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.

     

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.     

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.

     

Chromosome segment detection for seed size and shape traits using an improved population of wild soybean chromosome segment substitution lines

Size and shape of soybean seeds are closely related to seed yield and market value. Annual wild soybeans have the potential to improve cultivated soybeans, but their inferior seed characteristics should be excluded. To detect quantitative trait loci (QTLs)/segments of seed size and shape traits in annual wild soybean, its chromosome segment substitution lines (CSSLs) derived from NN1138-2 (recurrent parent, Glycine max) and N24852 (donor parent, Glycine soja) and then modified 2 iterations (coded SojaCSSLP3) were improved further to contain more lines (diagonal segments) and less heterozygous and missing portions. The new population (SojaCSSLP4) composed of 195 CSSLs was evaluated under four environments, and 11, 13, 7, 15 and 14 QTLs/segments were detected for seed length (SL), seed width (SW), seed roundness (SR), seed perimeter (SP) and seed cross section area (SA), respectively, with all 60 wild allele effects negative. Among them, 16 QTLs/segments were shared by 2–5 traits, respectively, but 0–3 segments for each of the 5 traits were independent. The non-shared Satt274 and shared Satt305, Satt540 and Satt239 were major segments, along with other segments composed of two different but related sets of genetic systems for SR and the other 4 traits, respectively. Compared with the literature, 7 SL, 5 SW and 2 SR QTLs/segments were also detected in cultivated soybeans; allele distinction took place between cultivated and wild soybeans, and also among cultivated parents. The present mapping is understood as macro-segment mapping, the segments may be further dissected into smaller segments as well as corresponding QTLs/genes.     

Mapping of days to flower and seed yield in spring oilseed <Emphasis Type="Italic">Brassica napus</Emphasis> carrying genome content introgressed from <Emphasis Type="Italic">Brassica oleracea</Emphasis>

Earliness of flowering and maturity and high seed yield are important objectives of breeding spring Brassica napus canola. Previously, we have introgressed earliness of flowering from Brassica oleracea into spring B. napus canola through interspecific crossing between these two species. In this paper, we report quantitative trait locus (QTL) mapping of days to flower and seed yield by use of publicly available markers and markers designed based on flowering time genes and a doubled haploid population, derived from crossing of the spring canola parent and an early flowering line developed from a B. napus × B. oleracea cross, tested in nine field trials for over 5 years. Five genomic regions associated with days to flower were identified on C1, C2, C3, and C6 of which the single QTL of C1 was detected in all trials; in all cases, the allele introgressed from B. oleracea reduced the number of days to flower. BLASTn search in the Brassica genomes located the physical position of the QTL markers and identified putative flowering time genes in these regions. In the case of seed yield, ten QTL from eight linkage groups were detected; however, none could be consistently detected in all trials. The QTL region of C1 associated with days to flower did not show significant association with seed yield in more than 80% of the field trials; however, in a single trial, the allele introgressed from B. oleracea exerted a negative effect on seed yield. Thus, the genomic regions and molecular markers identified in this research could potentially be used in breeding for the development of early flowering B. napus canola cultivars without affecting seed yield in a majority of the environments.     

Genetic variation for domestication-related traits revealed in a cultivated rice,Nipponbare (<Emphasis Type="Italic">Oryza sativa ssp. japonica</Emphasis>) × ancestral rice, <Emphasis Type="Italic">O. nivara</Emphasis>, mapping population

Oryza nivara is the ancestral species of cultivated rice (Oryza sativa). It has been the source of novel alleles for resistance to biotic and abiotic stresses, as well as yield improvement, lost during the course of domestication. To determine the molecular changes that occurred during domestication, the O. sativa ssp. japonica variety, Nipponbare, from which a reference sequence (RefSeq) was developed, was crossed with the O. nivara accession (IRGC100897), from which BAC-end sequences (BES) were derived. The mapping population composed of 279 F₂ progeny lines derived from this cross was phenotyped for 19 traits important to domestication and yield improvement, including basal sheath and culm color, culm angle, days to heading, plant height, seed shattering, flag leaf length and width, panicle type and length, awn length and color, pericarp color, and seed color, length, width, length to width ratio, volume and surface area. The population was genotyped using 95 SSR markers and 114 single nucleotide variation (SNV) markers, selected by comparing the Nipponbare RefSeq and O. nivara BES. At least one major QTL was identified for each trait evaluated, and for 28 of the 46 QTL, the trait increase was attributed to the allele contributed by the O. nivara parent. Candidate genes were identified in 37 of the QTL regions. This study validated SNV markers that can be used for mapping in populations with a wild species parent. In the future, SNVs could be used for marker-assisted selection to incorporate desirable, novel alleles for stress resistance and yield improvement, identified in rice wild species like O. nivara into elite, adapted O. sativa varieties.     

