QTL mapping for yield and photosynthetic related traits under different water regimes in wheat

The improvement for drought tolerance requires understanding of the genetic control of wheat (Triticum aestivum L.) reaction to drought. In this study, a set of 131 recombinant inbred lines of wheat were investigated under well-watered (WW) and drought stress (DS) environments across 2 years to map quantitative trait loci (QTLs) for yield and physiological traits. A total of 225 QTLs were detected, including 32 non-environment-specific loci that were significant in both DS and WW, one drought-specific locus and two watering-specific loci. Three consistently-expressed QTLs (QTkw-3A.2, QTss-1A, and QScn-7A.1) were identified in at least three environments and the QTkw-1D.1 was significant in DS across the 2 years. By unconditional and conditional QTL analysis, spike number per plant and kernel number per spike were more important than thousand-kernel weight for grain yield (GY) at the given genetic background. Meta-analysis identified 67 meta-QTLs that contained QTLs for at least two traits. High frequency co-location of QTLs was found among either the spike-related traits or the six physiological traits. Four photosynthesis traits (CHL, LWUE, P _N, and C _i) were co-located with GY and/or yield components on various MQTLs. The results provided QTLs that warrant further study for drought tolerance breeding and are helpful for understanding the genetic basis of drought tolerance and the genetic contribution of yield components to GY at individual QTL level in wheat.     

Mapping QTLs for physiological and biochemical traits related to grain yield under control and terminal heat stress conditions in bread wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

In order to detect genomic regions with different effects for some of the physiological and biochemical traits of wheat, four experiments were conducted at Research Farm of Agricultural and Natural Resources Research Center of Zabol in 2015–2016 and 2016–2017 growing seasons. The experiments were carried out using four alpha lattice designs with two replications under non-stress and terminal heat stress conditions. Plant materials used in this study included 167 recombinant inbred lines and their parents (‘SeriM82’ and ‘Babax’). Six traits including grain yield (GY), proline content (PRO), water soluble carbohydrates (WSC), maximum efficiency of photosystem II (Fv/Fm), cytoplasmic membrane stability (CMS) and chlorophyll content (CHL) were evaluated. Genetic linkage map consisted of 211 AFLP marker, 120 SSR marker and 144 DArT markers with 1864 cm length and 4.4 cm mean distance. QTL analysis was carried out using a mixed-model-based composite interval mapping (MCIM) method. By the combined analysis of normal phenotypic values, 27 additive QTLs and five pairs of epistatic effects were identified for studied traits, among which two additive and one epistatic QTL showed significant QTL?×?environment interactions. By the combined analysis of stress phenotypic values, a total of 26 QTLs with additive effects and 5 epistatic QTLs were detected, among which one additive and one epistatic QTL showed QTL?×?environment interactions. Six QTLs with major effects (QGY-2B, QGY-2D, QPro-5B, QWSC-4A, QFv/Fm-6A and QCMS-4B), which were common between two conditions could be useful for marker-assisted selection (MAS) in order to develop heat tolerant and high-performance wheat varieties.     

A major QTL (<Emphasis Type="Italic">qFT12.1</Emphasis>) allele from wild soybean delays flowering time

Soybean is highly sensitive to photoperiod. To improve the adaptability and productivity of soybean, it is essential to understand the molecular mechanisms regulating flowering time. To identify new flowering time QTLs, we evaluated a BC₃F₅ population consisting of 120 chromosome segment substitution lines (CSSLs) over 2 years under field conditions. CSSLs were derived from a cross between the cultivated soybean cultivar Jackson and the wild soybean accession JWS156-1, followed by continuous backcrossing using Jackson as the recurrent parent. Four QTLs (qFT07.1, qFT12.1, qFT12.2, and qFT19.1) were detected on three chromosomes. Of these, qFT12.1 showed the highest effect, accounting for 36.37–38.27% of the total phenotypic variation over 2 years. This QTL was further confirmed in the F₇ recombinant inbred line population (n?=?94) derived from the same cross (Jackson × JWS156-1). Analysis of the qFT12.1 BC₃F₅ residual heterozygous line RHL509 validated the allele effect of qFT12.1 and revealed that the recessive allele of qFT12.1 resulted in delayed flowering. Evaluating the qFT12.1 near-isogenic lines (NILs) under different growth conditions showed that NILs with the wild soybean genotype always showed later flowering than those with the cultivated soybean genotype. qFT12.1 was delimited to a 2703-kb interval between the markers BARCSOYSSR_12_0220 and BARCSOYSSR_12_0368 on chromosome 12. qFT12.1 may be a new flowering time gene locus in soybean.     

