PIF4 and PIF5 Transcription Factors Link Blue Light and Auxin to Regulate the Phototropic Response in Arabidopsis

Both blue light (BL) and auxin are essential for phototropism in Arabidopsis thaliana. However, the mechanisms by which light is molecularly linked to auxin during phototropism remain elusive. Here, we report that PHYTOCHROME INTERACTING FACTOR4 (PIF4) and PIF5 act downstream of the BL sensor PHOTOTROPIN1 (PHOT1) to negatively modulate phototropism in Arabidopsis. We also reveal that PIF4 and PIF5 negatively regulate auxin signaling. Furthermore, we demonstrate that PIF4 directly activates the expression of the AUXIN/INDOLE-3-ACETIC ACID (IAA) genes IAA19 and IAA29 by binding to the G-box (CACGTG) motifs in their promoters. Our genetic assays demonstrate that IAA19 and IAA29, which physically interact with AUXIN RESPONSE FACTOR7 (ARF7), are sufficient for PIF4 to negatively regulate auxin signaling and phototropism. This study identifies a key step of phototropic signaling in Arabidopsis by showing that PIF4 and PIF5 link light and auxin.     

A genome-wide association study of seed protein and oil content in soybean

Background

Association analysis is an alternative to conventional family-based methods to detect the location of gene(s) or quantitative trait loci (QTL) and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Seed protein and oil concentration are quantitative traits which are determined by the interaction among many genes with small to moderate genetic effects and their interaction with the environment. In this study, a genome-wide association study (GWAS) was performed to identify quantitative trait loci (QTL) controlling seed protein and oil concentration in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content.

Results

A total of 55,159 single nucleotide polymorphisms (SNPs) were genotyped using various methods including Illumina Infinium and GoldenGate assays and 31,954 markers with minor allele frequency >0.10 were used to estimate linkage disequilibrium (LD) in heterochromatic and euchromatic regions. In euchromatic regions, the mean LD (r ² ) rapidly declined to 0.2 within 360 Kbp, whereas the mean LD declined to 0.2 at 9,600 Kbp in heterochromatic regions. The GWAS results identified 40 SNPs in 17 different genomic regions significantly associated with seed protein. Of these, the five SNPs with the highest associations and seven adjacent SNPs were located in the 27.6-30.0 Mbp region of Gm20. A major seed protein QTL has been previously mapped to the same location and potential candidate genes have recently been identified in this region. The GWAS results also detected 25 SNPs in 13 different genomic regions associated with seed oil. Of these markers, seven SNPs had a significant association with both protein and oil.

Conclusions

This research indicated that GWAS not only identified most of the previously reported QTL controlling seed protein and oil, but also resulted in narrower genomic regions than the regions reported as containing these QTL. The narrower GWAS-defined genome regions will allow more precise marker-assisted allele selection and will expedite positional cloning of the causal gene(s).     

Use of synteny to identify candidate genes underlying QTL controlling stomatal traits in faba bean (Vicia faba L.)

Key message

We have identified QTLs for stomatal characteristics on chromosome II of faba bean by applying SNPs derived from M. truncatula , and have identified candidate genes within these QTLs using synteny between the two species.

Abstract

Faba bean (Vicia faba L.) is a valuable food and feed crop worldwide, but drought often limits its production, and its genome is large and poorly mapped. No information is available on the effects of genomic regions and genes on drought adaptation characters such as stomatal characteristics in this species, but the synteny between the sequenced model legume, Medicago truncatula, and faba bean can be used to identify candidate genes. A mapping population of 211 F₅ recombinant inbred lines (Mélodie/2 × ILB 938/2) were phenotyped to identify quantitative trait loci (QTL) affecting stomatal morphology and function, along with seed weight, under well-watered conditions in a climate-controlled glasshouse in 2013 and 2014. Canopy temperature (CT) was evaluated in 2013 under water-deficit (CTd). In total, 188 polymorphic single nucleotide polymorphisms (SNPs), developed from M. truncatula genome data, were assigned to nine linkage groups that covered ~928 cM of the faba bean genome with an average inter-marker distance of 5.8 cM. 15 putative QTLs were detected, of which eight (affecting stomatal density, length and conductance and CT) co-located on chromosome II, in the vicinity of a possible candidate gene—a receptor-like protein kinase found in the syntenic interval of M. truncatula chromosome IV. A ribose-phosphate pyrophosphokinase from M. truncatula chromosome V, postulated as a possible candidate gene for the QTL for CTd, was found some distance away in the same chromosome. These results demonstrate that genomic information from M. truncatula can successfully be translated to the faba bean genome.     

