Quantitative Trait Loci Markers Research Articles

Registration of PR1572‐19 and PR1572‐26 pinto bean germplasm lines with broad resistance to rust, BGYMV, BCMV, and BCMNV

AbstractCommon bean rust, Bean golden yellow mosaic virus (BGYMV), Bean common mosaic virus (BCMV), and Bean common mosaic necrosis virus (BCMNV) are devastating diseases of dry bean (Phaseolus vulgaris L.) in Central America and the Caribbean. The development of dry bean cultivars with enhanced levels of genetic resistance to these and other diseases is an important goal of the University of Puerto Rico (UPR) and other dry bean breeding programs in Central America and the Caribbean. PR1572‐19 (Reg. no. GP‐308, PI 692976) and PR1572‐26 (Reg. no. GP‐307, PI 692975) are multiple virus‐ and rust‐resistant pinto bean germplasm lines adapted to the humid tropics that were developed and released cooperatively in 2019 by the UPR Agricultural Experiment Station, the Instituto Dominicano de Investigaciones Agropecuarias y Forestales, and the USDA–ARS. Both PR1572‐19 and PR1572‐26 possess the bgm‐1 gene for resistance to BGYMV, the I and bc‐3 loci that provide broad resistance to all strains of BCMV and BCMNV in the United States and the Caribbean, and the Ur‐3 and Ur‐11 loci that confer comprehensive resistance to all known races of the bean rust pathogen. PR1572‐26 also has the SW12 quantitative trait locus marker associated with resistance to BGYMV. PR1572‐19 and PR1572‐26 produced mean seed yields similar to the check cultivar ‘Santa Fe’ in trials conducted in Puerto Rico and mean seed yields comparable to the pinto cultivar ‘La Paz’ in the Cooperative Dry Bean Nursery conducted in Puerto Rico. Both lines should serve as useful sources of resistance to BGYMV, BCMV, BCMNV, and bean rust for common beans of the Durango race that includes the pinto and great northern market classes.

QTL Mapping and Marker Development for Tolerance to Sulfur Phytotoxicity in Melon (Cucumis melo).

Elemental sulfur is an effective, inexpensive fungicide for many foliar pathogens, but severe phytotoxicity prohibits its use on many melon varieties. Sulfur phytotoxicity causes chlorosis and necrosis of leaf tissue, leading to plant death in the most sensitive lines, while other varieties have little to no damage. A high-density, genotyping-by-sequencing (GBS)-based genetic map of a recombinant inbred line (RIL) population segregating for sulfur tolerance was used for a quantitative trait loci (QTL) mapping study of sulfur phytotoxicity in melon. One major (qSulf-1) and two minor (qSulf-8 and qSulf-12) QTL were associated with sulfur tolerance in the population. The development of Kompetitive Allele-Specific PCR (KASP) markers developed across qSulf-1 decreased the QTL interval from 239 kb (cotyledons) and 157 kb (leaves) to 97 kb (both tissues). The markers were validated for linkage to sulfur tolerance in a set of melon cultivars. These KASP markers can be incorporated into melon breeding programs for introgression of sulfur tolerance into elite melon germplasm.

Uniparental Inheritance of Salinity Tolerance and Beneficial Phytochemicals in Rice