QTLs for heading date and plant height under multiple environments in rice

Both heading date and plant height are important traits related to grain yield in rice. In this study, a recombinant inbred lines (RILs) population was used to map quantitative trait loci (QTLs) for both traits under 3 long-day (LD) environments and 1 short-day (SD) environment. A total of eight QTLs for heading date and three QTLs for plant height were detected by composite interval mapping under LD conditions. Additional one QTL for heading date and three QTLs for plant height were identified by Two-QTL model under LD conditions. Among them, major QTLs qHd7.1, qHd7.2 and qHd8 for heading date, and qPh1 and qPh7.1 for plant height were commonly detected. qHd7.1 and qHd7.2 were mapped to small regions of less than 1 cM. Genome position comparison of previously cloned genes with QTLs detected in this study revealed that qHd5 and qPh3.1 were two novel QTLs. The alleles of these QTLs increasing trait values were dispersed in both parents, which well explained the transgressive segregation observed in this population. In addition, the interaction between qHd7.1 and qHd8 was detected under all LD conditions. Multiple-QTL model analysis revealed that all QTLs and their interactions explained over 80% of heading date variation and 50% of plant height variation. Two heading date QTLs were detected under SD condition. Of them, qHd10 were commonly identified under LD condition. The difference in QTL detection between LD and SD conditions indicated most heading date QTLs are sensitive to photoperiod. These findings will benefit breeding design for heading date and plant height in rice.     

QTL mapping for downy mildew resistance in cucumber via bulked segregant analysis using next-generation sequencing and conventional methods

Key message

QTL mapping using NGS-assisted BSA was successfully applied to an F ₂ population for downy mildew resistance in cucumber. QTLs detected by NGS-assisted BSA were confirmed by conventional QTL analysis.

Abstract

Downy mildew (DM), caused by Pseudoperonospora cubensis, is one of the most destructive foliar diseases in cucumber. QTL mapping is a fundamental approach for understanding the genetic inheritance of DM resistance in cucumber. Recently, many studies have reported that a combination of bulked segregant analysis (BSA) and next-generation sequencing (NGS) can be a rapid and cost-effective way of mapping QTLs. In this study, we applied NGS-assisted BSA to QTL mapping of DM resistance in cucumber and confirmed the results by conventional QTL analysis. By sequencing two DNA pools each consisting of ten individuals showing high resistance and susceptibility to DM from a F₂ population, we identified single nucleotide polymorphisms (SNPs) between the two pools. We employed a statistical method for QTL mapping based on these SNPs. Five QTLs, dm2.2, dm4.1, dm5.1, dm5.2, and dm6.1, were detected and dm2.2 showed the largest effect on DM resistance. Conventional QTL analysis using the F₂ confirmed dm2.2 (R ² = 10.8–24 %) and dm5.2 (R ² = 14–27.2 %) as major QTLs and dm4.1 (R ² = 8 %) as two minor QTLs, but could not detect dm5.1 and dm6.1. A new QTL on chromosome 2, dm2.1 (R ² = 28.2 %) was detected by the conventional QTL method using an F₃ population. This study demonstrated the effectiveness of NGS-assisted BSA for mapping QTLs conferring DM resistance in cucumber and revealed the unique genetic inheritance of DM resistance in this population through two distinct major QTLs on chromosome 2 that mainly harbor DM resistance.