Identification of QTL for maize grain yield and kernel-related traits

Grain yield (GY) is one of the most important and complex quantitative traits in maize (Zea mays L.) breeding practice. Quantitative trait loci (QTLs) for GY and three kernel-related traits were detected in a set of recombinant inbred lines (RILs). One hundred and seven simple sequence repeats (SSRs) and 168 insertion/deletion polymorphism markers (Indels) were used to genotype RILs. Eight QTLs were found to be associated with four yield-related traits: GY, 100-kernel weight (HKW), 10-kernel length (KL), and 10-kernel length width (KW). Each QTL explained between 5.96 (qKL2-1) and 13.05 (qKL1-1) per cent of the phenotypic variance. Notably, one common QTL, located at the marker interval between bnlg1893 and chr2-236477 (chromosomal bin 2.09) simultaneously controlled GY and HKW; another common QTL, at bin 2.03 was simultaneously responsible for HKW and KW. Of the QTLs identified, only one pair of significant epistatic interaction involved in chromosomal region at bin 2.03 was detected for HKW; no significant QTL × environment interactions were observed. These results provide the common QTLs and for marker-assisted breeding.     

Mapping of novel salt tolerance QTL in an Excalibur × Kukri doubled haploid wheat population

Key message

Novel QTL for salinity tolerance traits have been detected using non-destructive and destructive phenotyping in bread wheat and were shown to be linked to improvements in yield in saline fields.

Abstract

Soil salinity is a major limitation to cereal production. Breeding new salt-tolerant cultivars has the potential to improve cereal crop yields. In this study, a doubled haploid bread wheat mapping population, derived from the bi-parental cross of Excalibur?×?Kukri, was grown in a glasshouse under control and salinity treatments and evaluated using high-throughput non-destructive imaging technology. Quantitative trait locus (QTL) analysis of this population detected multiple QTL under salt and control treatments. Of these, six QTL were detected in the salt treatment including one for maintenance of shoot growth under salinity (QG_(1–5).asl-7A), one for leaf Na⁺ exclusion (QNa.asl-7A) and four for leaf K⁺ accumulation (QK.asl-2B.1, QK.asl-2B.2, QK.asl-5A and QK:Na.asl-6A). The beneficial allele for QG_(1–5).asl-7A (the maintenance of shoot growth under salinity) was present in six out of 44 mainly Australian bread and durum wheat cultivars. The effect of each QTL allele on grain yield was tested in a range of salinity concentrations at three field sites across 2 years. In six out of nine field trials with different levels of salinity stress, lines with alleles for Na⁺ exclusion and/or K⁺ maintenance at three QTL (QNa.asl-7A, QK.asl-2B.2 and QK:Na.asl-6A) excluded more Na⁺ or accumulated more K⁺ compared to lines without these alleles. Importantly, the QK.asl-2B.2 allele for higher K⁺ accumulation was found to be associated with higher grain yield at all field sites. Several alleles at other QTL were associated with higher grain yields at selected field sites.