Quantitative trait loci mapping and genetic dissection for lint percentage in upland cotton (Gossypium hirsutum)

Lint percentage is an important character of cotton yield components and it is also correlated with cotton fibre development. In this study, we used a high lint percentage variety, Baimian1, and a low lint percentage, TM-1 genetic standard for Gossypium hirsutum, as parents to construct a mapping populations in upland cotton (G. hirsutum). A quantitative trait locus/loci (QTL) analysis of lint percentage was performed by using two mapping procedures; composite interval mapping (CIM), inclusive composite interval mapping (ICIM) and the F_2:3 populations in 2 years. Six main-effect QTL (M-QTL) for lint percentage (four significant and two suggestive) were detected in both years by CIM, and were located on chr. 3, chr. 19, chr. 26 and chr. 5/chr. 19. Of the six QTL, marker intervals and favourable gene sources of the significant M-QTL, qLP-3(2010) and qLP-3(2011) were consistent. These QTL were also detected by ICIM, and therefore, should preferentially be used for marker-assisted selection (MAS) of lint percentage. Another M-QTL, qLP-19(2010), was detected by two mapping procedures, and it could also be a candidate for MAS. We detected the interaction between two M-QTL and environment, and 11 epistatic QTL (E-QTL) and their interaction with environment by using ICIM. The study also found two EST-SSRs, NAU1187 and NAU1255, linked to M-QTL for lint percentage that could be candidate markers affecting cotton fibre development.     

Genetic dissection of seed weight by QTL analysis and detection of allelic variation in Indian and east European gene pool lines of <Emphasis Type="Italic">Brassica juncea</Emphasis>

Key message

Seed weight QTL identified in different populations were synthesized into consensus QTL which were shown to harbor candidate genes by in silico mapping. Allelic variation inferred would be useful in breeding B. juncea lines with high seed weight.

Abstract

Seed weight is an important yield influencing trait in oilseed Brassicas and is a multigenic trait. Among the oilseed Brassicas, Brassica juncea harbors the maximum phenotypic variation wherein thousand seed weight varies from around 2.0 g to more than 7.0 g. In this study, we have undertaken quantitative trait locus/quantitative trait loci (QTL) analysis of seed weight in B. juncea using four bi-parental doubled-haploid populations. These four populations were derived from six lines (three Indian and three east European lines) with parental phenotypic values for thousand seed weight ranging from 2.0 to 7.6 g in different environments. Multi-environment QTL analysis of the four populations identified a total of 65 QTL ranging from 10 to 25 in each population. Meta-analysis of these component QTL of the four populations identified six ‘consensus’ QTL (C-QTL) in A3, A7, A10 and B3 by merging 33 of the 65 component Tsw QTL from different bi-parental populations. Allelic diversity analysis of these six C-QTL showed that Indian lines, Pusajaikisan and Varuna, hold the most positive allele in all the six C-QTL. In silico mapping of candidate genes with the consensus QTL localized 11 genes known to influence seed weight in Arabidopsis thaliana and also showed conserved crucifer blocks harboring seed weight QTL between the A subgenomes of B. juncea and B. rapa. These findings pave the way for a better understanding of the genetics of seed weight in the oilseed crop B. juncea and reveal the scope available for improvement of seed weight through marker-assisted breeding.

