Quantitative Trait Loci Alleles Research Articles

Fine mapping of a QTL on bovine chromosome 6 using imputed full sequence data suggests a key role for the group-specific component (GC) gene in clinical mastitis and milk production.

BackgroundClinical mastitis is an inflammation of the mammary gland and causes significant costs to dairy production. It is unfavourably genetically correlated to milk production, and, thus, knowledge of the mechanisms that underlie these traits would be valuable to improve both of them simultaneously through breeding. A quantitative trait locus (QTL) that affects both clinical mastitis and milk production has recently been fine-mapped to around 89 Mb on bovine chromosome 6 (BTA6), but identification of the gene that underlies this QTL was not possible due to the strong linkage disequilibrium between single nucleotide polymorphisms (SNPs) within this region. Our aim was to identify the gene and, if possible, the causal polymorphism(s) responsible for this QTL through association analysis of high-density SNPs and imputed full sequence data in combination with analyses of transcript and protein levels of the identified candidate gene.ResultsAssociations between SNPs and the studied traits were strongest for SNPs that were located within and immediately upstream of the group-specific component (GC) gene. This gene encodes the vitamin D-binding protein (DBP) and has multiple roles in immune defense and milk production. A 12-kb duplication that was identified downstream of this gene covered its last exon and segregated with the QTL allele that is associated with increased mastitis susceptibility and milk production. However, analyses of GC mRNA levels on the available samples revealed no differences in expression between animals having or lacking this duplication. Moreover, we detected no differences in the concentrations of DBP and its ligand vitamin D between the animals with different GC genotypes that were available for this study.ConclusionsOur results suggest GC as the gene that underlies the QTL for clinical mastitis and milk production. However, since only healthy animals were sampled for transcription and expression analyses, we could not draw any final conclusion on the absence of quantitative differences between animals with different genotypes. Future studies should investigate GC RNA expression and protein levels in cows with different genotypes during an infection.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0257-2) contains supplementary material, which is available to authorized users.

Contributions of linkage disequilibrium and co-segregation information to the accuracy of genomic prediction.

BackgroundTraditional genomic prediction models using multiple regression on single nucleotide polymorphisms (SNPs) genotypes exploit associations between genotypes of quantitative trait loci (QTL) and SNPs, which can be created by historical linkage disequilibrium (LD), recent co-segregation (CS) and pedigree relationships. Results from field data analyses show that prediction accuracy is usually much higher for individuals that are close relatives of the training population than for distantly related individuals. A possible reason is that historical LD between QTL and SNPs is weak and, for close relatives, prediction accuracy of SNP models is mainly contributed by pedigree relationships and CS. Information from pedigree relationships decreases fast over generations and only contributes to within-family prediction. Information from CS is affected by family structures and effective population size, and can have a substantial contribution to prediction accuracy when modeled explicitly.ResultsIn this study, a method to explicitly model CS was developed by following the transmission of putative QTL alleles using allele origins at SNPs. Bayesian hierarchical models that combine information from LD and CS (LD-CS model) were developed for genomic prediction in pedigree populations. Contributions of LD and CS information to prediction accuracy across families and generations without retraining were investigated in simulated half-sib datasets and deep pedigrees with different recent effective population sizes, respectively. Results from half-sib datasets showed that when historical LD between QTL and SNPs is low, accuracy of the LD model decreased when the training data size is increased by adding independent sire families, but accuracies from the CS and LD-CS models increased and plateaued rapidly. Results from deep pedigree datasets show that the LD model had high accuracy across generations only when historical LD between QTL and SNPs was high. Modeling CS explicitly resulted in higher accuracy than the LD model across generations when the mating design generated many close relatives.ConclusionsOur results suggest that modeling CS explicitly improves accuracy of genomic prediction when historical LD between QTL and SNPs is low. Modeling both LD and CS explicitly is expected to improve accuracy when recent effective population size is small, or when the training data include many independent families.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0255-4) contains supplementary material, which is available to authorized users.

