dx.doi.org/10.7554/eLife.03913.002

Genetic variation in the nuclear and organellar genomes modulates stochastic variation in the metabolome, growth, and defense

Recent studies are starting to show that genetic control over stochastic variation is a key evolutionary solution of single celled organisms in the face of unpredictable environments. This has been expanded to show that genetic variation can alter stochastic variation in transcriptional processes within multi-cellular eukaryotes. However, little is known about how genetic diversity can control stochastic variation within more non-cell autonomous phenotypes. Using an Arabidopsis reciprocal RIL population, we showed that there is significant genetic diversity influencing stochastic variation in the plant metabolome, defense chemistry, and growth. This genetic diversity included loci specific for the stochastic variation of each phenotypic class that did not affect the other phenotypic classes or the average phenotype. This suggests that the organism's networks are established so that noise can exist in one phenotypic level like metabolism and not permeate up or down to different phenotypic levels. Further, the genomic variation within the plastid and mitochondria also had significant effects on the stochastic variation of all phenotypic classes. The genetic influence over stochastic variation within the metabolome was highly metabolite specific, with neighboring metabolites in the same metabolic pathway frequently showing different levels of noise. As expected from bet-hedging theory, there was more genetic diversity and a wider range of stochastic variation for defense chemistry than found for primary metabolism. Thus, it is possible to begin dissecting the stochastic variation of whole organismal phenotypes in multi-cellular organisms. Further, there are loci that modulate stochastic variation at different phenotypic levels. Finding the identity of these genes will be key to developing complete models linking genotype to phenotype.

Extensive cis-regulatory variation robust to environmental perturbation in Arabidopsis

cis- and trans-acting factors affect gene expression and responses to environmental conditions. However, for most plant systems, we lack a comprehensive map of these factors and their interaction with environmental variation. Here, we examined allele-specific expression (ASE) in an F1 hybrid to study how alleles from two Arabidopsis thaliana accessions affect gene expression. To investigate the effect of the environment, we used drought stress and developed a variance component model to estimate the combined genetic contributions of cis- and trans-regulatory polymorphisms, environmental factors, and their interactions. We quantified ASE for 11,003 genes, identifying 3318 genes with consistent ASE in control and stress conditions, demonstrating that cis-acting genetic effects are essentially robust to changes in the environment. Moreover, we found 1618 genes with genotype x environment (GxE) interactions, mostly cis x E interactions with magnitude changes in ASE. We found fewer trans x E interactions, but these effects were relatively less robust across conditions, showing more changes in the direction of the effect between environments; this confirms that trans-regulation plays an important role in the response to environmental conditions. Our data provide a detailed map of cis- and trans-regulation and GxE interactions in A. thaliana, laying the ground for mechanistic investigations and studies in other plants and environments.

Molecular and physiological responses to abiotic stress in forest trees and their relevance to tree improvement

Abiotic stresses, such as drought, salinity and cold, are the major environmental stresses that adversely affect tree growth and, thus, forest productivity, and play a major role in determining the geographic distribution of tree species. Tree responses and tolerance to abiotic stress are complex biological processes that are best analyzed at a systems level using genetic, genomic, metabolomic and phenomic approaches. This will expedite the dissection of stress-sensing and signaling networks to further support efficient genetic improvement programs. Enormous genetic diversity for stress tolerance exists within some forest-tree species, and due to advances in sequencing technologies the molecular genetic basis for this diversity has been rapidly unfolding in recent years. In addition, the use of emerging phenotyping technologies extends the suite of traits that can be measured and will provide us with a better understanding of stress tolerance. The elucidation of abiotic stress-tolerance mechanisms will allow for effective pyramiding of multiple tolerances in a single tree through genetic engineering. Here we review recent progress in the dissection of the molecular basis of abiotic stress tolerance in forest trees, with special emphasis on Populus, Pinus, Picea, Eucalyptus and Quercus spp. We also outline practices that will enable the deployment of trees engineered for abiotic stress tolerance to land owners. Finally, recommendations for future work are discussed.

Elucidating the molecular responses of apple rootstock resistant to ARD pathogens: challenges and opportunities for development of genomics-assisted breeding tools