Salinity stress is one of the most problematic constraints to significantly reduce rice productivity. The Saltol QTL (quantitative trait locus) has been known as one among many principal genes/QTLs responsible for salinity tolerance in rice. However, the introgression of the Saltol QTL from the donor (male) into the recipient (female) cultivars induces great recessions from the progeny generation, which results in heavy fieldwork and greater cost and time required for breeding. In this study, the F1 generation of the cross TBR1 (female cultivar, salinity tolerant) × KD18 (male cultivar, salinity susceptible) was preliminarily treated with N-methyl-N-nitrosourea (MNU) to induce the mutants M1. Results on physiological traits show that all the M2 (self-pollinated from M1) and M3 (self-pollinated from M2) individuals obtain salinity tolerant levels as the recurrent TBR1. Twelve SSR (simple sequence repeat) markers involved in the Saltol QTL (RM493, RM562, RM10694, RM10720, RM10793, RM10852, RM13197, RM201, RM149, RM508, RM587, and RM589) and other markers related to yield-contributing traits and disease resistance, as well as water and nitrogen use, have efficacy that is polymorphic. The phenotype and genotype analyses indicate that the salinity tolerant Saltol QTL, growth parameter, grain yield and quality, pest resistance, water and nitrogen use efficacy, and beneficial phytochemicals including antioxidants, momilactone A (MA) and momilactone B (MB) are uniparentally inherited from the recurrent (female) TBR1 cultivar and stabilized in the M2 and M3 generations. Further MNU applications should be examined to induce the uniparental inheritance of other salinity tolerant genes such as OsCPK17, OsRMC, OsNHX1, OsHKT1;5 to target rice cultivars. However, the mechanism of inducing this novel uniparental inheritance for salinity tolerance by MNU application needs elaboration.

RNA-seq Reveals Differentially Expressed Genes between Two indica Inbred Rice Genotypes Associated with Drought-Yield QTLs

Two indica inbred rice lines, IR64, a drought-sensitive, and Apo, a moderately drought-tolerant genotype, were exposed to non- (control or unstressed) and water-stress treatments. Leaf samples collected at an early flowering stage were sequenced by RNA-seq. Reads generated were analyzed for differential expression (DE) implementing various models in baySeq to capture differences in genome-wide transcriptional response under contrasting water regimes. IR64, the drought-sensitive variety consistently exhibited a broader transcriptional response while Apo showed relatively modest transcriptional changes under water-stress conditions across all models implemented. Gene ontology (GO) and KEGG pathway analyses of genes revealed that IR64 showed enhancement of functions associated with signal transduction, protein binding and receptor activity. Apo uniquely showed significant enrichment of genes associated with an oxygen binding function and peroxisome pathway. In general, IR64 exhibited more extensive molecular re-programming, presumably, a highly energy-demanding route to deal with the abiotic stress. Several of these differentially expressed genes (DEGs) were found to co-localize with QTL marker regions previously identified to be associated with drought-yield response, thus, are the most promising candidate genes for further studies.

Tagging, Mapping and Identification of the QTLs Associated With Phosphorous Utilization for Phosphorous- Limiting Soils in Tropical Maize

Phosphorus (P) deficiency is one of the major abiotic constraints leading to low maize productivity. Twenty- four SSR markers sequence information was obtained from maize databases (MaizeGDB). These SSRs were selected from targeted regions of the maize genome linked to Quantitative Trait Loci (QTLs) for Phosphorus utilization efficiency. The mapping population consisting 67 F2 maize plants, were obtained from advancing a bi-parental cross between an efficient line (L354) and an in-efficient maize line (L585). Out of 24 SSRs five identified polymorphic SSR markers were subsequently used for genotyping the 67 tagged F2 plants. Sixty seven F2:3 maize families were used for QTL localization. Inclusive composite interval mapping (ICIM) analysis identified seven QTLs associated with phosphorus utilization on chromosome 5. All the mapped QTLs were more than 5 cM from the nearest molecular marker utilized in the study. The closest mapped QTL, PeSB-5, 7 associated with shoot biomass was at 11.7 cM, from the nearest marker umc2136 on chromosome 5. Therefore, there is need to saturate the map which may prove useful to identify and test several markers near the mapped QTLs. The identified markers could serve as potential SSR markers for QTLs associated with phosphorous utilization for phosphorous- limiting soils in tropical maize.

Genomic Prediction Accuracy of Seven Breeding Selection Traits Improved by QTL Identification in Flax.