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

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

Mapping of Fusarium Head Blight Resistance Quantitative Trait Loci in Winter Wheat Cultivar NC‐Neuse

Fusarium head blight (FHB), primarily caused by Fusarium graminearum, can significantly reduce the grain quality of wheat (Triticum aestivum L.) due to mycotoxin contamination. The objective of this study was to identify quantitative trait loci (QTL) for FHB resistance in the moderately resistant soft red winter wheat cultivar NC‐Neuse. A total of 170 recombinant inbred lines (RILs) from a cross between NC‐Neuse and the susceptible cultivar AGS 2000 were evaluated in inoculated, mist‐irrigated field nurseries. The lines were evaluated for FHB incidence (INC), severity (SEV), Fusarium‐damaged kernels (FDK), and deoxynivalenol (DON) content in seven environments between 2011 and 2014. A 3,419 cM linkage map was developed based on 1839 simple sequence repeat (SSR), diversity array technology (DArT), and single nucleotide polymorphism (SNP) markers. Seven FHB resistance QTL on chromosomes 1A, 1B, 1D, 2A, 4A, 5B, and 6A were mapped. The QTL alleles conferring resistance on 1A, 1B, 2A, 4A, and 6A originated from NC‐Neuse, while the alleles associated with resistance on 1D and 5B originated from AGS 2000. Quantitative trait loci effects ranged from 9 to 12% for INC, from 6 to 11% for SEV, from 8 to 20% for FDK, and from 6 to 18% for DON. The QTL on 5B co‐localized with the Vrn‐B1 locus. Kompetitive Allele‐Specific PCR (KASP) assays were developed for each NC‐Neuse QTL region. A preliminary test using these assays on recent Uniform Southern Winter Wheat Nursery (USWWN) entries indicated Qfhb.nc‐1A, Qfhb.nc‐1B, and Qfhb.nc‐6A as likely the best candidates for use in marker‐assisted selection.

Dissection of the qTGW1.1 region into two tightly-linked minor QTLs having stable effects for grain weight in rice.

BackgroundMost agronomical traits of crop species are complex traits controlled by multiple genes and affected by environmental factors. While considerable efforts have been made to fine-map and clone major quantitative trait loci (QTLs) for yield-related traits in rice, it is not until recently that the attention has been paid to minor QTLs. Following previous dissection of QTLs for grain weight and grain size in a 12-Mb interval on the long arm of chromosome 1 in rice, this study targeted at one putative QTL region for a more precise mapping and for analyzing the genotype-by-environment interaction of minor QTLs.ResultsFour BC2F10 plants of the indica rice cross ZS97///ZS97//ZS97/MY46 were selected. They carried overlapped heterozygous segments that jointly covered the entire putative region for qTGW1.1 detected previously. Four sets of near isogenic lines (NILs) were developed from selfing progenies of the four plants. Each NIL set consisted of 32 ZS97 homozygous lines and 32 MY46 homozygous lines that differed in the corresponding heterozygous region. They were grown in two locations having distinct ecological conditions and measured for 1000-grain weight, grain length and grain width. Two QTLs were separated in an 835.2-kb interval flanked by DNA markers Wn28447 and RM11569. They both showed consistent effects across the two environments. The qTGW1.1a located within the 120.4-kb interval Wn28447 − RM11543 significantly affect all the three traits with the enhancing allele derived from ZS97, showing a stronger influence on grain weight than on grain length and width. The qTGW1.1b located in the 521.8-kb interval RM11554 − RM11569 significantly affect grain weight and length with the enhancing allele derived from MY46, having a stronger influence on grain length than on grain weight. Consistent performance of the two QTLs was confirmed in a validation experiment using five NIL-F2 populations segregated for either qTGW1.1a or qTGW1.1b.ConclusionSeparation of closely-linked QTLs having small effects is achievable in the absence of major-QTL segregation. Minor QTLs for complex traits could act consistently in diverse environments, offering the potential of pyramiding beneficial alleles of multiple minor QTLs through marker-assisted selection.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0410-5) contains supplementary material, which is available to authorized users.

