Identification of four novel QTL linked to the metabolic syndrome in the Berlin Fat Mouse.

BACKGROUND: The Berlin Fat Mouse Inbred line (BFMI) is a model for obesity and the metabolic syndrome. This study aimed to identify genetic variants associated with impaired glucose metabolism using the obese lines BFMI861-S1 and BFMI861-S2, which are genetically closely related, but differ in several traits. BFMI861-S1 is insulin resistant and stores ectopic fat in the liver, whereas BFMI861-S2 is insulin sensitive. METHODS: In generation 10, 397 males of an advanced intercross line (AIL) BFMI861-S1 × BFMI861-S2 were challenged with a high-fat, high-carbohydrate diet and phenotyped over 25 weeks. QTL-analysis was performed after selective genotyping of 200 mice using the GigaMUGA Genotyping Array. Additional 197 males were genotyped for 7 top SNPs in QTL regions. For the prioritization of positional candidate genes whole genome sequencing and gene expression data of the parental lines were used. RESULTS: Overlapping QTL for gonadal adipose tissue weight and blood glucose concentration were detected on chromosome (Chr) 3 (95.8-100.1 Mb), and for gonadal adipose tissue weight, liver weight, and blood glucose concentration on Chr 17 (9.5-26.1 Mb). Causal modeling suggested for Chr 3-QTL direct effects on adipose tissue weight, but indirect effects on blood glucose concentration. Direct effects on adipose tissue weight, liver weight, and blood glucose concentration were suggested for Chr 17-QTL. Prioritized positional candidate genes for the identified QTL were Notch2 and Fmo5 (Chr 3) and Plg and Acat2 (Chr 17). Two additional QTL were detected for gonadal adipose tissue weight on Chr 15 (67.9-74.6 Mb) and for body weight on Chr 16 (3.9-21.4 Mb). CONCLUSIONS: QTL mapping together with a detailed prioritization approach allowed us to identify candidate genes associated with traits of the metabolic syndrome. In addition, we provided evidence for direct and indirect genetic effects on blood glucose concentration in the insulin-resistant mouse line BFMI861-S1.

Identification of consistent QTL for time to maturation in Virginia-type Peanut (Arachis hypogaea L.).

BACKGROUND: Time-to-maturation (TTM) is an important trait contributing to adaptability, yield and quality in peanut (Arachis hypogaea L). Virginia market-type peanut belongs to the late-maturing A. hypogaea subspecies with considerable variation in TTM within this market type. Consequently, planting and harvesting schedule of peanut cultivars, including Virginia market-type, need to be optimized to maximize yield and grade. Little is known regarding the genetic control of TTM in peanut due to the challenge of phenotyping and limited DNA polymorphism. Here, we investigated the genetic control of TTM within the Virginia market-type peanut using a SNP-based high-density genetic map. A recombinant inbred line (RIL) population, derived from a cross between two Virginia-type cultivars 'Hanoch' and 'Harari' with contrasting TTM (12-15 days on multi-years observations), was phenotyped in the field for 2 years following a randomized complete block design. TTM was estimated by maturity index (MI). Other agronomic traits like harvest index (HI), branching habit (BH) and shelling percentage (SP) were recorded as well. RESULTS: MI was highly segregated in the population, with 13.3-70.9% and 28.4-80.2% in years 2018 and 2019. The constructed genetic map included 1833 SNP markers distributed on 24 linkage groups, covering a total map distance of 1773.5 cM corresponding to 20 chromosomes on the tetraploid peanut genome with 1.6 cM mean distance between the adjacent markers. Thirty QTL were identified for all measured traits. Among the four QTL regions for MI, two consistent QTL regions (qMIA04a,b and qMIB03a,b) were identified on chromosomes A04 (118680323-125,599,371; 6.9Mbp) and B03 (2839591-4,674,238; 1.8Mbp), with LOD values of 5.33-6.45 and 5-5.35 which explained phenotypic variation of 9.9-11.9% and 9.3-9.9%, respectively. QTL for HI were found to share the same loci as MI on chromosomes B03, B05, and B06, demonstrating the possible pleiotropic effect of HI on TTM. Significant but smaller effects on MI were detected for BH, pod yield and SP. CONCLUSIONS: This study identified consistent QTL regions conditioning TTM for Virginia market-type peanut. The information and materials generated here can be used to further develop molecular markers to select peanut idiotypes suitable for diverse growth environments.