     

QTL mapping of root traits in phosphorus-deficient soils reveals important genomic regions for improving NDVI and grain yield in barley

Key message

Major QTLs for root rhizosheath size are not correlated with grain yield or yield response to phosphorus. Important QTLs were found to improve phosphorus efficiency.

Abstract

Root traits are important for phosphorus (P) acquisition, but they are often difficult to characterize and their breeding values are seldom assessed under field conditions. This has shed doubts on using seedling-based criteria of root traits to select and breed for P efficiency. Eight root traits were assessed under controlled conditions in a barley doubled-haploid population in soils differing in P levels. The population was also phenotyped for grain yield, normalized difference vegetation index (NDVI), grain P uptake and P utilization efficiency at maturity (PutE_GY) under field conditions. Several quantitative traits loci (QTLs) from the root screening and the field trials were co-incident. QTLs for root rhizosheath size and root diameter explained the highest phenotypic variation in comparison to QTLs for other root traits. Shared QTLs were found between root diameter and grain yield, and total root length and PutE_GY. A common major QTL for rhizosheath size and NDVI was mapped to the HvMATE gene marker on chromosome 4H. Collocations between major QTLs for NDVI and grain yield were detected on chromosomes 6H and 7H. When results from BIP and MET were combined, QTLs detected for grain yield were also those QTLs found for NDVI. QTLs qGY5H, qGY6H and qGY7Hb on 7H were robust QTLs in improving P efficiency. A selection of multiple loci may be needed to optimize the breeding outcomes due to the QTL x Environment interaction. We suggest that rhizosheath size alone is not a reliable trait to predict P efficiency or grain yield.

     

Genetic Dissection of Epistatic Interactions Contributing Grain Yield Variability in Rice under Drought

AimsThe aim of the present study was to evaluate the performance of ‘high’-‘low’ yielding pyramided lines (PLs), having the same combinations of qDTYs in Samba Mahsuri, MR219 and IR64-Sub1 genetic backgrounds, and to understand the genetic interactions among QTL and/with genetic background affecting grain yield.BackgroundEpistasis regulates the expression of traits governed by several major/minor genes/QTL. Multiple pyramided lines (PLs) with the same grain yield QTL (qDTYs) combinations but possessing grain yield variability under different levels of reproductive stage drought stress were identified in different rice genetic backgrounds at International Rice Research Institute (IRRI).ObjectivesThe objectives of the present study were to evaluate the performance pyramided lines (PLs) with drought QTL in the backgrounds of Samba Mahsuri, MR219 and IR64-Sub1 under reproductive stage drought stress (RS) and NS (non-stress) conditions, to understand the effect of epistatic interactions among qDTYs and with genetic background on GY under the differential level of stress and to identify the promising drought-tolerant lines with high yield under drought and higher background recovery in different genetic backgrounds.MethodsThe experiments were conducted in 2015 DS (dry season), 2015 WS (wet season) and 2017 DS at IRRI, Los Baños, Philippines, in a transplanted lowland ecosystem under lowland severe stress (LSS), lowland moderate stress (LMS) and lowland non-stress (LNS). The experiments were laid out in alpha lattice design with two replications.ResultsSeveral digenic interactions were found in different genetic backgrounds, 13 interactions in Samba Mahsuri, 11 in MR219 and 20 in IR64-Sub1 backgrounds. Among all digenic interactions, one QTL × QTL interaction, 17 QTL × background and 26 background × background interactions resulted in GY reduction in low yielding PLs in different genetic backgrounds under LSS or LMS. Negative interaction of qDTY_3.1, qDTY_4.1 and qDTY_9.1 with background markers and background × background interactions caused up to 15% GY reduction compared to the high yielding PLs under LMS in the Samba Mahsuri PLs. In MR219 PLs, the negative interaction of qDTY_2.2, qDTY_3.2, qDTY_4.1 and qDTY_12.1 with the background marker interval RM314-RM539, RM273-RM349 and RM445-RM346, RM473D-RM16, respectively resulted 52% GY reduction compared to the high yielding PLs under LSS. In IR64-Sub1 PLs, qDTY_6.1 interacted with background loci at RM16-RM135, RM228-RM333, RM202-RM287 and RM415-RM558A marker interval under LSS and at RM475-RM525 marker interval under LMS, causing GY reduction to 58% compared to the high yielding PLs.ConclusionHigh yielding PLs in Samba Mahsuri (IR 99734:1-33-69-1-22-6), MR219 (IR 99784-156-87-2-4-1) and IR64-Sub1 (IR 102784:2-89-632-2-1-2) backgrounds without any negative interactions were identified. The identified selected promising PLs may be used as potential drought-tolerant donors or may be released as varieties for drought-prone ecosystems in different countries.     