Association mapping for cold tolerance in two large maize inbred panels.

BackgroundBreeding for cold tolerance in maize promises to allow increasing growth area and production in temperate zones. The objective of this research was to conduct genome-wide association analyses (GWAS) in temperate maize inbred lines and to find strategies for pyramiding genes for cold tolerance. Two panels of 306 dent and 292 European flint maize inbred lines were evaluated per se and in testcrosses under cold and control conditions in a growth chamber. We recorded indirect measures for cold tolerance as the traits number of days from sowing to emergence, relative leaf chlorophyll content or quantum efficiency of photosystem II. Association mapping for identifying genes associated to cold tolerance in both panels was based on genotyping with 49,585 genome-wide single nucleotide polymorphism (SNP) markers.ResultsWe found 275 significant associations, most of them in the inbreds evaluated per se, in the flint panel, and under control conditions. A few candidate genes coincided between the current research and previous reports. A total of 47 flint inbreds harbored the favorable alleles for six significant quantitative trait loci (QTL) detected for inbreds per se evaluated under cold conditions, four of them had also the favorable alleles for the main QTL detected from the testcrosses. Only four dent inbreds (EZ47, F924, NK807 and PHJ40) harbored the favorable alleles for three main QTL detected from the evaluation of the dent inbreds per se under cold conditions. There were more QTL in the flint panel and most of the QTL were associated with days to emergence and ΦPSII.ConclusionsThese results open new possibilities to genetically improve cold tolerance either with genome-wide selection or with marker assisted selection.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-016-0816-2) contains supplementary material, which is available to authorized users.

Multi-Population Selective Genotyping to Identify Soybean [Glycine max (L.) Merr.] Seed Protein and Oil QTLs.

Plant breeders continually generate ever-higher yielding cultivars, but also want to improve seed constituent value, which is mainly protein and oil, in soybean [Glycine max (L.) Merr.]. Identification of genetic loci governing those two traits would facilitate that effort. Though genome-wide association offers one such approach, selective genotyping of multiple biparental populations offers a complementary alternative, and was evaluated here, using 48 F2:3 populations (n = ∼224 plants) created by mating 48 high protein germplasm accessions to cultivars of similar maturity, but with normal seed protein content. All F2:3 progeny were phenotyped for seed protein and oil, but only 22 high and 22 low extreme progeny in each F2:3 phenotypic distribution were genotyped with a 1536-SNP chip (ca. 450 bimorphic SNPs detected per mating). A significant quantitative trait locus (QTL) on one or more chromosomes was detected for protein in 35 (73%), and for oil in 25 (52%), of the 48 matings, and these QTL exhibited additive effects of ≥ 4 g kg–1 and R2 values of 0.07 or more. These results demonstrated that a multiple-population selective genotyping strategy, when focused on matings between parental phenotype extremes, can be used successfully to identify germplasm accessions possessing large-effect QTL alleles. Such accessions would be of interest to breeders to serve as parental donors of those alleles in cultivar development programs, though 17 of the 48 accessions were not unique in terms of SNP genotype, indicating that diversity among high protein accessions in the germplasm collection is less than what might ordinarily be assumed.

Molecular genetic analysis of grain protein content and flour whiteness degree using RILs in common wheat.

Grain protein content (GPC) and flour whiteness degree (FWD) are important qualitative traits in common wheat. Quantitative trait locus (QTL) mapping for GPC and FWD was conducted using a set of 131 recombinant-inbred lines derived from the cross 'Chuan 35050 × Shannong 483' in six environmental conditions. A total of 22 putative QTLs (nine GPC and 13 FWD) were identified on 12 chromosomes with individual QTL explaining 4.5-34.0% phenotypic variation. Nine QTLs (40.9%) were detected in two or more environments. The colocated QTLs were on chromosomes 1B and 4B. Among the QTLs identified for GPC, QGpc.sdau-4A from the parent Shannong 483 represented some important favourable QTL alleles. QGpc.sdau-2A.1 and QFwd.sdau-2A.1 had a significant association with both GPC and FWD. The markers detected on top of QTL regions could be potential targets for marker-assisted selection.