     

The causal deletions in the second exon of <Emphasis Type="Italic">An-3</Emphasis> closely associated with awn development and rice yield

Awn is one of important traits during rice domestication. To understand the development of rice awn and the roles it played in rice domestication, we preliminary mapped a major QTL An-3 for awn development using chromosome segment substitution line CSSL138 developed by introgressed genomic fragments of long-awned Guangxi common wild rice (GXCWR, Oryza rufipogon Griff.) into genetic background of short-awned indica cultivar 93–11. An-3 was then fine mapped to a 7-kb region of chromosome 8. An epidermal patterning factor-like protein gene was identified as the single candidate gene corresponding to this QTL. An-3 was showed to be an allele of RAE2 and GAD1, and negatively regulated 1000-grains weight, grain length, and length–width ratio. Comparing with the coding sequences of An-3 from CSSL138, a 2- and 4-bp frame-shift deletions in the second exon were identified in 93–11 and Nipponbare, respectively. Taken together, our results provide valuable natural variation in the alleles of An-3 between common wild rice and cultivated rice, which will be helpful in clarifying the mechanism of awn development and promoting the application of an-3 in genetic improvement of rice yield traits.     

Genetic analysis of shoot fresh weight in a cross of wild (<Emphasis Type="Italic">G. soja</Emphasis>) and cultivated (<Emphasis Type="Italic">G. max</Emphasis>) soybean

Shoot fresh weight (SFW) is one of the parameters, used to estimate the total plant biomass yield in soybean. In the present study, a total of 188 F_5:8 recombinant inbred lines (RIL) derived from an interspecific cross of PI 483463 (Glycine soja) and Hutcheson (Glycine max) were investigated for SFW variation in the field for three consecutive years. The parental lines and RILs were phenotyped in the field at the R6 stage by measuring total biomass in kg/plot to identify the QTLs for SFW. Three QTLs qSFW6_1, qSFW15_1, and qSFW19_1 influencing SFW were identified on chromosome 6, 15, and 19, respectively. The QTL qSFW19_1 flanked between the markers BARC-044913-08839 and BARC-029975-06765 was the stable QTL expressed in all the three environments. The phenotypic variation explained by the QTLs across all environments ranged from 6.56 to 21.32 %. The additive effects indicated contribution of alleles from both the parents and additive × environment interaction effects affected the expression of SFW QTL. Screening of the RIL population with additional SSRs from the qSFW19_1 region delimited the QTL between the markers SSR19-1329 and BARC-29975-06765. QTL mapping using bin map detected two QTLs, qSFW19_1A and qSFW19_1B. The QTL qSFW19_1A mapped close to the Dt1 gene locus, which affects stem termination, plant height, and floral initiation in soybean. Potential candidate genes for SFW were pinpointed, and sequence variations within their sequences were detected using high-quality whole-genome resequencing data. The findings in this study could be useful for understanding genetic basis of SFW in soybean.     

Identification of QTL regions for seedling root traits and their effect on nitrogen use efficiency in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Key message

QTL for a wheat ideotype root system and its plasticity to nitrogen deficiency were characterized.

Abstract

Root system architecture-related traits (RRTs) and their plasticity to nitrogen availability are important for nitrogen acquisition and yield formation in wheat (Triticum aestivum L.). In this study, quantitative trait loci (QTL) analysis was conducted under different nitrogen conditions, using the seedlings of 188 recombinant inbred lines derived from a cross between Kenong 9204 and Jing 411. Fifty-three QTL for seven RRTs and fourteen QTL for the plasticity of these RRTs to nitrogen deficiency were detected. Thirty of these QTL were mapped in nine clusters on chromosomes 2B, 2D, 3A, 3D, 6B, 6D, 7A and 7B. Six of these nine clusters were also colocated with loci for nitrogen use efficiency (NUE)-related traits (NRTs). Among them, three QTL clusters (C2B, C6D and C7B) were highlighted, considering that they individually harbored three stable robust QTL (i.e., QMrl-2B.1, QdRs-6D and QMrl-7B). C2B and C7B stably contributed to the optimal root system, and C6D greatly affected the plasticity of RRTs in response to nitrogen deficiency. However, strong artificial selection was only observed for C7B in 574 derivatives of Kenong 9204. Covariance analysis identified QMrl-7B as the major contributor in C7B that affected the investigated NRTs in mature plants. Phenotypic analysis indicated that thousand kernel weight might represent a “concomitant” above-ground trait of the “hidden” RRTs controlled by C7B, which are used for breeding selection. Dissecting these QTL regions with potential breeding value will ultimately facilitate the selection of donor lines with both high yield and NUE in wheat breeding programs.