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.     

QTLs for Tolerance of Drought and Breeding for Tolerance of Abiotic and Biotic Stress: An Integrated Approach

Background

The coupling of biotic and abiotic stresses leads to high yield losses in rainfed rice (Oryza sativa L.) growing areas. While several studies target these stresses independently, breeding strategies to combat multiple stresses seldom exist. This study reports an integrated strategy that combines QTL mapping and phenotypic selection to develop rice lines with high grain yield (GY) under drought stress and non-stress conditions, and tolerance of rice blast.

Methodology

A blast-tolerant BC₂F₃-derived population was developed from the cross of tropical japonica cultivar Moroberekan (blast- and drought-tolerant) and high-yielding indica variety Swarna (blast- and drought-susceptible) through phenotypic selection for blast tolerance at the BC₂F₂ generation. The population was studied for segregation distortion patterns and QTLs for GY under drought were identified along with study of epistatic interactions for the trait.

Results

Segregation distortion, in favour of Moroberekan, was observed at 50 of the 59 loci. Majority of these marker loci co-localized with known QTLs for blast tolerance or NBS-LRR disease resistance genes. Despite the presence of segregation distortion, high variation for DTF, PH and GY was observed and several QTLs were identified under drought stress and non-stress conditions for the three traits. Epistatic interactions were also detected for GY which explained a large proportion of phenotypic variance observed in the population.

Conclusions

This strategy allowed us to identify QTLs for GY along with rapid development of high-yielding purelines tolerant to blast and drought with considerably reduced efforts. Apart from this, it also allowed us to study the effects of the selection cycle for blast tolerance. The developed lines were screened at IRRI and in the target environment, and drought and blast tolerant lines with high yield were identified. With tolerance to two major stresses and high yield potential, these lines may provide yield stability in rainfed rice areas.     

Fine mapping a major QTL <Emphasis Type="Italic">qFCC7</Emphasis><Subscript><Emphasis Type="Italic">L</Emphasis></Subscript> for chlorophyll content in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) cv. PA64s

Chlorophyll (Chl) content is an important agronomic trait directly affecting the photosynthetic rate. Using a high-density genetic map of 132 recombinant inbred lines (RILs) derived from the cross between 93-11 and PA64s, we detected the quantitative trait loci (QTLs) for Chl content of the top three leaves under two nitrogen (N) conditions at two developmental stages. A total of 32 main-effect QTLs located on chromosomes 1, 4, 5, 6, 7, 8, and 12 were identified, and these QTLs individually accounted for 6.0–20.8?% of the total phenotypic variation. A major QTL qFCC7 _L affecting the Chl content under low N condition was identified, and its positive allele came from PA64s. This QTL might be associated with the ability to tolerate low-N stress in rice. The chromosomal segment substitution line (CSSL) with the corresponding segment from PA64s had a higher SPAD value and photosynthetic rate than 93-11 and showed a lower specific leaf area (SLA). We performed a fine-mapping using a BC₄F₂ population via marker-assisted backcross and finally mapped this QTL to a 124.5 kb interval on the long arm of chromosome 7. Candidate gene analysis showed that there were sequence variations and expression differences in the predicted candidate gene between the two parents. These results suggest that the QTL qFCC7 _L may be useful for breeding the rice varieties with higher photosynthetic rate and grain yield.     