Genetic control of protein content and sedimentation volume in European winter wheat cultivars.

Breeding of bread wheat in the last decades has maintained a high baking quality despite the intensive selection for grain yield. The quality trait sedimentation volume but not protein content is mainly controlled by the Glu - A1, Glu - B1, Glu - D1, Gli - B1 , and Pinb - D1 loci which are differentially used in varieties from different European origins. Protein content and sedimentation volume are two important quality traits in wheat breeding. In this study, we used a panel of 407 European winter wheat cultivars to dissect the genetic architecture of both traits and to assess the potential of genomics-assisted breeding. All lines were phenotyped in multi-location field trials, genotyped by a genotyping-by-sequencing approach, and assessed for the alleles at the Glu-A1, Glu-B1, Glu-D1, Gli-B1, and Pinb-D1 candidate loci. Our analyses revealed no effect of the candidate loci on protein content, but a strong effect on sedimentation volume, with Glu-B1 and Gli-B1 explaining 24.6 and 19.5% of the genotypic variance, respectively. The genome-wide scan identified three quantitative trait loci (QTL) for protein content which jointly explained only 18.5% of the genotypic variance. In contrast, four QTL were detected for sedimentation volume most likely identifying the Glu-B1 and Gli-B1 candidate loci and explaining approximately 60% of the genotypic variance. We observed differences for both traits between countries of origin of the cultivars, accompanied by corresponding geographic differences in QTL allele frequencies. Furthermore, a genome-wide prediction approach resulted in a higher predictive ability for both traits as compared to marker-assisted selection based on the identified QTL. Taken together, our results illustrate a different genetic architecture of the two quality traits and show the potential of their genomics-assisted improvement.

A high density genetic map and QTL for agronomic and yield traits in Foxtail millet [Setaria italica (L.) P. Beauv

BackgroundFoxtail millet [Setaria italica (L.) P. Beauv.], a crop of historical importance in China, has been adopted as a model crop for studying C-4 photosynthesis, stress biology and biofuel traits. Construction of a high density genetic map and identification of stable quantitative trait loci (QTL) lay the foundation for marker-assisted selection for agronomic traits and yield improvement.ResultA total of 10598 SSR markers were developed according to the reference genome sequence of foxtail millet cultivar ‘Yugu1’. A total of 1013 SSR markers showing polymorphism between Yugu1 and Longgu7 were used to genotype 167 individuals from a Yugu1 × Longgu7 F2 population, and a high density genetic map was constructed. The genetic map contained 1035 loci and spanned 1318.8 cM with an average distance of 1.27 cM between adjacent markers. Based on agronomic and yield traits identified in 2 years, 29 QTL were identified for 11 traits with combined analysis and single environment analysis. These QTL explained from 7.0 to 14.3 % of phenotypic variation. Favorable QTL alleles for peduncle length originated from Longgu7 whereas favorable alleles for the other traits originated from Yugu1 except for qLMS6.1.ConclusionsNew SSR markers, a high density genetic map and QTL identified for agronomic and yield traits lay the ground work for functional gene mapping, map-based cloning and marker-assisted selection in foxtail millet.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2628-z) contains supplementary material, which is available to authorized users.

Ancestral QTL Alleles from Wild Emmer Wheat Improve Drought Resistance and Productivity in Modern Wheat Cultivars.