     

Further insight into the role of <Emphasis Type="Italic">KAN1</Emphasis>, a member of <Emphasis Type="Italic">KANADI</Emphasis> transcription factor family in rice

The rice EMS-derived mutant leaf adaxialized 1 (lad1) was isolated based on its upward rolling leaf phenotype. Besides the adaxially rolled leaf, many other agronomic traits were also compromised in lad1. The rolling trait was characterized by a noticeable alteration of bulliform cells in the adaxial side of the leaves. Map-based cloning showed a single nucleotide substitution in the promoter region of the KAN1 gene in lad1 mutant. Further, over-expressing and CRISPR/cas9-edited knockdown transgenic plants confirmed that KAN1 was responsible for the mutant phenotype of lad1. Yeast two-hybrid and bimolecular fluorescence complementation assay demonstrated that KAN1 can interact with the auxin response factors ARF3, ARF7 and ARF15. Physiologically, the contents of auxin (IAA), abscisic acid (ABA), jasmonic acid (JA) and gibberellin (GA) were all significantly increased in the lad1 mutant. Moreover, the GA3 content dramatically decrease in wild-type, but increased in lad1 under IAA induction. Additionally, the expression levels of several IAA and GA biosynthesis and responsive-related genes and genes involved in leaf polarity determination were altered in lad1. Therefore, we hypothesized that KAN1/ARFs protein complexes act as auxin-dependent regulatory units that play a conserved role in leaf development.     

Association mapping of seed quality traits using the Canadian flax (Linum usitatissimum L.) core collection

Key message

The identification of stable QTL for seed quality traits by association mapping of a diverse panel of linseed accessions establishes the foundation for assisted breeding and future fine mapping in linseed.

Abstract

Linseed oil is valued for its food and non-food applications. Modifying its oil content and fatty acid (FA) profiles to meet market needs in a timely manner requires clear understanding of their quantitative trait loci (QTL) architectures, which have received little attention to date. Association mapping is an efficient approach to identify QTL in germplasm collections. In this study, we explored the quantitative nature of seed quality traits including oil content (OIL), palmitic acid, stearic acid, oleic acid, linoleic acid (LIO) linolenic acid (LIN) and iodine value in a flax core collection of 390 accessions assayed with 460 microsatellite markers. The core collection was grown in a modified augmented design at two locations over 3 years and phenotypic data for all seven traits were obtained from all six environments. Significant phenotypic diversity and moderate to high heritability for each trait (0.73–0.99) were observed. Most of the candidate QTL were stable as revealed by multivariate analyses. Nine candidate QTL were identified, varying from one for OIL to three for LIO and LIN. Candidate QTL for LIO and LIN co-localized with QTL previously identified in bi-parental populations and some mapped nearby genes known to be involved in the FA biosynthesis pathway. Fifty-eight percent of the QTL alleles were absent (private) in the Canadian cultivars suggesting that the core collection possesses QTL alleles potentially useful to improve seed quality traits. The candidate QTL identified herein will establish the foundation for future marker-assisted breeding in linseed.     

Combined use of bulked segregant analysis and microarrays reveals SNP markers pinpointing a major QTL for resistance to Phytophthora capsici in pepper

Key message

Bulked segregant analysis (BSA) using Affymetrix GeneChips revealed candidate genes underlying the major QTL for Phytophthora capsici resistance in Capsicum . Using the candidate genes, reliable markers for Phytophthora resistance were developed and validated.

Abstract

Phytophthora capsici L. is one of the most destructive pathogens of pepper (Capsicum spp.). Resistance of pepper against P. capsici is controlled by quantitative trait loci (QTL), including a major QTL on chromosome 5 that is the predominant contributor to resistance. Here, to maximize the effect of this QTL and study its underlying genes, an F₂ population and recombinant inbred lines were inoculated with P. capsici strain JHAI1-7 zoospores at a low concentration (3 × 10³/mL). Resistance phenotype segregation ratios for the populations fit a 3:1 and 1:1 (resistant:susceptible) segregation model, respectively, consistent with a single dominant gene model. Bulked segregant analysis (BSA) using Affymetrix GeneChips revealed a single position polymorphism (SPP) marker mapping to the major QTL. When this SPP marker (Phyto5SAR) together with other SNP markers located on chromosome 5 was used to confirm the position of the major QTL, Phyto5SAR showed the highest LOD value at the QTL. A scaffold sequence (scaffold194) containing Phyto5SAR was identified from the C. annuum genome database. The scaffold contained two putative NBS-LRR genes and one SAR 8.2A gene as candidates for contributing to P. capsici resistance. Markers linked to these genes were developed and validated by testing 100 F₁ commercial cultivars. Among the markers, Phyto5NBS1 showed about 90 % accuracy in predicting resistance phenotypes to a low-virulence P. capsici isolate. These results suggest that Phyto5NBS1 is a reliable marker for P. capsici resistance and can be used for identification of a gene(s) underlying the major QTL on chromosome 5.     

Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

Key message

A comprehensive linkage atlas for seed yield in rapeseed.

Abstract

Most agronomic traits of interest for crop improvement (including seed yield) are highly complex quantitative traits controlled by numerous genetic loci, which brings challenges for comprehensively capturing associated markers/genes. We propose that multiple trait interactions underlie complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual quantitative trait loci (QTL) effects more effectively and improve yield predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed a large set of trait data generated in 19 independent experiments to investigate correlations between seed yield and other complex traits, and further identified QTL in this population with a SNP-based genetic bin map. A total of 1904 consensus QTL accounting for 22 traits, including 80 QTL directly affecting seed yield, were anchored to the B. napus reference sequence. Through trait association analysis and QTL meta-analysis, we identified a total of 525 indivisible QTL that either directly or indirectly contributed to seed yield, of which 295 QTL were detected across multiple environments. A majority (81.5%) of the 525 QTL were pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting genetic effects, as well as 31 QTL with minor complementary effects. Implementation of the 525 QTL in genomic prediction models improved seed yield prediction accuracy. Dissecting the genetic and phenotypic interrelationships underlying complex quantitative traits using this method will provide valuable insights for genomics-based crop improvement.

     

Design of New Genome- and Gene-Sourced Primers and Identification of QTL for Seed Oil Content in a Specially High-Oil Brassica napus Cultivar

Rapeseed (Brassica napus L.) is one of most important oilseed crops in the world. There are now various rapeseed cultivars in nature that differ in their seed oil content because they vary in oil-content alleles and there are high-oil alleles among the high-oil rapeseed cultivars. For these experiments, we generated doubled haploid (DH) lines derived from the cross between the specially high-oil cultivar zy036 whose seed oil content is approximately 50% and the specially low-oil cultivar 51070 whose seed oil content is approximately 36%. First, to address the deficiency in polymorphic markers, we designed 5944 pairs of newly developed genome-sourced primers and 443 pairs of newly developed primers related to oil-content genes to complement the 2244 pairs of publicly available primers. Second, we constructed a new DH genetic linkage map using 527 molecular markers, consisting of 181 publicly available markers, 298 newly developed genome-sourced markers and 48 newly developed markers related to oil-content genes. The map contained 19 linkage groups, covering a total length of 2,265.54 cM with an average distance between markers of 4.30 cM. Third, we identified quantitative trait loci (QTL) for seed oil content using field data collected at three sites over 3 years, and found a total of 12 QTL. Of the 12 QTL associated with seed oil content identified, 9 were high-oil QTL which derived from the specially high-oil cultivar zy036. Two high-oil QTL on chromosomes A2 and C9 co-localized in two out of three trials. By QTL mapping for seed oil content, we found four candidate genes for seed oil content related to four gene markers: GSNP39, GSSR161, GIFLP106 and GIFLP046. This information will be useful for cloning functional genes correlated with seed oil content in the future.     