     

The seed dormancy allele <Emphasis Type="Italic">TaSdr</Emphasis>-<Emphasis Type="Italic">A1a</Emphasis> associated with pre-harvest sprouting tolerance is mainly present in Chinese wheat landraces

Key message

We cloned TaSdr - A1 gene, and developed a gene-specific marker for TaSdr - A1 . A QTL for germination index at the TaSdr - A1 locus was identified in the Yangxiaomai/Zhongyou 9507 RIL population.

Abstract

Pre-harvest sprouting (PHS) affects yield and end-use quality in bread wheat (Triticum aestivum L.). In the present study we found an association between the TaSdr-A1 gene and PHS tolerance in bread wheat. TaSdr-A1 on chromosome 2A was cloned using a homologous cloning approach. Sequence analysis of TaSdr-A1 revealed an SNP at position 643, with the G allele being present in genotypes with lower germination index (GI) values and A in those with higher GI. These alleles were designated as TaSdr-A1a and TaSdr-A1b, respectively. A cleaved amplified polymorphism sequence (CAPS) marker Sdr2A based on the SNP was developed, and linkage mapping and QTL analysis were conducted to confirm the association between TaSdr-A1 and seed dormancy. Sdr2A was located in a 2.9 cM interval between SSR markers Xgwm95 and Xgwm372. A QTL for GI at the TaSdr-A1 locus explained 6.6, 7.3, and 8.2 % of the phenotypic variances in a Yangxiaomai/Zhongyou 9507 RIL population grown at Beijing, Shijiazhuang, and the averaged data from the two environments, respectively. Two sets of Chinese wheat cultivars used for validating the TaSdr-A1 polymorphism and the corresponding gene-specific marker Sdr2A showed that TaSdr-A1 was significantly associated with GI. Among 29 accessions with TaSdr-A1a, 24 (82.8 %) were landraces, indicating the importance of Chinese wheat landraces as sources of PHS tolerance. This study identified a novel PHS resistance allele TaSdr-A1a mainly presented in Chinese landraces and it is likely to be the causal gene for QPhs.ccsu-2A.3, providing new information for an understanding of seed dormancy.

     

Identification of candidate genes of QTLs for seed weight in <Emphasis Type="Italic">Brassica napus</Emphasis> through comparative mapping among <Emphasis Type="Italic">Arabidopsis</Emphasis> and <Emphasis Type="Italic">Brassica</Emphasis>species

Background

Map-based cloning of quantitative trait loci (QTLs) in polyploidy crop species remains a challenge due to the complexity of their genome structures. QTLs for seed weight in B. napus have been identified, but information on candidate genes for identified QTLs of this important trait is still rare.

Results

In this study, a whole genome genetic linkage map for B. napus was constructed using simple sequence repeat (SSR) markers that covered a genetic distance of 2,126.4 cM with an average distance of 5.36 cM between markers. A procedure was developed to establish colinearity of SSR loci on B. napus with its two progenitor diploid species B. rapa and B. oleracea through extensive bioinformatics analysis. With the aid of B. rapa and B. oleracea genome sequences, the 421 homologous colinear loci deduced from the SSR loci of B. napus were shown to correspond to 398 homologous loci in Arabidopsis thaliana. Through comparative mapping of Arabidopsis and the three Brassica species, 227 homologous genes for seed size/weight were mapped on the B. napus genetic map, establishing the genetic bases for the important agronomic trait in this amphidiploid species. Furthermore, 12 candidate genes underlying 8 QTLs for seed weight were identified, and a gene-specific marker for BnAP2 was developed through molecular cloning using the seed weight/size gene distribution map in B. napus.

Conclusions

Our study showed that it is feasible to identify candidate genes of QTLs using a SSR-based B. napus genetic map through comparative mapping among Arabidopsis and B. napus and its two progenitor species B. rapa and B. oleracea. Identification of candidate genes for seed weight in amphidiploid B. napus will accelerate the process of isolating the mapped QTLs for this important trait, and this approach may be useful for QTL identification of other traits of agronomic significance.

