Minor Quantitative Trait Loci Research Articles

Polygenic analysis of very high acetic acid tolerance in the yeast Saccharomyces cerevisiae reveals a complex genetic background and several new causative alleles

BackgroundHigh acetic acid tolerance is of major importance in industrial yeast strains used for second-generation bioethanol production, because of the high acetic acid content of lignocellulose hydrolysates. It is also important in first-generation starch hydrolysates and in sourdoughs containing significant acetic acid levels. We have previously identified snf4E269* as a causative allele in strain MS164 obtained after whole-genome (WG) transformation and selection for improved acetic acid tolerance.ResultsWe have now performed polygenic analysis with the same WG transformant MS164 to identify novel causative alleles interacting with snf4E269* to further enhance acetic acid tolerance, from a range of 0.8–1.2% acetic acid at pH 4.7, to previously unmatched levels for Saccharomyces cerevisiae. For that purpose, we crossed the WG transformant with strain 16D, a previously identified strain displaying very high acetic acid tolerance. Quantitative trait locus (QTL) mapping with pooled-segregant whole-genome sequence analysis identified four major and two minor QTLs. In addition to confirmation of snf4E269* in QTL1, we identified six other genes linked to very high acetic acid tolerance, TRT2, MET4, IRA2 and RTG1 and a combination of MSH2 and HAL9, some of which have never been connected previously to acetic acid tolerance. Several of these genes appear to be wild-type alleles that complement defective alleles present in the other parent strain.ConclusionsThe presence of several novel causative genes highlights the distinct genetic basis and the strong genetic background dependency of very high acetic acid tolerance. Our results suggest that elimination of inferior mutant alleles might be equally important for reaching very high acetic acid tolerance as introduction of rare superior alleles. The superior alleles of MET4 and RTG1 might be useful for further improvement of acetic acid tolerance in specific industrial yeast strains.

QTL Mapping and Prediction of Haploid Male Fertility Traits in Maize (Zea mays L.).

Chromosome doubling of maize haploids is a bottleneck in the large-scale application of doubled haploid (DH) technology. Spontaneous chromosome doubling (SCD) of haploid has been taken as an important method in the production of DH lines and low haploid male fertility (HMF) is a main limiting factor for the use of SCD. To study its genetic basis, haploids of 119 DH lines derived from a cross between inbred lines Qi319 and Chang7-2 were used to map the quantitative trait locus (QTL) contributing to HMF. Three traits including anther emergence rate (AER), anther emergence score (AES) and pollen production score (PPS) of the haploid population were evaluated at two locations. The heritability of the three traits ranged from 0.70 to 0.81. The QTL contributing to AER, AES and PPS were identified on the chromosomes 1, 2, 3, 4, 5, 7, 9 and 10. Five major QTL, qAER5-1, qAER5-2, qAES3, qPPS1 and qPPS5, were found and each could explain more than 15% of the phenotypic variance at least in one environment. Two major QTL, qPPS1 and qPPS5, and two minor QTL, qAES2 and qAER3, were repeatedly detected at both locations. To increase the application efficiency of HMF in breeding programs, genomic prediction for the three traits were carried out with ridge regression best linear unbiased prediction (rrBLUP) and rrBLUP adding QTL effects (rrBLUP-QTL). The prediction accuracies of rrBLUP-QTL were significantly higher than that by rrBLUP for three traits (p < 0.001), which indirectly indicates these QTL were effective. The prediction accuracies for PPS were 0.604 (rrBLUP) and 0.703 (rrBLUP-QTL) across both locations, which were higher than that of AER and AES. Overall, this study provides important information to understand the genetic architecture of SCD of maize haploids.