Apple replant disease (ARD) is a major limitation to the establishment of economically viable orchards on replant sites due to the buildup and long-term survival of pathogen inoculum. Several soilborne necrotrophic fungi and oomycetes are primarily responsible for ARD, and symptoms range from serious inhibition of growth to the death of young trees. Chemical fumigation has been the primary method used for control of ARD, and manipulating soil microbial ecology to reduce pathogen density and aggressiveness is being investigated. To date, innate resistance of apple rootstocks as a means to control this disease has not been carefully explored, partly due to the complex etiology and the difficulty in phenotyping the disease resistance. Molecular defense responses of plant roots to soilborne necrotrophic pathogens are largely elusive, although considerable progress has been achieved using foliar disease systems. Plant defense responses to necrotrophic pathogens consist of several interacting modules and operate as a network. Upon pathogen detection by plants, cellular signals such as the oscillation of Ca(2+) concentration, reactive oxygen species (ROS) burst and protein kinase activity, lead to plant hormone biosynthesis and signaling. Jasmonic acid (JA) and ethylene (ET) are known to be fundamental to the induction and regulation of defense mechanisms toward invading necrotrophic pathogens. Complicated hormone crosstalk modulates the fine-tuning of transcriptional reprogramming and metabolic redirection, resulting in production of antimicrobial metabolites, enzyme inhibitors and cell wall refortification to restrict further pathogenesis. Transcriptome profiling of apple roots in response to inoculation with Pythium ultimum demonstrated that there is a high degree of conservation regarding the molecular framework of defense responses compared with those observed with foliar tissues. It is conceivable that the timing and intensity of genotype-specific defense responses may lead to different outcomes between rootstocks in response to invasion by necrotrophic pathogens. Elucidation of host defense mechanisms is critical in developing molecular tools for genomics-assisted breeding of resistant apple rootstocks. Due to their perennial nature, use of resistant rootstocks as a component for disease management might offer a durable and cost-effective benefit to tree performance than the standard practice of soil fumigation for control of ARD.

Expression quantitative trait loci infer the regulation of isoflavone accumulation in soybean (Glycine max L. Merr.) seed

BACKGROUND

Mapping expression quantitative trait loci (eQTL) of targeted genes represents a powerful and widely adopted approach to identify putative regulatory variants. Linking regulation differences to specific genes might assist in the identification of networks and interactions. The objective of this study is to identify eQTL underlying expression of four gene families encoding isoflavone synthetic enzymes involved in the phenylpropanoid pathway, which are phenylalanine ammonia-lyase (PAL; EC 4.3.1.5), chalcone synthase (CHS; EC 2.3.1.74), 2-hydroxyisoflavanone synthase (IFS; EC1.14.13.136) and flavanone 3-hydroxylase (F3H; EC 1.14.11.9). A population of 130 recombinant inbred lines (F5:11), derived from a cross between soybean cultivar 'Zhongdou 27' (high isoflavone) and 'Jiunong 20' (low isoflavone), and a total of 194 simple sequence repeat (SSR) markers were used in this study. Overlapped loci of eQTLs and phenotypic QTLs (pQTLs) were analyzed to identify the potential candidate genes underlying the accumulation of isoflavone in soybean seed.

RESULTS

Thirty three eQTLs (thirteen cis-eQTLs and twenty trans-eQTLs) underlying the transcript abundance of the four gene families were identified on fifteen chromosomes. The eQTLs between Satt278-Sat_134, Sat_134-Sct_010 and Satt149-Sat_234 underlie the expression of both IFS and CHS genes. Five eQTL intervals were overlapped with pQTLs. A total of eleven candidate genes within the overlapped eQTL and pQTL were identified.

CONCLUSIONS

These results will be useful for the development of marker-assisted selection to breed soybean cultivars with high or low isoflavone contents and for map-based cloning of new isoflavone related genes.

Genetical and comparative genomics of Brassica under altered Ca supply identifies Arabidopsis Ca-transporter orthologs

Although Ca transport in plants is highly complex, the overexpression of vacuolar Ca(2+) transporters in crops is a promising new technology to improve dietary Ca supplies through biofortification. Here, we sought to identify novel targets for increasing plant Ca accumulation using genetical and comparative genomics. Expression quantitative trait locus (eQTL) mapping to 1895 cis- and 8015 trans-loci were identified in shoots of an inbred mapping population of Brassica rapa (IMB211 × R500); 23 cis- and 948 trans-eQTLs responded specifically to altered Ca supply. eQTLs were screened for functional significance using a large database of shoot Ca concentration phenotypes of Arabidopsis thaliana. From 31 Arabidopsis gene identifiers tagged to robust shoot Ca concentration phenotypes, 21 mapped to 27 B. rapa eQTLs, including orthologs of the Ca(2+) transporters At-CAX1 and At-ACA8. Two of three independent missense mutants of BraA.cax1a, isolated previously by targeting induced local lesions in genomes, have allele-specific shoot Ca concentration phenotypes compared with their segregating wild types. BraA.CAX1a is a promising target for altering the Ca composition of Brassica, consistent with prior knowledge from Arabidopsis. We conclude that multiple-environment eQTL analysis of complex crop genomes combined with comparative genomics is a powerful technique for novel gene identification/prioritization.