Molecular markers are one of the major factors affecting genomic prediction accuracy and the cost of genomic selection (GS). Previous studies have indicated that the use of quantitative trait loci (QTL) as markers in GS significantly increases prediction accuracy compared with genome-wide random single nucleotide polymorphism (SNP) markers. To optimize the selection of QTL markers in GS, a set of 260 lines from bi-parental populations with 17,277 genome-wide SNPs were used to evaluate the prediction accuracy for seed yield (YLD), days to maturity (DTM), iodine value (IOD), protein (PRO), oil (OIL), linoleic acid (LIO), and linolenic acid (LIN) contents. These seven traits were phenotyped over four years at two locations. Identification of quantitative trait nucleotides (QTNs) for the seven traits was performed using three types of statistical models for genome-wide association study: two SNP-based single-locus (SS), seven SNP-based multi-locus (SM), and one haplotype-block-based multi-locus (BM) models. The identified QTNs were then grouped into QTL based on haplotype blocks. For all seven traits, 133, 355, and 1208 unique QTL were identified by SS, SM, and BM, respectively. A total of 1420 unique QTL were obtained by SS+SM+BM, ranging from 254 (OIL, LIO) to 361 (YLD) for individual traits, whereas a total of 427 unique QTL were achieved by SS+SM, ranging from 56 (YLD) to 128 (LIO). SS models alone did not identify sufficient QTL for GS. The highest prediction accuracies were obtained using single-trait QTL identified by SS+SM+BM for OIL (0.929 ± 0.016), PRO (0.893 ± 0.023), YLD (0.892 ± 0.030), and DTM (0.730 ± 0.062), and by SS+SM for LIN (0.837 ± 0.053), LIO (0.835 ± 0.049), and IOD (0.835 ± 0.041). In terms of the number of QTL markers and prediction accuracy, SS+SM outperformed other models or combinations thereof. The use of all SNPs or QTL of all seven traits significantly reduced the prediction accuracy of traits. The results further validated that QTL outperformed high-density genome-wide random markers, and demonstrated that the combined use of single and multi-locus models can effectively identify a comprehensive set of QTL that improve prediction accuracy, but further studies on detection and removal of redundant or false-positive QTL to maximize prediction accuracy and minimize the number of QTL markers in GS are warranted.

Validation of growth-related quantitative trait loci markers in different Exopalaemon carinicauda families for marker-assisted selection.

We detected growth-related QTL and associated markers from the backcross population of Exopalaemon carinicauda in the previous study. Based on our previous study, the 47 SNP markers associated with candidate growth trait QTL were selected to analyze the association between these markers and body weight (BW), body length and abdominal segment length traits in four different populations including wild population, a full-sib family, a half-sib family and a backcross population for evaluating their potential application of marker-assisted selection in E.carinicauda. The general linear model (GLM) and mixed linear model were applied and the associations between SNP loci and three growth-related traits verified. The results showed that the Marker79268 and Marker100644 were significantly associated with the BW trait in more than three populations by the GLM method. The Marker100644 was significantly associated with BW in the full-sib family, half-sib family and backcross populations by the GLM and mixed linear model methods. Our findings will provide useful SNP markers to go forward to improve growth performance through more refined marker-assisted selection in E.carinicauda.

Fiber Quality Improvement in Upland Cotton (Gossypium hirsutum L.): Quantitative Trait Loci Mapping and Marker Assisted Selection Application.

Genetic improvement in fiber quality is one of the main challenges for cotton breeders. Fiber quality traits are controlled by multiple genes and are classified as complex quantitative traits, with a negative relationship with yield potential, so the genetic gain is low in traditional genetic improvement by phenotypic selection. The availability of Gossypium genomic sequences facilitates the development of high-throughput molecular markers, quantitative trait loci (QTL) fine mapping and gene identification, which helps us to validate candidate genes and to use marker assisted selection (MAS) on fiber quality in breeding programs. Based on developments of high density linkage maps, QTLs fine mapping, marker selection and omics, we have performed trait dissection on fiber quality traits in diverse populations of upland cotton. QTL mapping combined with multi-omics approaches such as, RNA sequencing datasets to identify differentially expressed genes have benefited the improvement of fiber quality. In this review, we discuss the application of molecular markers, QTL mapping and MAS for fiber quality improvement in upland cotton.