New quantitative trait locus (QTLs) and candidate genes associated with the grape berry color trait identified based on a high-density genetic map

BackgroundBerry color is an important trait in grapes and is mainly determined by the anthocyanin content and composition. To further explore the coloring mechanism of grape berries, the F1 population of Vitis vinifera ‘Red Globe’ × ‘Muscat Hamburg’ was used to map the color locus, and transcriptome analysis was performed to assist in screening candidate genes.ResultsA total of 438,407 high-quality single-nucleotide polymorphisms (SNPs) were obtained from whole-genome resequencing (WGS) of the population, and 27,454 SNPs were selected to construct a high-density genetic map. The selected SNPs were clustered into 19 linkage groups (LGs) spanning a genetic distance of 1442.638 cM. Berry color was evaluated by color grade, chromatic aberration, total anthocyanin content and anthocyanin composition. The Pearson correlation coefficients of these phenotypes in 2017 and 2018 were significant at the 0.01 level. The major color locus of MYBA1 and MYBA2 on LG2 was identified, explaining between 26 and 63.6% of all phenotypic variance. Furthermore, 9 additional QTLs with smaller effects were detected on Chr2, Chr4, Chr6, Chr11 and Chr17. Combined with the gene annotation and RNA-seq data, multiple new candidate genes were selected from the above QTLs.ConclusionThese results indicated that grape berry color is a quantitative trait controlled by a major color locus and multiple minor loci. Though the major color locus was consistent with previous studies, several minor QTLs and candidate genes associated with grape berry color and anthocyanin accumulation were identified in this study. And the specific regulatory mechanism still needs to be further explored.

Fine mapping of qBlsr3d, a quantitative trait locus conferring resistance to bacterial leaf streak in rice

AbstractBacterial leaf streak (BLS) is a destructive bacterial disease in rice (Oryza sativa L.). To date, at least 13 quantitative trait loci (QTL) conferring resistance to BLS have been identified in rice, while only one QTL, qBlsr5a, has been fine mapped and cloned. The present study focuses on fine mapping of qBlsr3d, a minor QTL conferring resistance to BLS. To fine map this QTL, 24 overlapping chromosome segment substitution lines (CSSLs) were developed from the F2 population derived from H359 × H359‐BLSR3D. Combining genotyping of molecular markers with resistant performance, qBlsr3d was delimited to an 81‐kb interval on chromosome 3, which included 12 annotated genes. Sequence alignment indicated that one of the candidate genes, LOC_Os03g03570, has three nucleotide substitutions in the CDS region between H359 and H359‐BLSR3D. In particular, LOC_Os03g03570 encodes a leucine‐rich repeat transmembrane protein, which has been reported to be associated with disease resistance, suggesting that LOC_Os03g03570 may be the target gene. Our research also suggests that CSSLs are suitable for mapping of minor QTL confering disease resistance. Furthermore, our finding has potential value in breeding rice varieties with resistance to BLS in rice.

Identification of Blast Resistance QTLs Based on Two Advanced Backcross Populations in Rice

BackgroundRice blast is an economically important and mutable disease of rice. Using host resistance gene to breed resistant varieties has been proven to be the most effective and economical method to control rice blast and new resistance genes or quantitative trait loci (QTLs) are then needed.ResultsIn this study, we constructed two advanced backcross population to mapping blast resistance QTLs. CR071 and QingGuAi3 were as the donor parent to establish two BC3F1 and derived BC3F2 backcross population in the Jin23B background. By challenging the two populations with natural infection in 2011 and 2012, 16 and 13 blast resistance QTLs were identified in Jin23B/CR071 and Jin23B/QingGuAi3 population, respectively. Among Jin23B/CR071 population, 3 major and 13 minor QTLs have explained the phenotypic variation from 3.50% to 34.08% in 2 years. And, among Jin23B/QingGuAi3 population, 2 major and 11 minor QTLs have explained the phenotypic variation from 2.42% to 28.95% in 2 years.ConclusionsSixteen and thirteen blast resistance QTLs were identified in Jin23B/CR071 and Jin23B/QingGuAi3 population, respectively. QTL effect analyses suggested that major and minor QTLs interaction is the genetic basis for durable blast resistance in rice variety CR071 and QingGuAi3.

Different genetic basis for alcohol dehydrogenase activity and plasticity in a novel alcohol environment for Drosophila melanogaster.