     

Identification and validation of quantitative trait loci controlling seed isoflavone content across multiple environments and backgrounds in soybean

Soybean is important throughout the world not only due to the high seed protein and oil but also owing to the seed isoflavone. To improve the isoflavone concentration in seeds, detecting and mining the stable and reliable quantitative trait loci (QTLs) and related genes in multiple environments and genetic backgrounds become more and more important. In view of this, a F_6:7 recombinant inbred line (RIL) population of 345 lines derived from a cross between Zheng 92116 and Liaodou14 (ZL) was genotyped using 1739 polymorphic SNP and 127 SSR markers in this study and was phenotyped for individual and total seed isoflavone in four environments over 2 years. In total, 48 additive QTLs, which explained 3.00–29.83% of seed isoflavone variation, were identified. Of them, eight QTLs (qDA1_1, qGA1_1, qTIA1_1, qDA1_2, qGA1_2, qTIA1_2, qDA1_3, qTIA1_3) with phenotypic variation explained (PVE) ranging from 14.09 to 28.59% for daidzin, genistin, and total isoflavone were located on the same region of linkage group (LG) A1. These QTLs were further verified in another RIL population derived from Zheng 92116 × Qihuang 30 (ZQ). Meanwhile, the other four overlapping QTLs on linkage group B1, which were associated with glycitin content (qGLB1_1, qGLB1_2, qGLB1_3, qGLB1_4) and explained 16.52 to 29.83% of phenotypic variation, were also verified using the ZQ population. Moreover, the individuals with different genotypes at the common flanking SNP markers for these QTLs on LGs A1 and B1 in the two mapping populations showed significant different isoflavone content, which further validate the QTL mapping results. And also, some candidate genes might participate in the isoflavone biosynthesis processes were found in these stable QTL regions. Thus, the novel and stable QTLs identified and verified in this study could be applied in marker-assisted selection breeding or map-based candidate genes cloning in soybean seed isoflavone genetic improvement in future.     

Development of an integrated linkage map of einkorn wheat and its application for QTL mapping and genome sequence anchoring

Key message

An integrated genetic map was constructed for einkorn wheat A genome and provided valuable information for QTL mapping and genome sequence anchoring.

Abstract

Wheat is one of the most widely grown food grain crops in the world. The construction of a genetic map is a key step to organize biologically or agronomically important traits along the chromosomes. In the present study, an integrated linkage map of einkorn wheat was developed using 109 recombinant inbred lines (RILs) derived from an inter sub-specific cross, KT1-1 (T. monococcum ssp. boeoticum) × KT3-5 (T. monococcum ssp. monococcum). The map contains 926 molecular markers assigned to seven linkage groups, and covers 1,377 cM with an average marker interval of 1.5 cM. A quantitative trait locus (QTL) analysis of five agronomic traits identified 16 stable QTL on all seven chromosomes, except 6A. The total phenotypic variance explained by these stable QTL using multiple regressions varied across environments from 8.8 to 87.1 % for days to heading, 24.4–63.0 % for spike length, 48.2–79.6 % for spikelet number per spike, 13.1–48.1 % for plant architecture, and 12.2–26.5 % for plant height, revealing that much of the RIL phenotypic variation had been genetically dissected. Co-localizations of closely linked QTL for different traits were frequently observed, especially on 3A and 7A. The QTL on 3A, 5A and 7A were closely associated with Eps-A ^m 3, Vrn1 and Vrn3 loci, respectively. Furthermore, this genetic map facilitated the anchoring of 237 T. urartu scaffolds onto seven chromosomes with a physical length of 26.15 Mb. This map and the QTL data provide valuable genetic information to dissect important agronomic and developmental traits in diploid wheat and contribute to the genetic ordering of the genome assembly.