Wild emmer wheat (Triticum turgidum ssp. dicoccoides) is considered a promising source for improving stress resistances in domesticated wheat. Here we explored the potential of selected quantitative trait loci (QTLs) from wild emmer wheat, introgressed via marker-assisted selection, to enhance drought resistance in elite durum (T. turgidum ssp. durum) and bread (T. aestivum) wheat cultivars. The resultant near-isogenic lines (BC3F3 and BC3F4) were genotyped using SNP array to confirm the introgressed genomic regions and evaluated in two consecutive years under well-watered (690–710 mm) and water-limited (290–320 mm) conditions. Three of the introgressed QTLs were successfully validated, two in the background of durum wheat cv. Uzan (on chromosomes 1BL and 2BS), and one in the background of bread wheat cvs. Bar Nir and Zahir (chromosome 7AS). In most cases, the QTL x environment interaction was validated in terms of improved grain yield and biomass—specifically under drought (7AS QTL in cv. Bar Nir background), under both treatments (2BS QTL), and a greater stability across treatments (1BL QTL). The results provide a first demonstration that introgression of wild emmer QTL alleles can enhance productivity and yield stability across environments in domesticated wheat, thereby enriching the modern gene pool with essential diversity for the improvement of drought resistance.

Integration of genetic, genomic and transcriptomic information identifies putative regulators of adventitious root formation in Populus.

BackgroundAdventitious roots (AR) develop from tissues other than the primary root, in a process physiologically regulated by phytohormones. Adventitious roots provide structural support and contribute to water and nutrient absorption, and are critical for commercial vegetative propagation of several crops. Here we quantified the number of AR, root architectural traits and root biomass in cuttings from a pseudo-backcross population of Populus deltoides and Populus trichocarpa. Quantitative trait loci (QTL) mapping and whole-transcriptome analysis of individuals with alternative QTL alleles for AR number were used to identify putative regulators of AR development.ResultsParental individuals and progeny showed extensive segregation for AR developmental traits. Quantitative trait loci for number of AR mapped consistently in the same interval of linkage group (LG) II and LG XIV, explaining 7–10 % of the phenotypic variation. A time series transcriptome analysis identified 26,121 genes differentially expressed during AR development, particularly during the first 24 h after cuttings were harvested. Of those, 1929 genes were differentially regulated between individuals carrying alternative alleles for the two QTL for number of AR, in one or more time point. Eighty-one of these genes were physically located within the QTL intervals for number of AR, including putative homologs of the Arabidopsis genes SUPERROOT2 (SUR2) and TRYPTOPHAN SYNTHASE ALPHA CHAIN (TSA1), both of which are involved in the auxin indole-3-acetic acid (IAA) biosynthesis pathway.ConclusionsThis study suggests the involvement of two genes of the tryptophan-dependent auxin biosynthesis pathway, SUR2 and TSA1, in the regulation of a critical trait for the clonal propagation of woody species. A possible model for this regulation is that poplar individuals that have poor AR formation synthesize auxin indole-3-acetic acid (IAA) primarily through the tryptophan (Trp) pathway. Much of the Trp pathway flux appears to be directed to the synthesis of indole glucosinolates (IG), as suggested by the over-expression of SUR2. Individuals that are efficient in AR formation may utilize alternative (non-Trp) pathways to synthesize IAA, based on the observation that they down-regulate the expression of TSA1, one of the critical steps in the synthesis of tryptophan.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-016-0753-0) contains supplementary material, which is available to authorized users.

Genomic dissection of plant development and its impact on thousand grain weight in barley through nested association mapping.

Flowering time is a key agronomic trait that plays an important role in crop yield. There is growing interest in dissecting the developmental subphases of flowering to better understand and fine-tune plant development and maximize yield. To do this, we used the wild barley nested association mapping (NAM) population HEB-25, comprising 1420 BC1S3 lines, to map quantitative trait loci (QTLs) controlling five developmental traits, plant height, and thousand grain weight. Genome-wide association studies (GWAS) enabled us to locate a total of 89 QTLs that genetically regulate the seven investigated traits. Several exotic QTL alleles proved to be highly effective and potentially useful in barley breeding. For instance, thousand grain weight was increased by 4.5 g and flowering time was reduced by 9.3 days by substituting Barke elite QTL alleles for exotic QTL alleles at the denso/sdw1 and the Ppd-H1 loci, respectively. We showed that the exotic allele at the semi-dwarf locus denso/sdw1 can be used to increase grain weight since it uncouples the negative correlation between shoot elongation and the ripening phase. Our study demonstrates that nested association mapping of HEB-25 can help unravel the genetic regulation of plant development and yield formation in barley. Moreover, since we detected numerous useful exotic QTL alleles in HEB-25, we conclude that the introgression of these wild barley alleles into the elite barley gene pool may enable developmental phases to be specifically fine-tuned in order to maximize thousand grain weight and, potentially, yield in the long term.