Genetic architecture of ethanol-responsive transcriptome variation in Saccharomyces cerevisiae strains

Natural variation in gene expression is pervasive within and between species, and it likely explains a significant fraction of phenotypic variation between individuals. Phenotypic variation in acute systemic responses can also be leveraged to reveal physiological differences in how individuals perceive and respond to environmental perturbations. We previously found extensive variation in the transcriptomic response to acute ethanol exposure in two wild isolates and a common laboratory strain of Saccharomyces cerevisiae. Many expression differences persisted across several modules of coregulated genes, implicating trans-acting systemic differences in ethanol sensing and/or response. Here, we conducted expression QTL mapping of the ethanol response in two strain crosses to identify the genetic basis for these differences. To understand systemic differences, we focused on "hotspot" loci that affect many transcripts in trans. Candidate causal regulators contained within hotspots implicate upstream regulators as well as downstream effectors of the ethanol response. Overlap in hotspot targets revealed additive genetic effects of trans-acting loci as well as "epi-hotspots," in which epistatic interactions between two loci affected the same suites of downstream targets. One epi-hotspot implicated interactions between Mkt1p and proteins linked to translational regulation, prompting us to show that Mkt1p localizes to P bodies upon ethanol stress in a strain-specific manner. Our results provide a glimpse into the genetic architecture underlying natural variation in a stress response and present new details on how yeast respond to ethanol stress.

Deciphering gamma-decalactone biosynthesis in strawberry fruit using a combination of genetic mapping, RNA-Seq and eQTL analyses

BACKGROUND

Understanding the basis for volatile organic compound (VOC) biosynthesis and regulation is of great importance for the genetic improvement of fruit flavor. Lactones constitute an essential group of fatty acid-derived VOCs conferring peach-like aroma to a number of fruits including peach, plum, pineapple and strawberry. Early studies on lactone biosynthesis suggest that several enzymatic pathways could be responsible for the diversity of lactones, but detailed information on them remained elusive. In this study, we have integrated genetic mapping and genome-wide transcriptome analysis to investigate the molecular basis of natural variation in γ-decalactone content in strawberry fruit.

RESULTS

As a result, the fatty acid desaturase FaFAD1 was identified as the gene underlying the locus at LGIII-2 that controls γ-decalactone production in ripening fruit. The FaFAD1 gene is specifically expressed in ripe fruits and its expression fully correlates with the presence of γ-decalactone in all 95 individuals of the mapping population. In addition, we show that the level of expression of FaFAH1, with similarity to cytochrome p450 hydroxylases, significantly correlates with the content of γ-decalactone in the mapping population. The analysis of expression quantitative trait loci (eQTL) suggests that the product of this gene also has a regulatory role in the biosynthetic pathway of lactones.

CONCLUSIONS

Altogether, this study provides mechanistic information of how the production of γ-decalactone is naturally controlled in strawberry, and proposes enzymatic activities necessary for the formation of this VOC in plants.

Genome-wide association studies in Sjögren's syndrome: What do the genes tell us about disease pathogenesis?

The pathogenesis of Sjögren's syndrome (SS) likely involves complex interactions between genes and the environment. While the candidate gene approach has been previously used to identify several genes associated with SS, two recent large-scale genome-wide association studies (GWAS) have implicated many more loci as genetic risk factors. Of particular relevance, was the significant association of SS with additional immune-related genes including IL12A, BLK, and CXCR5. GWAS has also uncovered other loci and suggestive gene associations in SS, but none are related to genes encoding salivary or lacrimal components, secretion machinery and neuronal proteins involved in innervations of the glands, respectively. In this review, we discuss these genetic findings with particular attention paid to the genes identified, the strength of associations, and how the SS-associated genes compare to what has been discovered previously in systemic lupus erythematosus (SLE). We also summarize the potential impact of these associated gene products on NFκB and immune pathways and describe how this new information might be integrated further for identifying clinical subsets and understanding the pathogenesis of SS.

An expression quantitative trait loci-guided co-expression analysis for constructing regulatory network using a rice recombinant inbred line population

The ability to reveal the regulatory architecture of genes at the whole-genome level by constructing a regulatory network is critical for understanding the biological processes and developmental programmes of organisms. Here, we conducted an eQTL-guided function-related co-expression analysis to identify the putative regulators and construct gene regulatory network. We performed an eQTL analysis of 210 recombinant inbred lines (RILs) derived from a cross between two indica rice lines, Zhenshan 97 and Minghui 63, the parents of an elite hybrid, using data obtained by hybridizing RNA samples of flag leaves at the heading stage with Affymetrix whole-genome arrays. Making use of an ultrahigh-density single-nucleotide polymorphism bin map constructed by population sequencing, 13 647 eQTLs for 10 725 e-traits were detected, comprising 5079 cis-eQTLs (37.2%) and 8568 trans-eQTLs (62.8%). The analysis revealed 138 trans-eQTLs hotspots, each of which apparently regulates the expression variations of many genes. Co-expression analysis of functionally related genes within the framework of regulator-target relationships outlined by the eQTLs led to the identification of putative regulators in the system. The usefulness of the strategy was demonstrated with the genes known to be involved in flowering. We also applied this strategy to the analysis of QTLs for yield traits, which also suggested likely candidate genes. eQTL-guided co-expression analysis may provide a promising solution for outlining a framework for the complex regulatory network of an organism.