Rumen metaproteomics: Closer to linking rumen microbial function to animal productivity traits.

The rumen microbiome constitutes a dense and complex mixture of anaerobic bacteria, archaea, protozoa, virus and fungi. Collectively, rumen microbial populations interact closely in order to degrade and ferment complex plant material into nutrients for host metabolism, a process which also produces other by-products, such as methane gas. Our understanding of the rumen microbiome and its functions are of both scientific and industrial interest, as the metabolic functions are connected to animal health and nutrition, but at the same time contribute significantly to global greenhouse gas emissions. While many of the major microbial members of the rumen microbiome are acknowledged, advances in modern culture-independent meta-omic techniques, such as metaproteomics, enable deep exploration into active microbial populations involved in essential rumen metabolic functions. Meaningful and accurate metaproteomic analyses are highly dependent on representative samples, precise protein extraction and fractionation, as well as a comprehensive and high-quality protein sequence database that enables precise protein identification and quantification. This review focuses on the application of rumen metaproteomics, and its potential towards understanding the complex rumen microbiome and its metabolic functions. We present and discuss current methods in sample handling, protein extraction and data analysis for rumen metaproteomics, and finally emphasize the potential of (meta)genome-integrated metaproteomics for accurate reconstruction of active microbial populations in the rumen.

Reproductive tissues-specific meta-QTLs and candidate genes for development of heat-tolerant rice cultivars.

KEY MESSAGE: By integrating genetics and genomics data, reproductive tissues-specific and heat stress responsive 35 meta-QTLs and 45 candidate genes were identified, which could be exploited through marker-assisted breeding for fast-track development of heat-tolerant rice cultivars. Rice holds the key to future food security. In rice-growing areas, temperature has already reached an optimum level for growth, hence, any further increase due to global climate change could significantly reduce rice yield. Several mapping studies have identified a plethora of reproductive tissue-specific and heat stress associated inconsistent quantitative trait loci (QTL), which could be exploited for improvement of heat tolerance. In this study, we performed a meta-analysis on previously reported QTLs and identified 35 most consistent meta-QTLs (MQTLs) across diverse genetic backgrounds and environments. Genetic and physical intervals of nearly 66% MQTLs were narrower than 5 cM and 2 Mb respectively, indicating hotspot genomic regions for heat tolerance. Comparative analyses of MQTLs underlying genes with microarray and RNA-seq based transcriptomic data sets revealed a core set of 45 heat-responsive genes, among which 24 were reproductive tissue-specific and have not been studied in detail before. Remarkably, all these genes corresponded to various stress associated functions, ranging from abiotic stress sensing to regulating plant stress responses, and included heat-shock genes (OsBiP2, OsMed37_1), transcription factors (OsNAS3, OsTEF1, OsWRKY10, OsWRKY21), transmembrane transporters (OsAAP7A, OsAMT2;1), sugar metabolizing (OsSUS4, α-Gal III) and abiotic stress (OsRCI2-7, SRWD1) genes. Functional data evidences from Arabidopsis heat-shock genes also suggest that OsBIP2 may be associated with thermotolerance of pollen tubes under heat stress conditions. Furthermore, promoters of identified genes were enriched with heat, dehydration, pollen and sugar responsive cis-acting regulatory elements, proposing a common regulatory mechanism might exist in rice for mitigating reproductive stage heat stress. These findings strongly support our results and provide new candidate genes for fast-track development of heat-tolerant rice cultivars.

A trans-eQTL network regulates osteoclast multinucleation and bone mass.

Functional characterisation of cell-type-specific regulatory networks is key to establish a causal link between genetic variation and phenotype. The osteoclast offers a unique model for interrogating the contribution of co-regulated genes to in vivo phenotype as its multinucleation and resorption activities determine quantifiable skeletal traits. Here we took advantage of a trans-regulated gene network (MMnet, macrophage multinucleation network) which we found to be significantly enriched for GWAS variants associated with bone-related phenotypes. We found that the network hub gene Bcat1 and seven other co-regulated MMnet genes out of 13, regulate bone function. Specifically, global (Pik3cb-/-, Atp8b2+/-, Igsf8-/-, Eml1-/-, Appl2-/-, Deptor-/-) and myeloid-specific Slc40a1 knockout mice displayed abnormal bone phenotypes. We report opposing effects of MMnet genes on bone mass in mice and osteoclast multinucleation/resorption in humans with strong correlation between the two. These results identify MMnet as a functionally conserved network that regulates osteoclast multinucleation and bone mass.