Increased drought tolerance and wider adaptability of qDTY 12.1 conferred by its interaction with qDTY 2.3 and qDTY 3.2

The genetic basis of high grain yield under reproductive-stage drought was studied using an F3-derived population generated from the cross of upland rice (Oryza sativa L.) cultivars Vandana and Way Rarem. Contributed by the susceptible parent Way Rarem, locus qDTY _12.1 was hypothesized to have interaction with loci from the Vandana genome to enhance the grain yield of tolerant line Vandana under drought. A test of the digenic interaction of qDTY _12.1 showed that two loci, qDTY _2.3 on chromosome 2 and qDTY _3.2 on chromosome 3, significantly increased the yield and harvest index of qDTY _12.1 -positive lines under severe upland and lowland drought conditions. qDTY _2.3 and qDTY _3.2 , in interaction with qDTY _12.1 , reduced days to flowering and plant height of qDTY _12.1 -positive lines under stress and non-stress conditions in upland. BC2F3-derived backcross inbred lines (BILs) were used to validate these results and identify new quantitative trait loci. Lines with qDTY _2.3 and qDTY _12.1 showed increased yield over Way Rarem under severe and moderate stress conditions, in upland. IR84996-50-4-B-4, a selection from one of the BILs, yielded more than the popular drought-tolerant cultivars Apo, UPLRi7, and IR74371-54-1-1 under severe stress conditions. Introgressed segments from Vandana also improved yield under non-stress conditions. The results indicate that digenic interactions can explain the genetic control of complex quantitative traits such as grain yield under drought, and a few interacting loci with large effects on grain yield or yield-related traits may enhance drought response across a wide range of genetic backgrounds and environments when introgressed together.     

Identification of Early Vigor QTLs and QTL by Environment Interactions in Wheat (<Emphasis Type="Italic">Triticum eastivum</Emphasis> L.)

Crop productivity is highly dependent on successful seed germination and seedling establishment. This study evaluated two mapping populations, Batavia/Ernie (double haploid) and Synthetic/Opata (recombinant inbred lines), for early vigor under water stress and normal growing conditions. Significant gene, environment (water), and gene by environment interaction effects were observed. Broad sense heritability was 29 and 40% for the Batavia/Ernie and Synthetic/Opata populations, respectively. Quantitative trait loci (QTL) were analyzed based on single and multienvironment models. The two mapping populations differed in the number and locations of QTLs except qNev.uwa.4AL was identified in both populations under the non-stress condition, while qSev.uwa.3BL was specifically expressed under the stress condition in the Synthetic/Opata population. QTL by environment interaction (QEI) enabled identification of nine QTLs, including those identified by the single environment approach. Phenotypic variation expression (PVE) of QEIs ranged from 4.8 to 14.9% across the populations. Larger proportion of PVE of QEIs was explained by the additive components. Favorable alleles for three of the QTLs identified in the Synthetic/Opata population were derived from Synthetic, while Batavia contributed favorable alleles to a QTL on the long arm of chromosome 1D in the Batavia/Ernie population. QTL detected under water stress (qSev.uwa.3BL) co-located with the DREB 1 gene, which was mapped between markers Xmwg818 and Xfbb117 (58.1–77.6 cM). QTLs with high proportion of additive components can be validated for marker assisted gene pyramiding and selection.     

Genetic dissection of lint yield and fiber quality traits of <Emphasis Type="Italic">G. hirsutum</Emphasis> in <Emphasis Type="Italic">G. barbadense</Emphasis> background