Phenotypic plasticity is known to enhance population persistence, facilitate adaptive evolution and initiate novel phenotypes in novel environments. How plasticity can contribute or hinder adaptation to different environments hinges on its genetic architecture. Even though plasticity in many traits is genetically controlled, whether and how plasticity's genetic architecture might change in novel environments is still unclear. Because much of gene expression can be environmentally influenced, each environment may trigger different sets of genes that influence a trait. Using a quantitative trait loci (QTL) approach, we investigated the genetic basis of plasticity in a classic functional trait, alcohol dehydrogenase (ADH) activity in D. melanogaster, across both historical and novel alcohol environments. Previous research in D. melanogaster has also demonstrated that ADH activity is plastic in response to alcohol concentration in substrates used by both adult flies and larvae. We found that across all environments tested, ADH activity was largely influenced by a single QTL encompassing the Adh-coding gene and its known regulatory locus, delta-1. After controlling for the allelic variation of the Adh and delta-1 loci, we found additional but different minor QTLs in the 0 and 14% alcohol environments. In contrast, we discovered no major QTL for plasticity itself, including the Adh locus, regardless of the environmental gradients. This suggests that plasticity in ADH activity is likely influenced by many loci with small effects, and that the Adh locus is not environmentally sensitive to dietary alcohol.

Identification of two novel Hessian fly resistance genes H35 and H36 in a hard winter wheat line SD06165.

Two new Hessian fly resistance QTLs (H35 and H36) and tightly linked SNP markers were identified in a US hard winter wheat SD06165. Hessian fly (HF), Mayetiola destructor (Say), is one of the most destructive pests in wheat (Triticum aestivum L.) worldwide. Growing resistant cultivars is the most effective approach to minimize Hessian fly damage. To identify new quantitative trait loci (QTLs) for HF resistance, a recombinant inbred line population was developed by crossing HF resistant wheat line SD06165 to a susceptible line OK05312. The population was genotyped with 1709 single-nucleotide polymorphisms (SNPs) generated from genotyping-by-sequencing and phenotyped for HF resistance in greenhouses. Two novel QTLs for HF resistance were identified from SD06165. The major QTL, designated as H35, was closely linked to SNP marker SDOKSNP7679 on chromosome 3BS that explained 23.8% and 36.0% of the phenotypic variations; the minor QTL, designated as H36, was flanked by SNP markers SDOKSNP1618 and SDOKSNP8089 on chromosome 7AS and explained 8.5% and 13.1% of the phenotypic variation in the two experiments. Significant interaction was detected between the two QTLs. Seventeen SNPs that tightly link to H35 and eight SNPs that tightly link to H36 were converted to kompetitive allele specific polymerase chain reaction markers for selecting these QTLs in breeding programs.

Genetic mapping and genomic selection for maize stalk strength

BackgroundMaize is one of the most important staple crops and is widely grown throughout the world. Stalk lodging can cause enormous yield losses in maize production. However, rind penetrometer resistance (RPR), which is recognized as a reliable measurement to evaluate stalk strength, has been shown to be efficient and useful for improving stalk lodging-resistance. Linkage mapping is an acknowledged approach for exploring the genetic architecture of target traits. In addition, genomic selection (GS) using whole genome markers enhances selection efficiency for genetically complex traits. In the present study, two recombinant inbred line (RIL) populations were utilized to dissect the genetic basis of RPR, which was evaluated in seven growth stages.ResultsThe optimal stages to measure stalk strength are the silking phase and stages after silking. A total of 66 and 45 quantitative trait loci (QTL) were identified in each RIL population. Several potential candidate genes were predicted according to the maize gene annotation database and were closely associated with the biosynthesis of cell wall components. Moreover, analysis of gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway further indicated that genes related to cell wall formation were involved in the determination of RPR. In addition, a multivariate model of genomic selection efficiently improved the prediction accuracy relative to a univariate model and a model considering RPR-relevant loci as fixed effects.ConclusionsThe genetic architecture of RPR is highly genetically complex. Multiple minor effect QTL are jointly involved in controlling phenotypic variation in RPR. Several pleiotropic QTL identified in multiple stages may contain reliable genes and can be used to develop functional markers for improving the selection efficiency of stalk strength. The application of genomic selection to RPR may be a promising approach to accelerate breeding process for improving stalk strength and enhancing lodging-resistance.