Use of a Bayesian model including QTL markers increases prediction reliability when test animals are distant from the reference population

Relatedness between reference and test animals has an important effect on the reliability of genomic prediction for test animals. Because genomic prediction has been widely applied in practical cattle breeding and bulls have been selected according to genomic breeding value without progeny testing, the sires or grandsires of candidates might not have phenotypic information and might not be in the reference population when the candidates are selected. The objective of this study was to investigate the decreasing trend of the reliability of genomic prediction given distant reference populations, using genomic best linear unbiased prediction (GBLUP) and Bayesian variable selection models with or without including the quantitative trait locus (QTL) markers detected from sequencing data. The data used in this study consisted of 22,242 bulls genotyped using the 54K SNP array from EuroGenomics. Among them, 1,444 Danish bulls born from 2006 to 2010 were selected as test animals. Different reference populations with varying relationships to test animals were created according to pedigree-based relationships. The reference individuals having a relationship with one or more test animals higher than 0.4 (scenario ρ < 0.4), 0.2 (ρ < 0.2), or 0.1 (ρ < 0.1, where ρ = relationship coefficient) were removed from reference sets; these represented the distance between reference and test animals being 2 generations, 3 generations, and 4 generations, respectively. Imputed whole-genome sequencing data of bulls from Denmark were used to conduct a genome-wide association study (GWAS). A small number of significant variants (QTL markers) from the GWAS were added to the array data. To compare the effects of different models, the basic GBLUP model, a Bayesian selection variable model, a GBLUP model with 2 components of genetic effects, and a Bayesian model with pooled array data and QTL markers were used for estimating genomic estimated breeding values (GEBV) of test animals. The reliability of genomic prediction decreased when the test animals were more generations away from the reference population. The reliability of genomic prediction was 0.461 for 1 generation away and 0.396 for 3 generations away, with the same number of individuals in the reference set, using a GBLUP model with chip markers only. The results showed that using the Bayesian method and QTL markers improved the reliability of genomic prediction in all scenarios of relationship between test and reference animals, in a range of 1.3% and 65.1% (4 generations away with only 841 individuals in the reference set). However, most gains were for predictions of milk yield and fat yield. There was little improvement for predictions of protein yield and mastitis, and no improvement for prediction of fertility, except for scenario ρ < 0.1, in which there was a large improvement for predictions of all traits. On the other hand, models including more than 10% polygenic effect decreased prediction reliability when the relationship between test and reference animals was distant.

Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat

BackgroundPlant height is an important selection target since it is associated with yield potential, stability and particularly with lodging resistance in various environments. Rapid and cost-effective estimation of plant height from airborne devices using a digital surface model can be integrated with academic research and practical wheat breeding programs. A bi-parental wheat population consisting of 198 doubled haploid lines was used for time-series assessments of progress in reaching final plant height and its accuracy was assessed by quantitative genomic analysis. UAV-based data were collected at the booting and mid-grain fill stages from two experimental sites and compared with conventional measurements to identify quantitative trait loci (QTL) underlying plant height.ResultsA significantly high correlation of R2 = 0.96 with a 5.75 cm root mean square error was obtained between UAV-based plant height estimates and ground truth observations at mid-grain fill across both sites. Correlations for UAV and ground-based plant height data were also very high (R2 = 0.84–0.85, and 0.80–0.83) between plant height at the booting and mid-grain fill stages, respectively. Broad sense heritabilities were 0.92 at booting and 0.90–0.91 at mid-grain fill across sites for both data sets. Two major QTL corresponding to Rht-B1 on chromosome 4B and Rht-D1 on chromosome 4D explained 61.3% and 64.5% of the total phenotypic variations for UAV and ground truth data, respectively. Two new and stable QTL on chromosome 6D seemingly associated with accelerated plant growth was identified at the booting stage using UAV-based data. Genomic prediction accuracy for UAV and ground-based data sets was significantly high, ranging from r = 0.47–0.55 using genome-wide and QTL markers for plant height. However, prediction accuracy declined to r = 0.20–0.31 after excluding markers linked to plant height QTL.ConclusionThis study provides a fast way to obtain time-series estimates of plant height in understanding growth dynamics in bread wheat. UAV-enabled phenotyping is an effective, high-throughput and cost-effective approach to understand the genetic basis of plant height in genetic studies and practical breeding.