Recent insights into barley and Rhynchosporium commune interactions.

Rhynchosporium commune is the causal pathogen of scald in barley (Hordeum vulgare), a foliar disease that can reduce yield by up to 40% in susceptible cultivars. R. commune is found worldwide in all temperate growing regions and is regarded as one of the most economically important barley pathogens. It is a polycyclic pathogen with the ability to rapidly evolve new virulent strains in response to resistance genes deployed in commercial cultivars. Hence, introgression and pyramiding of different loci for resistance (qualitative or quantitative) through marker-assisted selection is an effective way to improve scald resistance in barley. This review summarizes all 148 resistance quantitative trait loci reported at the date of submission of this review and projects them onto the barley physical map, where it is clear many loci co-locate on chromosomes 3H and 7H. We have summarized the major named resistance loci and reiterated the renaming of Rrs15 (CI8288) to Rrs17. This review provides a comprehensive resource for future discovery and breeding efforts of qualitative and quantitative scald resistance loci.

3D interactions with the growth hormone locus in cellular signalling and cancer-related pathways.

Growth hormone (GH) is a peptide hormone predominantly produced by the anterior pituitary and is essential for normal growth and metabolism. The GH locus contains five evolutionarily related genes under the control of an upstream locus control region that coordinates tissue-specific expression of these genes. Compromised GH signalling and genetic variation in these genes has been implicated in various disorders including cancer. We hypothesised that regulatory regions within the GH locus coordinate expression of a gene network that extends the impact of the GH locus control region. We used the CoDeS3D algorithm to analyse 529 common single nucleotide polymorphisms (SNPs) across the GH locus. This algorithm identifies colocalised Hi-C and eQTL associations to determine which SNPs are associated with a change in gene expression at loci that physically interact within the nucleus. One hundred and eighty-one common SNPs were identified that interacted with 292 eGenes across 48 different tissues. One hundred and forty-five eGenes were regulated in trans. eGenes were found to be enriched in GH/GHR-related cellular signalling pathways including MAPK, PI3K-AKT-mTOR, ERBB and insulin signalling, suggesting that these pathways may be co-regulated with GH signalling. Enrichment was also observed in the Wnt and Hippo signalling pathways and in pathways associated with hepatocellular, colorectal, breast and non-small cell lung carcinoma. Thirty-three eQTL SNPs identified in our study were found to be of regulatory importance in a genome-wide Survey of Regulatory Elements reporter screen. Our data suggest that the GH locus functions as a complex regulatory region that coordinates expression of numerous genes in cis and trans, many of which may be involved in modulating GH function in normal and disease states.

Paternal inheritance of diet induced metabolic traits correlates with germline regulation of diet induced coding gene expression.

Inheritance of induced traits through the germline is poorly understood and controversial. The ideal evidence correlating induced and inherited traits with germline gene expression remains largely obscure. Using a Drosophila coding transcriptome level model of paternal high sugar diet induced alterations in triglyceride levels across generations, in conjunction with pre-existing data, we show here highly significant overlap of differentially expressed genes between the ancestral generation, the resulting sperm and embryos, and the future generation individuals. Further, gene ontology and literature-wide overrepresentation analysis reveal association of lipid and carbohydrate metabolism, and immune response, besides others, with differentially expressed genes in the above samples. Analysis of available mouse data on inheritance of diet induced metabolic traits also revealed a similar correlation. Our results support a causal role of sperm borne mRNAs in inheritance of acquired characteristics, consistent with the evidence that these mRNAs are delivered to the oocyte and influence embryonic development.

Designing a QTL Mapping Study for Implementation in the Realized Collaborative Cross Genetic Reference Population.