Identification and mapping of quantitative trait loci (QTL) and epistatic QTL for salinity tolerance at seedling stage in traditional aromatic short grain rice landrace Kolajoha (Oryza sativa L.) of Assam, India

Salinity stress is the most prominent stress impacting rice productivity worldwide. In the past, several quantitative trait loci (QTLs) for salinity tolerance had been identified in rice, however their utilization in rice breeding programs is largely confounded due to the unwanted linkage drag associated with the QTL region. Thus, it is strongly desirable to delimit the QTL region to a least possible chromosomal interval minimising any unwanted association. Addressing this, we have evaluated 68 recombinant inbred lines (RILs) derived from a cross between a salinity tolerant parent ‘Kolajoha’ and a salinity sensitive parent ‘Ranjit’ for identification of QTL(s) involved in imparting salinity tolerance at seedling stage. Genotyping by sequencing approach (GBS) was followed for SNP identification at genome wide scale. Around 3649 SNPs were identified by GBS method initially at 20% minor allele frequency. After filtering of SNPs with polymorphism with less than 10–15% of missing data, a total of 1248 SNPs were mapped to 1247 recombination points and the genetic map was constructed with a total map length of 1201.21 cM and resolution of 0.95 cM between markers. For 10 traits, a total of 23 additive QTLs were identified of which only 1 was a major QTL and 22 were minor QTLs. The average QTL interval size is about 2945 kb. Epistatic QTL mapping had identified one pair of QTLs that contribute significantly in the phenotypic variation of traits among the RILs. Total 1895 genes were identified in the QTL intervals, majority of them are located in Chr1 of rice genome between 22.09 and 38.29 Mb region. Although, this region is not very narrow, some of the genes falling in this region can be utilized for validation of QTLs in future. One differentially methylated region was found to be colocalized within the QTL intervals determined in Chr2 which indicates their potential role in epigenetic modifications in improving stress tolerance in rice.

Quantitative phenotyping of shell suture strength in walnut (Juglans regia L.) enhances precision for detection of QTL and genome-wide association mapping.

Walnut shell suture strength directly impacts the ability to maintain shell integrity during harvest and processing, susceptibility to insect damage and other contamination, and the proportion of kernel halves recovered during cracking. Suture strength is therefore an important breeding objective. Here, two methods of phenotyping this trait were investigated: 1) traditional, qualitative and rather subjective scoring on an interval scale by human observers, and; 2) quantitative and continuous measurements captured by a texturometer. The aim of this work was to increase the accuracy of suture strength phenotyping and to then apply two mapping approaches, quantitative trait loci (QTL) mapping and genome wide association (GWAS) models, in order to dissect the genetic basis of the walnut suture trait. Using data collected on trees within the UC Davis Walnut Improvement Program (n = 464), the genetic correlation between the texturometer method and qualitatively scored method was high (0.826). Narrow sense heritability calculated using quantitative measurements was 0.82. A major QTL for suture strength was detected on LG05, explaining 34% of the phenotypic variation; additionally, two minor QTLs were identified on LG01 and LG11. All three QTLs were confirmed with GWAS on corresponding chromosomes. The findings reported in this study are relevant for application towards a molecular breeding program in walnut.

Effectiveness of multigenerational transfer of Sumai 3 Fusarium head blight resistance in hard red spring wheat breeding populations

Several quantitative trait loci (QTL) have been identified for Fusarium head blight (FHB) resistance in the cultivar Sumai 3. Wheat breeders need to know which Sumai 3 loci are present in derived lines used as parents for effective marker-assisted selection for genetic improvement. This study was conducted to identify the loci in Sumai 3 derived parents that contribute FHB resistance in breeding populations. Three doubled haploid (DH) populations utilizing Sumai 3 derived parents, ND3085, ND744, and Alsen, were evaluated during 2007 and 2008 in FHB nurseries near Carman, MB, Ottawa, ON and Charlottetown, PE. The percentage of incidence, severity, Fusarium-damaged kernels (FDK), and deoxynivalenol (DON) accumulation were measured, and FHB index calculated. DNA markers at six FHB resistance loci detected in Sumai 3 were evaluated on the populations. For each trait, a t test was applied to means of observations pooled by parental type of each marker to determine which loci contributed to resistance. The alleles at 3BS and 5AS most frequently contributed to Type I and Type II FHB resistance, as well as to reduced FDK and DON in all three populations. Markers revealed resistance on 3BS and 5AS in Alsen, ND3085, and ND744, on 3BSc, 4D, and 6BS in ND744, on 4D in ND3085, and on 6BS in Alsen. In some environments, the susceptible parent Infinity contributed minor QTL on 2D, 3BSc, and 6BS. Likewise, Helios contributed minor QTL on 5AS and 6BS.