Dissection of Genetic Factors underlying Wheat Kernel Shape and Size in an Elite × Nonadapted Cross using a High Density SNP Linkage Map.

Wheat kernel shape and size has been under selection since early domestication. Kernel morphology is a major consideration in wheat breeding, as it impacts grain yield and quality. A population of 160 recombinant inbred lines (RIL), developed using an elite (ND 705) and a nonadapted genotype (PI 414566), was extensively phenotyped in replicated field trials and genotyped using Infinium iSelect 90K assay to gain insight into the genetic architecture of kernel shape and size. A high density genetic map consisting of 10,172 single nucleotide polymorphism (SNP) markers, with an average marker density of 0.39 cM/marker, identified a total of 29 genomic regions associated with six grain shape and size traits; ∼80% of these regions were associated with multiple traits. The analyses showed that kernel length (KL) and width (KW) are genetically independent, while a large number (∼59%) of the quantitative trait loci (QTL) for kernel shape traits were in common with genomic regions associated with kernel size traits. The most significant QTL was identified on chromosome 4B, and could be an ortholog of major rice grain size and shape gene or . Major and stable loci also were identified on the homeologous regions of Group 5 chromosomes, and in the regions of (6A) and (7A) genes. Both parental genotypes contributed equivalent positive QTL alleles, suggesting that the nonadapted germplasm has a great potential for enhancing the gene pool for grain shape and size. This study provides new knowledge on the genetic dissection of kernel morphology, with a much higher resolution, which may aid further improvement in wheat yield and quality using genomic tools.

Analysis of root-knot nematode and fusarium wilt disease resistance in cotton (Gossypium spp.) using chromosome substitution lines from two alien species

Chromosome substitution (CS) lines in plants are a powerful genetic resource for analyzing the contribution of chromosome segments to phenotypic variance. In this study, a series of interspecific cotton (Gossypium spp.) CS lines were used to identify a new germplasm resource, and to validate chromosomal regions and favorable alleles associated with nematode or fungal disease resistance traits. The CS lines were developed in the G. hirsutum L. TM-1 background with chromosome or chromosome segment substitutions from G. barbadense L. Pima 3-79 or G. tomentosum. Root-knot nematode (Meloidogyne incognita) and fusarium wilt (Fusarium oxysporum f. sp. vasinfectum) (races 1 and 4) resistance alleles and quantitative trait loci (QTL) previously placed on cotton chromosomes using SSR markers in two interspecific recombinant inbred line populations were chosen for testing. Phenotypic responses of increased resistance or susceptibility in controlled inoculation and infested field assays confirmed the resistance QTLs, based on substitution with the positive or negative allele for resistance. Lines CS-B22Lo, CS-B04, and CS-B18 showed high resistance to nematode root-galling, confirming QTLs on chromosomes 4 and 22 (long arm) with resistance alleles from Pima 3-79. Line CS-B16 had less fusarium race 1-induced vascular root staining and higher percent survival than the TM-1 parent, confirming a major resistance QTL on chromosome 16. Lines CS-B(17-11) and CS-B17 had high fusarium race 4 vascular symptoms and low survival due to susceptible alleles introgressed from Pima 3-79, confirming the localization on chromosome 17 of an identified QTL with resistance alleles from TM1 and other resistant lines. Analyses validated regions on chromosomes 11, 16, and 17 harboring nematode and fusarium wilt resistance genes and demonstrated the value of CS lines as both a germplasm resource for breeding programs and as a powerful genetic analysis tool for determining QTL effects for disease resistance. CS lines carrying small alien chromosome segments with favorable QTL alleles could be used for effective introgression of biotic stress resistance or many other desirable traits by targeting gene interactions and reducing linkage drag effects.