Gossypium hirsutum L. is a widely cultivated species characterized by its high yield and wide environmental adaptability, while Gossypium barbadense is well known for its superior fiber quality. In the present report, we, for the first time, developed G. hirsutum chromosome segment introgression lines (ILs) in a G. barbadense background (GhILs_Gb) and genetically dissected the inheritance of lint yield and fiber quality of G. hirsutum in G. barbadense background. The GhILs_Gb contains introgressed segments spanning 4121.20 cM, which represents 82.20% of the tetraploid cotton genome, with an average length of 18.65 cM. A total of 39 quantitative trait loci (QTLs) for six traits are identified in this IL population planted in Xinjiang. Four QTL clusters are detected. Of them, however, three clusters have deleterious effects on fiber length and strength and boll weight, and only one cluster on Chr. D9 can be used in marker-assisted selection (MAS) to increase lint percentage and decrease micronaire value in G. barbadense. QTL mapping showed that most of yield-related QTLs detected have positive effects and increase lint yield in G. barbadense, while most of fiber quality-related QTLs have deleterious effects except for micronaire. It suggested that G. hirsutum evolved to have a high lint yield. Several lines improved in lint percentage and boll size in G. barbadense by introgressed one fragment of G. hirsutum have been developed from the GhILs_Gb. The ILs developed, and the analyses presented here will enhance the understanding of the genetics of lint yield and fiber quality in G. hirsutum and facilitate further molecular breeding to improve lint yield in G. barbadense.     

A novel allele of <Emphasis Type="Italic">TaGW2</Emphasis>-<Emphasis Type="Italic">A1</Emphasis> is located in a finely mapped QTL that increases grain weight but decreases grain number in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Key message

A novel TaGW2-A1 allele was identified from a stable, robust QTL region, which is pleiotropic for thousand grain weight, grain number per spike, and grain morphometric parameters in wheat.

Abstract

Thousand grain weight (TGW) and grain number per spike (GNS) are two crucial determinants of wheat spike yield, and genetic dissection of their relationships can help to fine-tune these two components and maximize grain yield. By evaluating 191 recombinant inbred lines in 11 field trials, we identified five genomic regions on chromosomes 1B, 3A, 3B, 5B, or 7A that solely influenced either TGW or GNS, and a further region on chromosome 6A that concurrently affected TGW and GNS. The QTL of interest on chromosome 6A, which was flanked by wsnp_BE490604A_Ta_2_1 and wsnp_RFL_Contig1340_448996 and designated as QTgw/Gns.cau-6A, was finely mapped to a genetic interval shorter than 0.538 cM using near isogenic lines (NILs). The elite NILs of QTgw/Gns.cau-6A increased TGW by 8.33%, but decreased GNS by 3.05% in six field trials. Grain Weight 2 (TaGW2-A1), a well-characterized gene that negatively regulates TGW and grain width in wheat, was located within the finely mapped interval of QTgw/Gns.cau-6A. A novel and rare TaGW2-A1 allele with a 114-bp deletion in the 5′ flanking region was identified in the parent with higher TGW, and it reduced TaGW2-A1 promoter activity and expression. In conclusion, these results expand our knowledge of the genetic and molecular basis of TGW-GNS trade-offs in wheat. The QTLs and the novel TaGW2-A1 allele are likely useful for the development of cultivars with higher TGW and/or higher GNS.

     

A QTL on Chromosome 3B in Bread Wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis>) Is Associated with Leaf Width Under Well-Watered and Water-Deficit Conditions

At an early stage of crop development, the rate of growth is largely determined by leaf characteristics. Plants with rapid leaf area development could save more water for transpiration and crop growth. In our study, a recombinant inbred family was used to identify quantitative trait loci (QTL) controlling leaf length (LL), leaf width (LW), and leaf area (LA) in wheat seedlings under well-watered (WW) and PEG-induced water-deficit (WD) conditions. A total of five QTL for LW, LL, and LA were detected, most of which were reported for the first time. A “constitutive” QTL for LW (Qheb.LW-3B), located on the long arm of chromosome 3B, was consistently detected under two water conditions, explaining 17.7 % of the phenotypic variance with a LOD value of 7.20 under WW condition and 13.3 % of the phenotypic variance with a LOD value of 4.87 under WD condition. The other four “adaptive” QTL were detected under a single water condition only. These QTL include the following: Qheb.LW-5B for LW (WW condition), Qheb.LL-3A, and Qheb.LL-5B for LL (WD condition) and Qheb.LA-3B for LA (WW condition). Four pairs of near isogenic lines (NILs) were developed to validate the effects of Qheb.LW-3B. The allele from the parent “CSCR6” increased the LW by an average of 8.2 % under WW condition and 13.8 % under WD condition, respectively. The position and effects of Qheb.LW-3B was confirmed. Qheb.LW-3B would be a valuable genetic resource to improve wheat seedling early establishment. The NILs we have generated would be useful for further characterization of Qheb.LW-3B, in studying its interaction with other traits of agronomic importance and in developing markers that can be reliably used to follow this major locus.     