Narrowing Down a Major QTL Region Conferring Pod Fiber Contents in Yardlong Bean (Vigna unguiculata), a Vegetable Cowpea.

Yardlong bean (Vigna unguiculata (L.) Walp. ssp. sesquipedalis), a subgroup of cowpea, is an important vegetable legume crop of Asia where its young pods are consumed in both fresh and cooked forms. Pod fiber contents (cellulose, hemicellulose and lignin) correlates with pod tenderness (softness/hardness) and pod shattering. In a previous study using populations derived from crosses between yardlong bean and wild cowpea (V. unguiculata ssp. unguiculata var. spontanea), three major quantitative trait loci (QTLs), qCel7.1, qHem7.1 and qLig7.1, controlling these fibers were identified on linkage group 7 (cowpea chromosome 5) and are co-located with QTLs for pod tenderness and pod shattering. The objective of this study was to identify candidate gene(s) controlling the pod fiber contents. Fine mapping for qCel7.1, qHem7.1 and qLig7.1 was conducted using F2 and F2:3 populations of 309 and 334 individuals, respectively, from the same cross combination. New DNA markers were developed from cowpea reference genome sequence and used for fine mapping. A QTL analysis showed that in most cases, each pod fiber content was controlled by one major and one minor QTLs on the LG7. The major QTLs for cellulose, hemicellulose and lignin in pod were always mapped to the same regions or close to each other. In addition, a major QTL for pod shattering was also located in the region. Although there were several annotated genes relating to pod fiber contents in the region, two genes including Vigun05g266600 (VuBGLU12) encoding a beta glucosidase and Vigun05g273500 (VuMYB26b) encoding a transcription factor MYB26 were identified as candidate genes for the pod fiber contents and pod shattering. Function(s) of these genes in relation to pod wall fiber biosynthesis and pod shattering was discussed.

Genome-Wide Mapping of Adult Plant Resistance to Leaf Rust and Stripe Rust in CIMMYT Wheat Line Arableu#1.

Leaf (brown) rust (LR) and stripe (yellow) rust (YR), caused by Puccinia triticina and P. striiformis f. sp. tritici, respectively, significantly reduce wheat production worldwide. Disease-resistant wheat varieties offer farmers one of the most effective ways to manage these diseases. The common wheat (Triticum aestivum L.) Arableu#1, developed by the International Maize and Wheat Improvement Center and released as Deka in Ethiopia, shows susceptibility to both LR and YR at the seedling stage but a high level of adult plant resistance (APR) to the diseases in the field. We used 142 F5 recombinant inbred lines (RILs) derived from Apav#1 × Arableu#1 to identify quantitative trait loci (QTLs) for APR to LR and YR. A total of 4,298 genotyping-by-sequencing markers were used to construct a genetic linkage map. The study identified four LR resistance QTLs and six YR resistance QTLs in the population. Among these, QLr.cim-1BL.1/QYr.cim-1BL.1 was located in the same location as Lr46/Yr29, a known pleiotropic resistance gene. QLr.cim-1BL.2 and QYr.cim-1BL.2 were also located on wheat chromosome 1BL at 37 cM from Lr46/Yr29 and may represent a new segment for pleiotropic resistance to both rusts. QLr.cim-7BL is likely Lr68 given its association with the tightly linked molecular marker cs7BLNLRR. In addition, QLr.cim-3DS, QYr.cim-2AL, QYr.cim-4BL, QYr.cim-5AL, and QYr.cim-7DS are probably new resistance loci based on comparisons with published QTLs for resistance to LR and YR. Our results showed the diversity of minor resistance QTLs in Arableu#1 and their role in conferring near-immune levels of APR to both LR and YR, when combined with the pleiotropic APR gene Lr46/Yr29.

High Density Mapping of Quantitative Trait Loci Conferring Gluten Strength in Canadian Durum Wheat.