Linkage disequilibrium, persistence of phase and effective population size estimates in Hereford and Braford cattle.

BackgroundThe existence of moderate to high levels of linkage disequilibrium (LD) between genetic markers and quantitative trait loci (QTL) affecting traits of interest is fundamental for the success of genome-wide association (GWAS) and genomic selection (GS) studies. Knowledge about the extent and the pattern of LD in livestock populations is essential to determine the density of single nucleotide polymorphisms (SNP) required for accurate GWAS and GS. Moreover, observed LD is related to historical effective population sizes (Ne), and can provide insights into the genetic diversity history of populations. Estimates of the consistency of linkage phase across breeds (RH,B) can be used to determine if there is sufficient relationship to use pooled reference populations in multi-breed GS programs. The objective of this study was to estimate LD levels, persistence of phase and effective population size in Hereford and Braford cattle populations sampled in Brazil.ResultsMean LD estimates, measured using the squared correlation of alleles at two loci (r2), obtained between adjacent SNP across all chromosomes were 0.21 ± 0.27 for Herefords (391 samples with 41,241 SNP) and 0.16 ± 0.22 for Brafords (2044 samples and 41,207 SNP). Estimated r2 was > 0.2 and 0.3, respectively, for 34 and 25 % of adjacent markers in Herefords, and 26 and 17 % in Brafords. Estimated Ne for Brafords and Herefords at the current generation was 220 and 153 individuals, respectively. The two breeds demonstrated moderate to strong persistence of phase at all distances (RH,B = 0.53 to 0.97). The largest phase correlations were found in the 0 to 50 Kb bins (RH,B = 0.92 to 0.97). Estimated LD decreased rapidly with increasing distance between SNP, however, useful linkage for GWAS and GS (r2 > 0.2) was found spanning to ~50 Kb.ConclusionsPanels containing about 50,000 and 150,000 SNP markers are necessary to detect minimal levels of LD between adjacent markers that would be useful for GWAS and GS studies to Hereford and Braford breeds, respectively. Markers are expected to be linked to the same QTL alleles in distances < 50 Kb in both populations due to observed high persistence of phase levels.

Genetic dissection of leaf-related traits using 156 chromosomal segment substitution lines

A two-line super-hybrid rice (Oryza sativa L.) variety [Liangyoupei9 (LYP9)] demonstrated superiority over its both parents, viz. elite inbred lines 93-11 and Pei-ai64S (PA64S), as well as other conventional hybrids, and had long been exploited in China. However, the genetic basis of its leaf-related traits, supposed to be an important component for yield potential, remains elusive. Here, initially a set of chromosome segment substitution lines (CSSLs) was constructed, in which the genome of Pei-ai64S has been introgressed into the background of 93-11. This set was developed by marker aided selection, based on 123 polymorphic SSR markers. The introgressed chromosomal segments presented in the 156 CSSLs covered 96.46% of Pei-ai64S genome. Afterwards, the CSSLs were deployed to assess the genetic basis of leaf size (length and width) and chlorophyll content of top three leaves across five different environments. The CSSLs showed transgressive segregation for all of the traits, and significant correlations were detected among most of the traits. A total of 27 quantitative trait loci (QTL) were identified on ten chromosomes, and three QTL cluster affecting related traits were found on chromosome 3, 6, and 8, respectively. Remarkably, two key QTLs, qALW3-1 and qALW3-2, both controlling the antepenultimate leaf width, were identified in all five environments, and their effect were further validated by CSSLs harboring the two QTL alleles. Our results indicate that developing CSSLs is a powerful tool for genetic dissection of quantitative traits. Meanwhile, the QTLs controlling leaf-related traits uncovered here provide useful information for marker-assisted selection in improving the performance of leaf morphology and photosynthetic ability.