The Collaborative Cross (CC) mouse resource is a next-generation mouse genetic reference population (GRP) designed for high-resolution mapping of quantitative trait loci (QTL) of large effect affecting complex traits during health and disease. The CC resource consists of a set of 72 recombinant inbred lines (RILs) generated by reciprocal crossing of five classical and three wild-derived mouse founder strains. Complex traits are controlled by variations within multiple genes and environmental factors, and their mutual interactions. These traits are observed at multiple levels of the animals' systems, including metabolism, body weight, immune profile, and susceptibility or resistance to the development and progress of infectious or chronic diseases. Herein, we present general guidelines for design of QTL mapping experiments using the CC resource-along with full step-by-step protocols and methods that were implemented in our lab for the phenotypic and genotypic characterization of the different CC lines-for mapping the genes underlying host response to infectious and chronic diseases. © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: CC lines for whole body mass index (BMI) Basic Protocol 2: A detailed assessment of the power to detect effect sizes based on the number of lines used, and the number of replicates per line Basic Protocol 3: Obtaining power for QTL with given target effect by interpolating in Table 1 of Keele et al. (2019).

Genome-wide association and differential expression analysis of salt tolerance in Gossypium hirsutum L at the germination stage.

BACKGROUND: Salinity is a major abiotic stress seriously hindering crop yield. Development and utilization of tolerant varieties is the most economical way to address soil salinity. Upland cotton is a major fiber crop and pioneer plant on saline soil and thus its genetic architecture underlying salt tolerance should be extensively explored. RESULTS: In this study, genome-wide association analysis and RNA sequencing were employed to detect salt-tolerant qualitative-trait loci (QTLs) and candidate genes in 196 upland cotton genotypes at the germination stage. Using comprehensive evaluation values of salt tolerance in four environments, we identified 33 significant single-nucleotide polymorphisms (SNPs), including 17 and 7 SNPs under at least two and four environments, respectively. The 17 stable SNPs were located within or near 98 candidate genes in 13 QTLs, including 35 genes that were functionally annotated to be involved in salt stress responses. RNA-seq analysis indicated that among the 98 candidate genes, 13 were stably differentially expressed. Furthermore, 12 of the 13 candidate genes were verified by qRT-PCR. RNA-seq analysis detected 6640, 3878, and 6462 differentially expressed genes at three sampling time points, of which 869 were shared. CONCLUSIONS: These results, including the elite cotton accessions with accurate salt tolerance evaluation, the significant SNP markers, the candidate genes, and the salt-tolerant pathways, could improve our understanding of the molecular regulatory mechanisms under salt stress tolerance and genetic manipulation for cotton improvement.

Identification of heat-tolerance QTLs and high-temperature stress-responsive genes through conventional QTL mapping, QTL-seq and RNA-seq in tomato.

BACKGROUND: High temperature is one of the major abiotic stresses in tomato and greatly reduces fruit yield and quality. Identifying high-temperature stress-responsive (HSR) genes and breeding heat-tolerant varieties is an effective way to address this issue. However, there are few reports on the fine mapping of heat-tolerance quantitative trait locus (QTL) and the identification of HSR genes in tomato. Here, we applied three heat tolerance-related physiological indexes, namely, relative electrical conductivity (REC), chlorophyll content (CC) and maximum photochemical quantum efficiency (Fv/Fm) of PSII (photosystem II), as well as the phenotypic index, the heat injury index (HII), and conventional QTL analysis combined with QTL-seq technology to comprehensively detect heat-tolerance QTLs in tomato seedlings. In addition, we integrated the QTL mapping results with RNA-seq to identify key HSR genes within the major QTLs. RESULTS: A total of five major QTLs were detected: qHII-1-1, qHII-1-2, qHII-1-3, qHII-2-1 and qCC-1-5 (qREC-1-3). qHII-1-1, qHII-1-2 and qHII-1-3 were located, respectively, in the intervals of 1.43, 1.17 and 1.19 Mb on chromosome 1, while the interval of qHII-2-1 was located in the intervals of 1.87 Mb on chromosome 2. The locations observed with conventional QTL mapping and QTL-seq were consistent. qCC-1-5 and qREC-1-3 for CC and REC, respectively, were located at the same position by conventional QTL mapping. Although qCC-1-5 was not detected in QTL-seq analysis, its phenotypic variation (16.48%) and positive additive effect (0.22) were the highest among all heat tolerance QTLs. To investigate the genes involved in heat tolerance within the major QTLs in tomato, RNA-seq analysis was performed, and four candidate genes (SlCathB2, SlGST, SlUBC5, and SlARG1) associated with heat tolerance were finally detected within the major QTLs by DEG analysis, qRT-PCR screening and biological function analysis. CONCLUSIONS: In conclusion, this study demonstrated that the combination of conventional QTL mapping, QTL-seq analysis and RNA-seq can rapidly identify candidate genes within major QTLs for a complex trait of interest to replace the fine-mapping process, thus greatly shortening the breeding process and improving breeding efficiency. The results have important applications for the fine mapping and identification of HSR genes and breeding for improved thermotolerance.