Introgression of resistance to Rhopalosiphum padi L. from wild barley into cultivated barley facilitated by doubled haploid and molecular marker techniques

Key messageLong-term pre-breeding using Hordeum vulgare ssp. spontaneum as a donor of bird cherry-oat aphid resistance has resulted in agronomically improved resistance sources of barley along with easy-to-use molecular markers.Bird cherry-oat aphid (Rhopalosiphum padi L.) is a pest and a virus vector in barley to which there are no bred-resistant cultivars. The present study describes how resistance from Hordeum vulgare ssp. spontaneum has been introgressed in cultivated barley via five successive crosses with the same cultivar Lina (BC) and in parallel with other more modern barley cultivars. Most of the selections for resistance are based on measurements of individual aphid growth in the laboratory. This very slow phenotyping method has been complemented by molecular marker evaluation and application in part of the breeding material. Doubled haploid production in each generation has been crucial for more precise selection of lines with the quantitatively expressed resistance. A field trial of selected “BC3”-generation lines essentially confirmed the laboratory results, so did genotyping of the whole pedigree of parents and selected “BC2” and “BC4” offspring lines. The Infinium iSelect 50 K SNP assay confirmed relationships between lines and discerned several new markers for a resistance QTL on chromosome 2H.

Development of Sakon Nakhon Rice Variety for Blast Resistance through Marker Assisted Backcross Breeding

The Sakon Nakhon (SKN) rice cultivar is non-photosensitive, rich in aroma, and an excellent choice for cooking quality; which adapts well to both upland and lowland conditions. Furthermore, it has been adopted by Thailand’s sugarcane growers, as it has proved fit for an upland crop preceding the sugarcane cropping system. However, SKN is very susceptible to blast disease caused by Pyricularia oryzae. The purpose of this study was to breed SKN for blast resistance, using marker-assisted backcrossing, together with phenotypic selection. The breeding population was constructed by crossing the SKN (recurrent) with the RD6 introgression line (donor), which contained four blast resistant quantitative trait loci (QTLs). Franking microsatellite markers for blast resistance QTLs on chromosomes 1, 2, 11 and 12 were used for selection through BC2F2. Thirteen BC2F3 selected lines were evaluated under greenhouse conditions, and seven lines of BC2F4 were evaluated against blast, along with their agronomic traits, under field conditions (upland and lowland). SKN 39-10-19-29-12 and SKN 39-10-19-29-13 presented high resistance to leaf and neck blast; and were non-photosensitive, with the same agronomic traits as the SKN. This study successfully demonstrates the improvement of the recommended SKN variety blast resistance, while maintaining similar agronomic traits.

KASPspoon: an invitro and in silico PCR analysis tool for high-throughput SNP genotyping.

MotivationFine mapping becomes a routine trial following quantitative trait loci (QTL) mapping studies to shrink the size of genomic segments underlying causal variants. The availability of whole genome sequences can facilitate the development of high marker density and predict gene content in genomic segments of interest. Correlations between genetic and physical positions of these loci require handling of different experimental genetic data types, and ultimately converting them into positioning markers using a routine and efficient tool.ResultsTo convert classical QTL markers into KASP assay primers, KASPspoon simulates a PCR by running an approximate-match searching analysis on user-entered primer pairs against the provided sequences, and then comparing in vitro and in silico PCR results. KASPspoon reports amplimers close to or adjoining genes/SNPs/simple sequence repeats and those that are shared between in vitro and in silico PCR results to select the most appropriate amplimers for gene discovery. KASPspoon compares physical and genetic maps, and reports the primer set genome coverage for PCR-walking. KASPspoon could be used to design KASP assay primers to convert QTL acquired by classical molecular markers into high-throughput genotyping assays and to provide major SNP resource for the dissection of genotypic and phenotypic variation. In addition to human-readable output files, KASPspoon creates Circos configurations that illustrate different in silico and in vitro results.Availability and implementationCode available under GNU GPL at (http://www.ageri.sci.eg/index.php/facilities-services/ageri-softwares/kaspspoon).Supplementary information Supplementary data are available at Bioinformatics online.