Light-dependent gravitropism and negative phototropism of inflorescence stems in a dominant Aux/IAA mutant of Arabidopsis thaliana,axr2

Gravitropism and phototropism of the primary inflorescence stems were examined in a dominant Aux/IAA mutant of Arabidopsis, axr2/iaa7, which did not display either tropism in hypocotyls. axr2-1 stems completely lacked gravitropism in the dark but slowly regained it in light condition. Though wild-type stems showed positive phototropism, axr2 stems displayed negative phototropism with essentially the same light fluence-response curve as the wild type (WT). Application of 1-naphthaleneacetic acid-containing lanolin to the stem tips enhanced the positive phototropism of WT, and reduced the negative phototropism of axr2. Decapitation of stems caused a small negative phototropism in WT, but did not affect the negative phototropism of axr2. p-glycoprotein 1 (pgp1) pgp19 double mutants showed no phototropism, while decapitated double mutants exhibited negative phototropism. Expression of auxin-responsive IAA14/SLR, IAA19/MSG2 and SAUR50 genes was reduced in axr2 and pgp1 pgp19 stems relative to that of WT. These suggest that the phototropic response of stem is proportional to the auxin supply from the shoot apex, and that negative phototropism may be a basal response to unilateral blue-light irradiation when the levels of auxin or auxin signaling are reduced to the minimal level in the primary stems. In contrast, all of these treatments reduced or did not affect gravitropism in wild-type or axr2 stems. Tropic responses of the transgenic lines that expressed axr2-1 protein by the endodermis-specific promoter suggest that AXR2-dependent auxin response in the endodermis plays a more crucial role in gravitropism than in phototropism in stems but no significant roles in either tropism in hypocotyls.     

Multi-trait and multi-environment QTL analysis reveals the impact of seed colour on seed composition traits in <Emphasis Type="Italic">Brassica napus</Emphasis>

Brassica napus seed composition traits (fibre, protein, oil and fatty acid profiles), seed colour and yield-associated traits are regulated by a complex network of genetic factors. Although previous studies have attempted to dissect the underlying genetic basis for these traits, a more complete picture of the available quantitative trait loci (QTL) variation and any interaction between the different traits is required. In this study, QTL mapping for eleven seed composition traits, seed colour and a yield-related trait (TSW) was conducted in a spring-type canola-quality B. napus doubled haploid (DH) population from a cross between black-seeded (DH12075) and yellow-seeded (YN01-429) lines across five environments. A major QTL associated with fibre traits (acid detergent fibre, acid detergent lignin and neutral detergent fibre) and seed colour (whiteness index) was mapped on chromosome N9 across the five environments. Multi-trait analysis identified QTL which had pleiotropic effect for seed colour and other composition traits. Multi-environment analysis revealed genetic (QTL) × environment effects on most QTL. These findings provide a more detailed insight into the complex QTL networks controlling seed composition and yield-associated traits in canola-quality B. napus.     

QTL mapping in autotetraploids using SNP dosage information

Key message

Dense linkage maps derived by analysing SNP dosage in autotetraploids provide detailed information about the location of, and genetic model at, quantitative trait loci.

Abstract

Recent developments in sequencing and genotyping technologies enable researchers to generate high-density single nucleotide polymorphism (SNP) genotype data for mapping studies. For polyploid species, the SNP genotypes are informative about allele dosage, and Hackett et al. (PLoS ONE 8:e63939, 2013) presented theory about how dosage information can be used in linkage map construction and quantitative trait locus (QTL) mapping for an F₁ population in an autotetraploid species. Here, QTL mapping using dosage information is explored for simulated phenotypic traits of moderate heritability and possibly non-additive effects. Different mapping strategies are compared, looking at additive and more complicated models, and model fitting as a single step or by iteratively re-weighted modelling. We recommend fitting an additive model without iterative re-weighting, and then exploring non-additive models for the genotype means estimated at the most likely position. We apply this strategy to re-analyse traits of high heritability from a potato population of 190 F₁ individuals: flower colour, maturity, height and resistance to late blight (Phytophthora infestans (Mont.) de Bary) and potato cyst nematode (Globodera pallida), using a map of 3839 SNPs. The approximate confidence intervals for QTL locations have been improved by the detailed linkage map, and more information about the genetic model at each QTL has been revealed. For several of the reported QTLs, candidate SNPs can be identified, and used to propose candidate trait genes. We conclude that the high marker density is informative about the genetic model at loci of large effects, but that larger populations are needed to detect smaller QTLs.