QTL × environment interactions underlie adaptive divergence in switchgrass across a large latitudinal gradient.

Local adaptation is the process by which natural selection drives adaptive phenotypic divergence across environmental gradients. Theory suggests that local adaptation results from genetic trade-offs at individual genetic loci, where adaptation to one set of environmental conditions results in a cost to fitness in alternative environments. However, the degree to which there are costs associated with local adaptation is poorly understood because most of these experiments rely on two-site reciprocal transplant experiments. Here, we quantify the benefits and costs of locally adaptive loci across 17° of latitude in a four-grandparent outbred mapping population in outcrossing switchgrass (Panicum virgatum L.), an emerging biofuel crop and dominant tallgrass species. We conducted quantitative trait locus (QTL) mapping across 10 sites, ranging from Texas to South Dakota. This analysis revealed that beneficial biomass (fitness) QTL generally incur minimal costs when transplanted to other field sites distributed over a large climatic gradient over the 2 y of our study. Therefore, locally advantageous alleles could potentially be combined across multiple loci through breeding to create high-yielding regionally adapted cultivars.

Accelerated flowering time reduces lifetime water use without penalizing reproductive performance in Arabidopsis.

Natural selection driven by water availability has resulted in considerable variation for traits associated with drought tolerance and leaf-level water-use efficiency (WUE). In Arabidopsis, little is known about the variation of whole-plant water use (PWU) and whole-plant WUE (transpiration efficiency). To investigate the genetic basis of PWU, we developed a novel proxy trait by combining flowering time and rosette water use to estimate lifetime PWU. We validated its usefulness for large-scale screening of mapping populations in a subset of ecotypes. This parameter subsequently facilitated the screening of water use and drought tolerance traits in a recombinant inbred line population derived from two Arabidopsis accessions with distinct water-use strategies, namely, C24 (low PWU) and Col-0 (high PWU). Subsequent quantitative trait loci mapping and validation through near-isogenic lines identified two causal quantitative trait loci, which showed that a combination of weak and nonfunctional alleles of the FRIGIDA (FRI) and FLOWERING LOCUS C (FLC) genes substantially reduced plant water use due to their control of flowering time. Crucially, we observed that reducing flowering time and consequently water use did not penalize reproductive performance, as such water productivity (seed produced per unit of water transpired) improved. Natural polymorphisms of FRI and FLC have previously been elucidated as key determinants of natural variation in intrinsic WUE (δ13 C). However, in the genetic backgrounds tested here, drought tolerance traits, stomatal conductance, δ13 C. and rosette water use were independent of allelic variation at FRI and FLC, suggesting that flowering is critical in determining lifetime PWU but not always leaf-level traits.

Mapping of QTL for chicken body weight, carcass composition, and meat quality traits in a slow-growing line.

Slow-growing chicken lines are valuable genetic resources for the development of well-perceived alternative free-range production. While there is no constraint on increasing growth rate, breeding programs have to evolve in order to include new traits improving the positioning of such lines in the growing market for parts and processed products. In this study, we used dense genotyping to fine map QTL for chicken growth, body composition, and meat quality traits in view of developing new tools for selection of a slow-growing line. The dataset included a total of 836 birds (10 sires, 87 dams, 739 descendants) and 40,203 SNP. QTL for the 15 traits analyzed were detected by 3 different methods, i.e., linkage and linkage disequilibrium haplotype-based analysis (LDLA), family-based single marker association (FASTA), and Bayesian multi-marker regression (Bayes Cπ). After filtering for QTL redundancy, we found 16, 16, and 9 QTL when using the FASTA, LDLA, and Bayes Cπ methods, respectively, with a threshold of 2.49 × 10-5 for FASTA and LDLA, and a Bayes factor of 150 for the Bayes Cπ analysis. They comprised 17 QTL for body weight, 9 QTL for body composition, and 15 QTL for breast meat quality or behavior at slaughter. The 3 methods agreed in the detection of highly significant QTL such as that detected on GGA24 for body weight at 3, 6, and 9 wk, and the 2 QTL detected on GGA17 and GGA18 for breast meat yield. Several significant QTL were also detected for the different components of breast meat quality. This study provided new locations for investigation in order to improve our understanding of the genetic architecture of growth, carcass composition, and meat quality in the chicken and to develop molecular tools for the selection of these traits in a slow-growing line.