Identification of salt tolerance‐improving quantitative trait loci alleles from a salt‐susceptible rice breeding line by introgression breeding

AbstractTo improve salt tolerance of two elite rice varieties, Ce258 and Zhongguangxiang1 (ZGX1), two sets of introgression lines (ILs) each comprising 200 BC1F10 lines derived from a common donor, IR75862, and two recipient parents, Ce258 and ZGX1, were used for mapping of QTLs for four salt tolerance‐related traits at the seedling stage. Although the three parents were susceptible to salt, the two IL populations showed transgressive segregations for salt tolerance with 12 and 8 salt tolerance ILs in the Ce258‐ILs and ZGX1‐ILs. Eighteen main‐effect QTLs were identified for the four traits in the two IL populations, and the IR75862 alleles at most loci showed increased and decreased salt tolerance in the ZGX1 and Ce258 backgrounds, suggesting overwhelming genetic background effects on QTL detection for salt tolerance. The qDSS11 simultaneously detected in the two backgrounds was validated in a F2 population derived from a salt tolerance line and ZGX1. Our results indicated that salt tolerance‐enhancing allele could be identified in the elite susceptible breeding lines and that introgression of the favourable alleles could facilitate the development of superior lines with greater salt tolerance levels.

Using Targeted Resequencing for Identification of Candidate Genes and SNPs for a QTL Affecting the pH Value of Chicken Meat.

Using targeted genetical genomics, a quantitative trait locus (QTL) affecting the initial postmortem pH value of chicken breast muscle (Pectoralis major) on chromosome 1 (GGA1) recently was fine-mapped. Thirteen genes were present in the QTL region of approximately 1 Mb. In this study, 10 birds that were inferred to be homozygous for either the high (QQ) or low (qq) QTL allele were selected for resequencing. After enrichment for 1 Mb around the QTL region, >500 × coverage for the QTL region in each of the 10 birds was obtained. In total 5056 single-nucleotide polymorphisms (SNPs) were identified for which the genotypes were consistent with one of the QTL genotypes. We used custom tools to identify putative causal mutations in the mapped QTL region from these SNPs. Four nonsynonymous SNPs differentiating the two QTL genotype groups were identified within four local genes (PRDX4, EIF2S3, PCYT1B, and E1BTD2). Although these are likely candidate SNPs to explain the QTL effect, 54 additional consensus SNPs were detected within gene-related regions (untranslated regions, splicing sites CpG island, and promoter regions) for the QQ birds and 71 for the qq birds. These could also play a role explaining the observed QTL effect. The results provide an important step for prioritizing among a large amount of candidate mutations and significantly contribute to the understanding of the genetic mechanisms affecting the initial postmortem pH value of chicken muscle.

Patterns of longevity and fecundity at two temperatures in a set of heat-selected recombinant inbred lines of Drosophila melanogaster.

Quantitative trait loci (QTL) were mapped for longevity and fecundity at two temperatures, 20 and 30 °C, in two sets of recombinant inbred lines (RIL) highly differing in thermotolerance. Early fecundity (EF) and longevity showed a negative association between temperatures. For instance, longevity was higher and fecundity was lower in the RIL panel showing higher life span at 30 °C. One X-linked QTL (7B3-12E) co-localized for longevity and EF at 20 °C, with one QTL allele showing a positive additive effect on longevity and a negative effect on EF. The across-RIL genetic correlation between longevity and EF was not significant within each temperature, and most QTL that affect life span have no effect on EF at each temperature. EF and longevity can mostly be genetically uncoupled in the thermotolerance-divergent RIL within each temperature as opposed to between temperatures. QTL were mostly temperature specific, although some trait-specific QTL showed possible antagonistic effects between temperatures.