     

Application of gliadin polymorphism for pedigree analysis in common wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.) from Northern Kazakhstan

Gliadins, seed storage proteins, are popular markers effectively employed for the analysis of common wheat. Gliadin electrophoretic patterns are genotype-specific, reproducible, not dependent on growing conditions and are suitable for germplasm identification complementary to molecular markers. Gliadins have been identified and used in wheat from various countries, but prior to this study little was known about gliadin polymorphism in wheat from Kazakhstan. In this study, 48 alleles of six gliadin-coding loci were identified in 43 cultivars of spring wheat from Northern Kazakhstan. The alleles Gli-A1 f , Gli-B1 e , Gli-D1 a , Gli-A2 p , Gli-B2 d and Gli-D2 e had maximal frequencies in each of the six loci. Identified Gli alleles in the loci formed ‘Gliadin Genetic Formula’ unique for each studied variety, and these were compared to the published data from previously analyzed wheat varieties. Pedigree analysis of 43 varieties studied for gliadin polymorphisms indicated that some Gli alleles were conserved and inherited from the progenitor cultivar Akmolinka 1. In contrast, other Gli alleles were replaced by those from modern germplasms. It is assumed that a higher frequency of gliadin alleles can be associated with the selection of genotypes with improved traits for yield and seed quality in the studied wheat cultivars from Northern Kazakhstan.     

Round fruit shape in WI7239 cucumber is controlled by two interacting quantitative trait loci with one putatively encoding a tomato <Emphasis Type="Italic">SUN</Emphasis> homolog

Key message

QTL analysis revealed two interacting loci, FS1.2 and FS2.1, underlying round fruit shape in WI7239 cucumber; CsSUN , a homolog of tomato fruit shape gene SUN , was a candidate for FS1.2.

Abstract

Fruit size is an important quality and yield trait in cucumber, but its genetic basis remains poorly understood. Here we reported QTL mapping results on fruit size with segregating populations derived from the cross between WI7238 (long fruit) and WI7239 (round fruit) inbred cucumber lines. Phenotypic data of fruit length and diameter were collected at anthesis, immature and mature fruit stages in four environments. Ten major-effect QTL were detected for six traits; synthesis of information from these QTL supported two genes, FS1.2 and FS2.1, underlying fruit size variation in the examined populations. Under the two-gene model, deviation from expected segregation ratio in fruit length and diameter among segregating populations was observed, which could be explained mainly by the interactions between FS1.2 and FS2.1, and segregation distortion in the FS2.1 region. Genome-wide candidate gene search identified CsSUN, a homolog of the tomato fruit shape gene SUN, as the candidate for FS1.2. The round-fruited WI7239 had a 161-bp deletion in the first exon of CsSUN, and its expression in WI7239 was significantly lower than that in WI7238. A marker derived from this deletion was mapped at the peak location of FS1.2 in QTL analysis. Comparative analysis suggested the melon gene CmSUN-14, a homolog of CsSUN as a candidate of the fl2/fd2/fw2 QTL in melon. This study revealed the unique genetic architecture of round fruit shape in WI7239 cucumber. It also highlights the power of QTL analysis for traits with a simple genetic basis but their expression is complicated by other factors.

     

Characterisation of a novel quantitative trait locus, <Emphasis Type="Italic">GN4</Emphasis>-<Emphasis Type="Italic">1</Emphasis>, for grain number and yield in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Key message

A novel QTL for grain number, GN4-1, was identified and fine-mapped to an ~ 190-kb region on the long arm of rice chromosome 4.

Abstract

Rice grain yield is primarily determined by three components: number of panicles per plant, grain number per panicle and grain weight. Among these traits, grain number per panicle is the major contributor to grain yield formation and is a crucial trait for yield improvement. In this study, we identified a major quantitative trait locus (QTL) responsible for rice grain number on chromosome 4, designated GN4-1 (a QTL for Grain Number on chromosome 4), using advanced segregating populations derived from the crosses between an elite indica cultivar ‘Zhonghui 8006’ (ZH8006) and a japonica rice ‘Wuyunjing 8’ (WYJ8). GN4-1 was delimited to an ~ 190-kb region on chromosome 4. The genetic effect of GN4-1 was estimated using a pair of near-isogenic lines. The GN4-1 gene from WYJ8 promoted accumulation of cytokinins in the inflorescence and increased grain number per panicle by ~ 17%. More importantly, introduction of the WYJ8 GN4-1 gene into ZH8006 increased grain yield by ~ 14.3 and ~ 11.5% in the experimental plots in 2014 and 2015, respectively. In addition, GN4-1 promoted thickening of the culm and may enhance resistance to lodging. These results demonstrate that GN4-1 is a potentially valuable gene for improvement of yield and lodging resistance in rice breeding.