QTL Mapping and Marker Identification for Sex-Determining: Indicating XY Sex Determination System in the Swimming Crab (Portunus trituberculatus).

Sex determination is an important area of research, which has always had an intriguing aspect in evolutionary and developmental biology. Quantitative trait locus (QTL) mapping for sex will be helpful in clarifying the sex determination system. In this study, the sex QTL mapping of the swimming crab (Portunus trituberculatus) was performed based on a high-density linkage map, and a highly significant QTL specifically mapped on a single linkage group (LG) was firstly identified (LG24, LOD > 14). Twenty markers in the QTL region showed significant associations with sex by association analysis, of which heterogametic genotypes in males supported the XY sex determination mechanism. Two sex-specific markers at the family level were identified via segregation distortion analysis, which were known to be the most closely linked to the sex of P. trituberculatus. Based on sex marker sequences (Marker3840, Marker20320, and Marker10494), three potential sex-related genes were identified, and the quantitative real-time PCR results suggested that these genes were important in spermatogenesis or sex characteristics in males. Our results will contribute to the fine-mapping of sex-determining genes and clarify the sex determination mechanism of P. trituberculatus.

Validation of growth-related quantitative trait loci markers in turbot (Scophthalmus maximus) families as a step toward marker assisted selection

Turbot (Scophthalmus maximus) is a valuable flatfish with current selection programs to increase growth rate in the fifth generation. Disentangling the genetic architecture of growth traits has biological and productive relevance. Growth-related quantitative trait loci (QTL) and associated markers have been previously reported in turbot. Here, we tested the performance of 39 markers associated with three growth-related traits (body weight (BW), body length (BL) and condition factor (FK)) in 18 families for their potential application in marker assisted selection (MAS) in this species. A cost-effective selective genotyping approach was developed by checking the statistical power of small samples at the extreme of the phenotypic distributions. Associations between growth traits and markers were performed using two statistical approaches (contingency chi-square tests and stepwise regression analysis) to identify the most robust set of markers. Twenty markers were detected by both methods, mostly linked to previously reported growth-related QTL and encompassing 11 linkage groups (LGs). The stepwise regression analysis revealed that a subset of seven markers explained nearly 40% and 60% of the phenotypic variation at genotypic and allelic level, respectively, for BW and BL. Seven markers for BW and BL and other two for FK showed association at population level, when all family data were pooled. Validated markers might be useful to go a step forward to improve growth performance through more refined MAS, and as physical anchors for identifying causal genes underpinning growth traits in turbot.

Identification and validation of genomic regions influencing kernel zinc and iron in maize

Key messageGenome-wide association study (GWAS) on 923 maize lines and validation in bi-parental populations identified significant genomic regions for kernel-Zinc and-Iron in maize.Bio-fortification of maize with elevated Zinc (Zn) and Iron (Fe) holds considerable promise for alleviating under-nutrition among the world’s poor. Bio-fortification through molecular breeding could be an economical strategy for developing nutritious maize, and hence in this study, we adopted GWAS to identify markers associated with high kernel-Zn and Fe in maize and subsequently validated marker-trait associations in independent bi-parental populations. For GWAS, we evaluated a diverse maize association mapping panel of 923 inbred lines across three environments and detected trait associations using high-density Single nucleotide polymorphism (SNPs) obtained through genotyping-by-sequencing. Phenotyping trials of the GWAS panel showed high heritability and moderate correlation between kernel-Zn and Fe concentrations. GWAS revealed a total of 46 SNPs (Zn-20 and Fe-26) significantly associated (P ≤ 5.03 × 10−05) with kernel-Zn and Fe concentrations with some of these associated SNPs located within previously reported QTL intervals for these traits. Three double-haploid (DH) populations were developed using lines identified from the panel that were contrasting for these micronutrients. The DH populations were phenotyped at two environments and were used for validating significant SNPs (P ≤ 1 × 10−03) based on single marker QTL analysis. Based on this analysis, 11 (Zn) and 11 (Fe) SNPs were found to have significant effect on the trait variance (P ≤ 0.01, R2 ≥ 0.05) in at least one bi-parental population. These findings are being pursued in the kernel-Zn and Fe breeding program, and could hold great value in functional analysis and possible cloning of high-value genes for these traits in maize.