Genome-wide association study of callus induction variation to explore the callus formation mechanism of rice.

Rice (Oryza sativa) is one of the most widely cultivated food crops, worldwide. Tissue culture is extensively used in rice breeding and functional genome research. The ability to induce callus determines whether a particular rice variety can be subjected to tissue culture and Agrobacterium-mediated transformation. Over the past two decades, many quantitative trait loci (QTLs) related to callus induction traits have been identified; however, individual genes associated with rice callus induction have not been reported. In this study, we characterized three callus-induction traits in a global collection of 510 rice accessions. A genome-wide association study of the rice population in its entirety as well as subpopulations revealed 21 significant loci located in rice callus induction QTLs. We identified three candidate callus induction genes, namely CRL1, OsBMM1, and OsSET1, which are orthologs of Arabidopsis LBD17/LBD29, BBM, and SWN, respectively, which are known to affect callus formation. Furthermore, we predicted that 14 candidate genes might be involved in rice callus induction and showed that RNA interference (RNAi)-mediated disruption of OsIAA10 inhibited callus formation on tissue culture medium. Embryo growth in the OsIAA10 RNAi line was not inhibited by synthetic auxin (2,4-D) treatment, suggesting that OsIAA10 may perceive auxin and activate the expression of downstream genes, such as CRL1, to induce callus formation. The significant loci and candidate genes identified here may provide insight into the mechanism underlying callus formation in rice.

QTL and QTL networks for cold tolerance at the reproductive stage detected using selective introgression in rice.

Low temperature stress is one of the major abiotic stresses limiting the productivity of Geng (japonica) rice grown the temperate regions as well as in tropical high lands worldwide. To develop rice varieties with improved cold tolerance (CT) at the reproductive stage, 84 BC2 CT introgression lines (ILs) were developed from five populations through backcross breeding. These CT ILs plus 310 random ILs from the same BC populations were used for dissecting genetic networks underlying CT in rice by detecting QTLs and functional genetic units (FGUs) contributing to CT. Seventeen major QTLs for CT were identified using five selective introgression populations and the method of segregation distortion. Of them, three QTLs were confirmed using the random populations and seven others locate in the regions with previously reported CT QTLs/genes. Using multi-locus probability tests and linkage disequilibrium (LD) analyses, 46 functional genetic units (FGUs) (37 single loci and 9 association groups or AGs) distributed in 37 bins (~20%) across the rice genome for CT were detected. Together, each of the CT loci (bins) was detected in 1.7 populations, including 18 loci detected in two or more populations. Putative genetic networks (multi-locus structures) underlying CT were constructed based on strong non-random associations between or among donor alleles at the unlinked CT loci/FGUs identified in the CT ILs, suggesting the presence of strong epistasis among the detected CT loci. Our results demonstrated the power and usefulness of using selective introgression for simultaneous improvement and genetic dissection of complex traits such as CT in rice.

Natural variation at qHd1 affects heading date acceleration at high temperatures with pleiotropism for yield traits in rice.