Gluten strength is one of the factors that determine the end-use quality of durum wheat and is an important breeding target for this crop. To characterize the quantitative trait loci (QTL) controlling gluten strength in Canadian durum wheat cultivars, a population of 162 doubled haploid (DH) lines segregating for gluten strength and derived from cv. Pelissier × cv. Strongfield was used in this study. The DH lines, parents, and controls were grown in 3 years and two seeding dates in each year and gluten strength of grain samples was measured by sodium dodecyl sulfate (SDS)-sedimentation volume (SV). With a genetic map created by genotyping the DH lines using the Illumina Infinium iSelect Wheat 90K SNP (single nucleotide polymorphism) chip, QTL contributing to gluten strength were detected on chromosome 1A, 1B, 2B, and 3A. Two major and stable QTL detected on chromosome 1A (QGlu.spa-1A) and 1B (QGlu.spa-1B.1) explaining 13.7–18.7% and 25.4–40.1% of the gluten strength variability respectively were consistently detected over 3 years, with the trait increasing alleles derived from Strongfield. Putative candidate genes underlying the major QTL were identified. Two novel minor QTL (QGlu.spa-3A.1 and QGlu.spa-3A.2) with the trait increasing allele derived from Pelissier were mapped on chromosome 3A explaining up to 8.9% of the phenotypic variance; another three minor QTL (QGlu.spa-2B.1, QGlu.spa-2B.2, and QGlu.spa-2B.3) located on chromosome 2B explained up to 8.7% of the phenotypic variance with the trait increasing allele derived from Pelissier. QGlu.spa-2B.1 is a new QTL and has not been reported in the literature. Multi-environment analysis revealed genetic (QTL) × environment interaction due to the difference of effect in magnitude rather than the direction of the QTL. Eleven pairs of digenic epistatic QTL were identified, with an epistatic effect between the two major QTL of QGlu.spa-1A and QGlu.spa-1B.1 detected in four out of six environments. The peak SNPs and SNPs flanking the QTL interval of QGlu.spa-1A and QGlu.spa-1B.1 were converted to Kompetitive Allele Specific PCR (KASP) markers, which can be deployed in marker-assisted breeding to increase the efficiency and accuracy of phenotypic selection for gluten strength in durum wheat. The QTL that were expressed consistently across environments are of great importance to maintain the gluten strength of Canadian durum wheat to current market standards during the genetic improvement.

Fine-mapping of qTGW2, a quantitative trait locus for grain weight in rice (Oryza sativa L.).

BackgroundGrain weight is a grain yield component, which is an integrated index of grain length, width and thickness. They are controlled by a large number of quantitative trait loci (QTLs). Besides major QTLs, minor QTLs play an essential role. In our previous studies, QTL analysis for grain length and width was performed using a recombinant inbred line population derived from rice cross TQ/IRBB lines. Two major QTLs were detected, which were located in proximity to GS3 and GW5 that have been cloned. In the present study, QTLs for grain weight and shape were identified using rice populations that were homozygous at GS3 and GW5.MethodNine populations derived from the indica rice cross TQ/IRBB52 were used. An F10:11population named W1, consisting of 250 families and covering 16 segregating regions, was developed from one residual heterozygote (RH) in the F7generation of Teqing/IRBB52. Three near isogenic line (NIL)-F2 populations, ZH1, ZH2 and ZH3 that comprised 205, 239 and 234 plants, respectively, were derived from three RHs in F10:11. They segregated the target QTL region in an isogenic background. Two NIL populations, HY2 and HY3, were respectively produced from homozygous progeny of the ZH2 and ZH3 populations. Three other NIL-F2 populations, Z1, Z2 and Z3, were established using three RHs having smaller heterozygous segments. QTL analysis for 1000-grain weight (TGW), grain length (GL), grain width (GW), and length/width ratio (LWR) was conducted using QTL IciMapping and SAS procedure with GLM model.ResultA total of 27 QTLs distributed on 12 chromosomes were identified. One QTL cluster, qTGW2/qGL2/qGW2 located in the terminal region of chromosome 2, were selected for further analysis. Two linked QTLs were separated in region Tw31911−RM266. qGL2 was located in Tw31911−Tw32437 and mainly controlled GL and GW. The effects were larger on GL than on GW and the allelic directions were opposite. qTGW2 was located in Tw35293−RM266 and affected TGW, GL and GW with the same allelic direction. Finally, qTGW2 was delimited within a 103-kb region flanked by Tw35293 and Tw35395.ConclusionqTGW2 with significant effects on TGW, GL and GW was validated and fine-mapped using NIL and NIL-F2 populations. These results provide a basis for map-based cloning of qTGW2 and utilization of qTGW2 in the breeding of high-yielding rice varieties.