Low validation rate of quantitative trait loci for Gibberella ear rot resistance in European maize

Key message

Six quantitative trait loci (QTL) for Gibberella ear rot resistance in maize were tested in two different genetic backgrounds; three QTL displayed an effect in few near isogenic line pairs.

Abstract

Few quantitative trait loci (QTL) mapping studies for Gibberella ear rot (GER) have been conducted, but no QTL have been verified so far. QTL validation is prudent before their implementation into marker-assisted selection (MAS) programs. Our objectives were to (1) validate six QTL for GER resistance, (2) evaluate the QTL across two genetic backgrounds, (3) investigate the genetic background outside the targeted introgressions. Pairs of near isogenic lines (NILs) segregating for a single QTL (Qger1, Qger2, Qger10, Qger13, Qger16, or Qger21) were developed by recurrent backcross until generation BC₃S₂. Donor parents (DP) carrying QTL were backcrossed to a susceptible (UH009) and a moderately resistant (UH007) recurrent parent. MAS was performed using five SNP markers covering a region of 40 cM around each QTL. All NILs were genotyped with the MaizeSNP50 assay and phenotyped for GER severity and deoxynivalenol and zearalenone content. Traits were significantly (P < 0.001) intercorrelated. Out of 34 NIL pairs with the UH009 genetic background, three pairs showed significant differences in at least one trait for three QTL (Qger1, Qger2, Qger13). Out of 25 NIL pairs with the UH007 genetic background, five pairs showed significant differences in at least one trait for two QTL (Qger2, Qger21). However, Qger16, Qger10 and Qger13 were most likely false positives. The genetic background possibly affected NIL pairs comparisons due to linkage drag and/or epistasis with residual loci from the DP in non-target regions. In conclusion, validation rates were disappointingly low, which further indicates that GER resistance is controlled by many low-effect QTL.

     

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.     

Host plant quantitative trait loci affect specific behavioral sequences in oviposition by a stem-mining insect

Key message

Genetic diversity in quantitative loci associated with plant traits used by insects as cues for host selection can influence oviposition behavior and maternal choice.

Abstract

Host plant selection for oviposition is an important determinant of progeny performance and survival for phytophagous insects. Specific cues from the plant influence insect oviposition behavior; but, to date, no set of host plant quantitative trait loci (QTLs) have been shown to have an effect on behavioral sequences leading to oviposition. Three QTLs in wheat (Triticum aestivum L.) have been identified as influencing resistance to the wheat stem sawfly (WSS) (Cephus cinctus Norton). Wheat near-isogenic lines (NILs) for each of the three QTLs were used to test whether foraging WSS were able to discriminate variation in plant cues resulting from allelic changes. A QTL on chromosome 3B (Qss-msub-3BL) previously associated with stem solidness and larval antibiosis was shown to affect WSS oviposition behavior, host preference, and field infestation. Decreased preference for oviposition was also related to a QTL allele on chromosome 2D (Qwss.msub-2D). A QTL on chromosome 4A (Qwss.msub-4A.1) affected host plant attractiveness to foraging females, but did not change oviposition preference after females landed on the stem. These findings show that oviposition decisions regarding potential plant hosts require WSS females to discriminate signals from the plant associated with allelic variation at host plant quantitative loci. Allele types in a host plant QTL associated with differential survival of immature progeny can affect maternal choices for oviposition. The multidisciplinary approach used here may lead to the identification of plant genes with important community consequences, and may complement the use of antibiosis due to solid stems to control the wheat stem sawfly in agroecosystems.