BACKGROUND: Rice is highly sensitive to temperature fluctuations. Recently, the frequent occurrence of high temperature stress has heavily influenced rice production. Proper heading date in specific environmental conditions could ensure high grain yield. Rice heading greatly depends on the accurate measurement of environmental changes, particularly in day length and temperature. In contrary to the detailed understanding of the photoperiod pathway, little has been known about how temperature regulates the genetic control of rice heading. RESULTS: Near isogenic lines that were segregated for qHd1, were developed from a cross between indica rice varieties Zhenshan 97 (ZS97) and Milyang 46 (MY46). Using a five sowing-date experiment in the paddy field, we observed the involvement of qHd1 in temperature responses. With the gradual increase of temperature from Trial I to V, heading date of MY46 homozygotes continued to decrease for about 5 d per trial from 76 to 58 d, while that of ZS97 homozygotes was promoted at the same rate from Trial I to III and then stabilized at 69 d. This thermal response was confirmed in a temperature-gradient experiment conducted in the phytotron. It is also found that tolerance of the ZS97 allele to heading acceleration at high temperature was associated with higher grain weight that resulted in higher grain yield. Then, by qRT-PCR and RNA-seq, we found the pathway OsMADS51-Ehd1-RFT1/Hd3a underlying the qHd1-mediated floral response to temperature. By sequence comparison, OsMADS51 for qHd1 displayed a 9.5-kb insertion in the 1st intron of the ZS97 allele compared to the MY46 allele. Furthermore, this large insertion is commonly found in major early-season indica rice varieties, but not in the middle- and late-season ones, which corresponds to the requirement for high-temperature tolerance during the heading and grain-filling stages of early-season rice. CONCLUSIONS: Beneficial alleles at qHd1 confer tolerance to high temperatures at the heading and grain-filling stages, playing a significant role in the eco-geographical adaptation of early-season indica rice during modern breeding. These results, together with the underlying OsMADS51-Ehd1-RFT1/Hd3a floral pathway, provide valuable information for better understanding the molecular mechanism of temperature responsive regulation of heading date and yield traits in rice.

Interaction of maternal environment and allelic differences in seed vigour genes determines seed performance in Brassica oleracea.

Seed vigour is a key trait essential for the production of sustainable and profitable crops. The genetic basis of variation in seed vigour has recently been determined in Brassica oleracea, but the relative importance of the interaction with parental environment is unknown. We produced seeds under a range of maternal environments, including global warming scenarios. Lines were compared that had the same genetic background, but different alleles (for high and low vigour) at the quantitative trait loci responsible for determining seed vigour by altering abscisic acid (ABA) content and sensitivity. We found a consistent effect of beneficial alleles across production environments; however, environmental stress during production also had a large impact that enhanced the genetic difference in seed performance, measured as germination speed, resistance to controlled deterioration and induction of secondary dormancy. Environmental interaction with allelic differences in key genes that determine ABA content and sensitivity develops a continuity in performance from rapid germination through to failure to complete germination, and increasing depths of seed dormancy. The genetic-environmental interaction revealed provides a robust mechanism of bet-hedging to minimize environmental risk during subsequent germination, and this could have facilitated the rapid change in seed behaviour (reduced dormancy and rapid germination) observed during crop domestication.

Exploring regulation in tissues with eQTL networks.

Characterizing the collective regulatory impact of genetic variants on complex phenotypes is a major challenge in developing a genotype to phenotype map. Using expression quantitative trait locus (eQTL) analyses, we constructed bipartite networks in which edges represent significant associations between genetic variants and gene expression levels and found that the network structure informs regulatory function. We show, in 13 tissues, that these eQTL networks are organized into dense, highly modular communities grouping genes often involved in coherent biological processes. We find communities representing shared processes across tissues, as well as communities associated with tissue-specific processes that coalesce around variants in tissue-specific active chromatin regions. Node centrality is also highly informative, with the global and community hubs differing in regulatory potential and likelihood of being disease associated.

Copy number variations of CBF genes at the Fr-A2 locus are essential components of winter hardiness in wheat.

Winter hardiness is important for the adaptation of wheat to the harsh winter conditions in temperate regions and is thus also an important breeding goal. Here, we employed a panel of 407 European winter wheat cultivars to dissect the genetic architecture of winter hardiness. We show that copy number variation (CNV) of CBF (C-repeat Binding Factor) genes at the Fr-A2 locus is the essential component for winter survival, with CBF-A14 CNV being the most likely causal polymorphism, accounting for 24.3% of the genotypic variance. Genome-wide association mapping identified several markers in the Fr-A2 chromosomal region, which even after accounting for the effects of CBF-A14 copy number explained approximately 15% of the genotypic variance. This suggests that additional, as yet undiscovered, polymorphisms are present at the Fr-A2 locus. Furthermore, CNV of Vrn-A1 explained an additional 3.0% of the genotypic variance. The allele frequencies of all loci associated with winter hardiness were found to show geographic patterns consistent with their role in adaptation. Collectively, our results from the candidate gene analysis, association mapping and genome-wide prediction show that winter hardiness in wheat is a quantitative trait, but with a major contribution of the Fr-A2 locus.