Construction of a single nucleotide polymorphism marker based QTL map and validation of resistance loci to bacterial wilt caused by Ralstonia solanacearum species complex in tomato

Bacterial wilt (BW), caused by Ralstonia solanacearum species complex is one of the major biotic factors limiting tomato production in the humid tropics. Pyramiding of resistance genes through marker-assisted selection is an efficient way to develop durable BW resistant cultivars. Tomato line ‘Hawaii 7996’ (H7996) is a stable and robust resistance source against various strains of the species complex. Major BW resistance quantitative trait loci (QTLs) Bwr-12 and Bwr-6, and several minor or strain specific QTLs have been coarse-mapped in this line, but none has been fine-mapped and validated. The objective of the current study was to construct a high density genetic map using single-nucleotide polymorphism (SNP) markers derived from genotyping-by-sequencing, fine-map Bwr-12 and Bwr-6 and determine the effects of these QTLs using a near isogenic line (NIL) population. A high density genetic map using 1604 SNP markers with an average distance of 0.82 cM was developed for 188 F9 recombinant inbred lines derived from the cross H7996 × WVa700. A total of seven QTLs associated with BW resistance to race 1-phylotype I (R. pseudosolanacearum) or/and race 3-phylotype II (R. solanacearum) strains were located on chromosomes 6 (Bwr-6.1, 6.2, 6.3 and 6.4) and 12 (Bwr-12.1, Bwr-12.2 and Bwr-12.3) with logarithm of odds (LOD) scores of 6.2–15.6 and 6.2–31.1, explaining 14.2–33.4% and 15.9–53.9% of the total phenotypic variation contributed from H7996, respectively. To validate the genetic effects of the two QTL regions, a set of 80 BC3F3 NILs containing different sections of Bwr-6 with or without Bwr-12 was phenotyped for disease severity after challenge with either race 1-phylotype I Pss4 or race 3-phylotype II Pss1632 BW strains over two seasons. Bwr-6.1 specific to Pss4 and Bwr-6.3 specific to Pss1632 were mapped to an interval of 5.0 cM (P < 0.05) between 6_33,444,000_SLM6-47 and 6_33,868,000_SLM6-124 SNP marker, and to 2.7 cM (P < 0.01) between positions 6_35,949,000 _SLM6-107 to 6_36,750,000_SLM6-82 marker, respectively. In addition, the specific effect of Bwr-12 for resistance to Pss4 (LOD score of 5.8-16.1, P < 0.01) was confirmed.

Quantitative trait loci analysis of potato tuber greening

A conversion of amyloplasts into chloroplasts in the potato tuber after light exposure is known as tuber greening and is one of the major causes of tuber loss. We report here the first mapping of the factors affecting tuber greening in potato. We used an F1 mapping population of diploid potatoes and DArTseq™ markers to construct a genetic map. The individuals of the mapping population, parents and standards were phenotyped for two tuber greening parameters: external tuber greening and internal greening depth on 0–5 scales in three years 2015, 2016 and 2018. The results were used for the analysis of Quantitative Trait Loci (QTLs) by an interval QTL mapping. Two most important QTLs were covering large regions of chromosomes VII and X and had the strongest effect on both greening parameters in data sets obtained in particular years and in the mean data set. Variance observed in the mean tuber greening could be ascribed in 16.9% to the QTL on chromosome VII and in 23.4% to the QTL on chromosome X. The QTL on chromosome VII explained 13.1%, while the QTL on chromosome X explained up to 17.7% of the variance in the mean tuber greening depth. Additional, minor QTLs were year- and/or trait-specific. The QTLs on chromosomes VII and X determine big parts of the observed tuber greening variation and should be investigated further in order to identify the genes underlying their effects but also should be taken into account when selecting non-greening potato lines in the breeding process.