Cattle Tick Rhipicephalus microplus-Host Interface: A Review of Resistant and Susceptible Host Responses.

Ticks are able to transmit tick-borne infectious agents to vertebrate hosts which cause major constraints to public and livestock health. The costs associated with mortality, relapse, treatments, and decreased production yields are economically significant. Ticks adapted to a hematophagous existence after the vertebrate hemostatic system evolved into a multi-layered defense system against foreign invasion (pathogens and ectoparasites), blood loss, and immune responses. Subsequently, ticks evolved by developing an ability to suppress the vertebrate host immune system with a devastating impact particularly for exotic and crossbred cattle. Host genetics defines the immune responsiveness against ticks and tick-borne pathogens. To gain an insight into the naturally acquired resistant and susceptible cattle breed against ticks, studies have been conducted comparing the incidence of tick infestation on bovine hosts from divergent genetic backgrounds. It is well-documented that purebred and crossbred Bos taurus indicus cattle are more resistant to ticks and tick-borne pathogens compared to purebred European Bos taurus taurus cattle. Genetic studies identifying Quantitative Trait Loci markers using microsatellites and SNPs have been inconsistent with very low percentages relating phenotypic variation with tick infestation. Several skin gene expression and immunological studies have been undertaken using different breeds, different samples (peripheral blood, skin with tick feeding), infestation protocols and geographic environments. Susceptible breeds were commonly found to be associated with the increased expression of toll like receptors, MHC Class II, calcium binding proteins, and complement factors with an increased presence of neutrophils in the skin following tick feeding. Resistant breeds had higher levels of T cells present in the skin prior to tick infestation and thus seem to respond to ticks more efficiently. The skin of resistant breeds also contained higher numbers of eosinophils, mast cells and basophils with up-regulated proteases, cathepsins, keratins, collagens and extracellular matrix proteins in response to feeding ticks. Here we review immunological and molecular determinants that explore the cattle tick Rhipicephalus microplus-host resistance phenomenon as well as contemplating new insights and future directions to study tick resistance and susceptibility, in order to facilitate interventions for tick control.

Identification of quantitative trait loci markers using diversity arrays technology for polyphenol oxidase activity in hexaploid wheat

ABSTRACTPolyphenol oxidase (PPO) causes undesirable darkening in wheat products such as Asian noodles. The inheritance of PPO activity was investigated in a doubled haploid (DH) population derived from a hybrid between a null PPO genotype VAW08-A17 and Australian wheat variety QALBis. The observed genetic ratio indicated three genes controlling high PPO activity. Quantitative trait loci (QTL) mapping was performed in this DH population using diversity arrays technology (DArT) to genotype the population. Three highly significant QTLs that control PPO activity were identified on chromosomes 2AL, 2BS and 2DL with additive mode of action. Three closely associated DArT markers, wPt-7024, wPt-0094 and wPt-2544, were identified corresponding to these QTLs. Collectively, these loci explained 74% of the observed variation in PPO activity. Identification of DArT markers associated with PPO genes will accelerate the development of null or very low PPO cultivars that exhibit reduced time-dependent darkening of Asian noodles.

Development and Validation of KASP-SNP Markers for QTL Underlying Resistance to Stripe Rust in Common Wheat Cultivar P10057.