Genome-wide discovery and characterization of maize long non-coding RNAs

BACKGROUND

Long non-coding RNAs (lncRNAs) are transcripts that are 200 bp or longer, do not encode proteins, and potentially play important roles in eukaryotic gene regulation. However, the number, characteristics and expression inheritance pattern of lncRNAs in maize are still largely unknown.

RESULTS

By exploiting available public EST databases, maize whole genome sequence annotation and RNA-seq datasets from 30 different experiments, we identified 20,163 putative lncRNAs. Of these lncRNAs, more than 90% are predicted to be the precursors of small RNAs, while 1,704 are considered to be high-confidence lncRNAs. High confidence lncRNAs have an average transcript length of 463 bp and genes encoding them contain fewer exons than annotated genes. By analyzing the expression pattern of these lncRNAs in 13 distinct tissues and 105 maize recombinant inbred lines, we show that more than 50% of the high confidence lncRNAs are expressed in a tissue-specific manner, a result that is supported by epigenetic marks. Intriguingly, the inheritance of lncRNA expression patterns in 105 recombinant inbred lines reveals apparent transgressive segregation, and maize lncRNAs are less affected by cis- than by trans-genetic factors.

CONCLUSIONS

We integrate all available transcriptomic datasets to identify a comprehensive set of maize lncRNAs, provide a unique annotation resource of the maize genome and a genome-wide characterization of maize lncRNAs, and explore the genetic control of their expression using expression quantitative trait locus mapping.

Genomewide discovery of DNA polymorphisms in rice cultivars with contrasting drought and salinity stress response and their functional relevance

Next-generation sequencing technologies provide opportunities to understand the genetic basis of phenotypic differences, such as abiotic stress response, even in the closely related cultivars via identification of large number of DNA polymorphisms. We performed whole-genome resequencing of three rice cultivars with contrasting responses to drought and salinity stress (sensitive IR64, drought-tolerant Nagina 22 and salinity-tolerant Pokkali). More than 356 million 90-bp paired-end reads were generated, which provided about 85% coverage of the rice genome. Applying stringent parameters, we identified a total of 1 784 583 nonredundant single-nucleotide polymorphisms (SNPs) and 154 275 InDels between reference (Nipponbare) and the three resequenced cultivars. We detected 401 683 and 662 509 SNPs between IR64 and Pokkali, and IR64 and N22 cultivars, respectively. The distribution of DNA polymorphisms was found to be uneven across and within the rice chromosomes. One-fourth of the SNPs and InDels were detected in genic regions, and about 3.5% of the total SNPs resulted in nonsynonymous changes. Large-effect SNPs and InDels, which affect the integrity of the encoded protein, were also identified. Further, we identified DNA polymorphisms present in the differentially expressed genes within the known quantitative trait loci. Among these, a total of 548 SNPs in 232 genes, located in the conserved functional domains, were identified. The data presented in this study provide functional markers and promising target genes for salinity and drought tolerance and present a valuable resource for high-throughput genotyping and molecular breeding for abiotic stress traits in rice.

The AT-hook motif-encoding gene METABOLIC NETWORK MODULATOR 1 underlies natural variation in Arabidopsis primary metabolism

Regulation of primary metabolism is a central mechanism by which plants coordinate their various responses to biotic and abiotic challenge. To identify genes responsible for natural variation in primary metabolism, we focused on cloning a locus from Arabidopsis thaliana that influences the level of TCA cycle metabolites in planta. We found that the Met.V.67 locus was controlled by natural variation in METABOLIC NETWORK MODULATOR 1 (MNM1), which encoded an AT-hook motif-containing protein that was unique to the Brassicales lineage. MNM1 had wide ranging effects on plant metabolism and displayed a tissue expression pattern that was suggestive of a function in sink tissues. Natural variation within MNM1 had differential effects during a diurnal time course, and this temporal dependency was supported by analysis of T-DNA insertion and over-expression lines for MNM1. Thus, the cloning of a natural variation locus specifically associated with primary metabolism allowed us to identify MNM1 as a lineage-specific modulator of primary metabolism, suggesting that the regulation of primary metabolism can change during evolution.