MAJOR EFFECT QTL ON CHROMOSOME 3 CONFERRING MAIZE RESISTANCE TO SUGARCANE MOSAIC VIRUS

The Sugarcane mosaic virus (SCMV), a maize pathogen epidemic worldwide, is the causal agent of common mosaic, one of the most important viral diseases in Brazil. In this study, we mapped and characterized quantitative trait loci (QTL) conferring resistance to SCMV in a maize population consisting of 127 F2:3 families from the cross between two Brazilian maize inbred lines, L18 (resistant) × L19 (susceptible). Field trials were carried out in two years to evaluate the F2:3 families according to a resistance score after artificial inoculation. QTLs were detected via composite interval mapping, using a linkage map based on 82 SSRs, 3 CAPS and 296 SNPs. The heritability ranged from 73.68 to 95.16% and SCMV resistance QTLs were consistently identified on chromosomes 1 and 3, showing minor and major effects, respectively. The major QTL on chromosome 3 explained a large proportion of the genetic variance, being 50 and 70% in year 1 and 2, respectively, while the minor QTL on chromosome 1 explained 11 and 8% in year 1 and 2, respectively. The SNP marker co-localized with the major QTL peak on chromosome 3 and its right flanking marker are positioned inside the predicted gene GRMZM2G122443 encoding a glucosidase II, and the left flanking marker inside the GRMZM2G140537 that encodes a protein tyrosine kinase. Moreover, within this QTL region there are also the GRMZM2G160902 and GRMZM2G122481 predicted genes, encoding a bZIP transcription factor and a cytochrome C oxidase, respectively. The colocalization with this major effect QTL suggests a putative involvement of these candidate genes with maize responses to SCMV resistance, but further functional studies are required for such validation. Our results provide resistance source and genomic target for marker-assisted breeding aiming the development of maize resistant cultivars to SCMV.

Genome-Wide Identification of QTLs for Grain Protein Content Based on Genotyping-by-Resequencing and Verification of qGPC1-1 in Rice.

To clarify the genetic mechanism underlying grain protein content (GPC) and to improve rice grain qualities, the mapping and cloning of quantitative trait loci (QTLs) controlling the natural variation of GPC are very important. Based on genotyping-by-resequencing, a total of 14 QTLs were detected with the Huanghuazhan/Jizi1560 (HHZ/JZ1560) recombinant inbred line (RIL) population in 2016 and 2017. Seven of the fourteen QTLs were repeatedly identified across two years. Using three residual heterozygote-derived populations, a stably inherited QTL named as qGPC1-1 was validated and delimited to a ~862 kb marker interval JD1006–JD1075 on the short arm of chromosome 1. Comparing the GPC values of the RIL population determined by near infrared reflectance spectroscopy (NIRS) and Kjeldahl nitrogen determination (KND) methods, high correlation coefficients (0.966 and 0.983) were observed in 2016 and 2017. Furthermore, 12 of the 14 QTLs were identically identified with the GPC measured by the two methods. These results indicated that instead of the traditional KND method, the rapid and easy-to-operate NIRS was suitable for analyzing a massive number of samples in mapping and cloning QTLs for GPC. Using the gel-based low-density map consisted of 208 simple sequence repeat (SSR) and insert/deletion (InDel) markers, the same number of QTLs (fourteen) were identified in the same HHZ/JZ1560 RIL population, and three QTLs were repeatedly detected across two years. More stably expressed QTLs were identified based on the genome resequencing, which might be attributed to the high-density map, increasing the detection power of minor QTLs. Our results are helpful in dissecting the genetic basis of GPC and improving rice grain qualities through molecular assisted selection.

Genetic analysis of resistance to bacterial leaf spot in the heirloom lettuce cultivar Reine des Glaces

Bacterial leaf spot (BLS) is a disease that affects lettuce (Lactuca sativa L.) worldwide. The disease is caused by the bacterium Xanthomonas campestris pathovar vitians (Xcv), which exclusively infects lettuce and is particularly devastating in warm humid climates. Reine des Glaces (RG), an old Batavia-type cultivar, exhibited an uninvestigated partial resistance to Xcv. Quantitative trait loci (QTLs) were analyzed using two recombinant inbred line (RIL) populations derived from RG × Eruption and RG × Delsay using three isolates collected in California and Canada, each representing a different race, and an isolate collected in France. A major QTL was identified in linkage group 2 in both populations; additional, minor QTLs were also detected in other linkage groups. The major QTL collocates with the Xanthomonas resistance 1 (Xar1) and Xanthomonas campestris vitians resistance (Xcvr) genes that had previously been identified using RIL populations derived from Salinas 88 × La Brillante and PI 358001-1 × Tall Guzmaine. RG provides another resistance resource for combating BLS using data provided by this study for marker-assisted selection.