Stripe rust (Puccinia striiformis f. sp. tritici) is among the most important diseases of wheat (Triticum aestivum L.) globally. Utilization of adult plant resistance (APR) constitutes a key tool for maintaining protection against this disease. The CIMMYT wheat cultivar P10057 displayed a high level of APR to stripe rust in germplasm evaluation in field environments. To clarify the genetic basis and identify quantitative trait loci (QTLs) involved in stripe rust resistance in P10057, three wheat populations were used: 150 F5:6 recombinant inbred lines (RILs) derived from the cross Mingxian 169 × P10057, and 161 and 140 F2:3 lines from Avocet S × P10057 and Zhengmai 9023 × P10057, respectively. These three populations were evaluated for infection type (IT) and disease severity (DS) in Shaanxi, Gansu, and Sichuan during the 2014-15 and 2015-16 cropping seasons. Genotyping was performed with Kompetitive Allelic Specific PCR (KASP) and simple sequence repeat (SSR) markers linked to the resistance loci. Using QTL analysis, two genomic regions associated with resistance were found on chromosome arms 2BS and 3BS, respectively. These two stable QTLs, designated Qyrlov.nwafu-2BS and Qyrlov.nwafu-3BS, were detected across all environments and explained average 22.6 to 31.6% and 21.3 to 32.3% of stripe rust severity phenotypic variation, respectively. Qyrlov.nwafu-2BS may be the resistance allele derived from CIMMYT germplasm and Qyrlov.nwafu-3BS likely corresponds to the locus Sr2/Lr27/Yr30/Pbc. The KASP markers IWA5377, IWA2674, and IWA5830 linked to QYrlov.nwafu-2BS and IWB57990 and IWB6491 linked to Qyrlov.nwafu-3BS were reliable for marker-assisted selection (MAS) in the Zhengmai 9023 × P10057 population. These QTLs with KASP markers are expected to contribute in developing wheat cultivars with improved stripe rust resistance.

QTL mapping and marker analysis of main stem height and the first lateral branch length in peanut (Arachis hypogaea L.)

Main stem height (MSH) and the first lateral branch length (LBL) of peanut (Arachis hypogaea L.) are important traits affecting plant shape and yield. Identification of quantitative trait loci (QTLs) related to these two traits, the prediction and cloning of candidate genes, and identification of plant height-related molecular markers are the basis for analysis of the molecular genetic mechanism of plant shape in peanut. In this study, a population of 151 recombinant inbred lines from a single seed, derived from a cross between variety 79266 (P1) and its variant progeny D893 (P2), was used to construct a peanut genetic map. The map consisted of 231 simple sequence repeat markers in 23 linkage groups, had a total length of 905.18 cM with average and minimum marker intervals of 3.92 and 0.1 cM, respectively. There were 11 and 16 QTLs detected in six environments for MSH and LBH with 6.26–22.53 and 5.89–21.63% phenotypic variation explained (PVE), respectively. Seven QTLs were detected in two or more environments: 3 QTLs for MSH (including Qmsh-14-3) with 7.66–22.53% PVE, and 4 QTLs for LBL (including Qllb-11-1) with 6.12–21.63% PVE. Qmsh-14-3 was steadily detected in five environments, localized between two markers, ARS376 and SEQ4G02, exhibited a genetic distance of 0.59–2.59 and 4.11–6.11 cM from the two markers, respectively. Qllb-11-1 was steadily detected in five environments, localized between two markers, ARS203 and AHS1413, exhibited a genetic distance of 1.06–3.06 and 0.23–2.23 cM from the two markers, respectively. There were 220 germplasm accessions used to detect the relationship between genotype and phenotypic values of traits at the marker loci ARS376 and SEQ4G02, average values of MSH and LBL were significantly higher for germplasm with the P1 compared to the P2 genotype. Determination of the marker loci ARS203 and AHS1413 indicated that average values of LBL were greater in germplasm with the P1 than the P2 genotype. The results provide references for fine mapping of QTLs for MSH and LBL, as well as breeding optimum plant-types in peanut.