Pleiotropic Quantitative Trait Loci Research Articles

Genetic dissection of Brassica napus seed vigor after aging.

Stable and novel QTLs that affect seed vigor under different storage durations were discovered, and BnaOLE4, located in the interval of cqSW-C2-3, increased seed vigor after aging. Seed vigor is an important trait in crop breeding; however, the underlying molecular regulatory mechanisms governing this trait in rapeseed remain largely unknown. In the present study, vigor-related traits were analyzed in seeds from a doubled haploid (DH) rapeseed (Brassica napus) population grown in 2 different environments using seeds stored for 7, 5, and 3years under natural storage conditions. A total of 229 quantitative trait loci (QTLs) were identified and were found to explain 3.78%-17.22% of the phenotypic variance for seed vigor-related traits after aging. We further demonstrated that seed vigor-related traits were positively correlated with oil content (OC) but negatively correlated with unsaturated fatty acids (FAs). Some pleiotropic QTLs that collectively regulate OC, FAs, and seed vigor, such as uq.A8, uq.A3-2, uq.A9-2, and uq.C3-1, were identified. The transcriptomic results from extreme pools of DH lines with distinct seed vigor phenotypes during accelerated aging revealed that various biological pathways and metabolic processes (such as glutathione metabolism and reactive oxygen species) were involved in seed vigor. Through integration of QTL analysis and RNA-Seq, a regulatory network for the control of seed vigor was constructed. Importantly, a candidate (BnaOLE4) from cqSW-C2-3 was selected for functional analysis, and transgenic lines overexpressing BnaOLE4 showed increased seed vigor after artificial aging. Collectively, these results provide novel information on QTL and potential candidate genes for molecular breeding for improved seed storability.

Unravelling novel and pleiotropic genes for cannon bone circumference and bone mineral density in Yorkshire pigs.

Leg weakness is a prevalent health condition in pig farms. The augmentation of cannon bone circumference and bone mineral density can effectively improve limb strength in pigs and alleviate leg weakness. This study measured forelimb cannon bone circumference (fCBC) and rear limb cannon bone circumference (rCBC) using an inelastic tapeline and rear limb metatarsal area bone mineral density (raBMD) using a dual-energy X-ray absorptiometry bone density scanner. The samples of Yorkshire castrated boars were genotyped using a 50K single-nucleotide polymorphism (SNP) array. The SNP-chip data were imputed to the level of whole-genome sequencing data (iWGS). This study used iWGS data to perform genome-wide association studies and identified novel significant SNPs associated with fCBC on SSC6, SSC12, and SSC13, rCBC on SSC12 and SSC14, and raBMD on SSC7. Based on the high phenotypic and genetic correlations between CBC and raBMD, multi-trait meta-analysis was performed to identify pleiotropic SNPs. A significant potential pleiotropic quantitative trait locus (QTL) regulating both CBC and raBMD was identified on SSC15. Bayes fine mapping was used to establish the confidence intervals for these novel QTLs with the most refined confidence interval narrowed down to 56kb (15.11 to 15.17Mb on SSC12 for fCBC). Furthermore, the confidence interval for the potential pleiotropic QTL on SSC15 in the meta-analysis was narrowed down to 7.45kb (137.55 to137.56Mb on SSC15). Based on the biological functions of genes, the following genes were identified as novel regulatory candidates for different phenotypes: DDX42, MYSM1, FTSJ3, and MECOM for fCBC; SMURF2, and STC1 for rCBC; RGMA for raBMD. Additionally, RAMP1, which was determined to be located 23.68kb upstream of the confidence interval of the QTL on SSC15 in the meta-analysis, was identified as a potential pleiotropic candidate gene regulating both CBC and raBMD. These findings offered valuable insights for identifying pathogenic genes and elucidating the genetic mechanisms underlying CBC and BMD.

A consistent 100-seed weight QTL with pleiotropy for seed number/plant in soybean (Glycine max L.)

Seed weight and seed number/plant are important determinants of seed yield in soybean (Glycine max L.). A recombinant inbred line (RIL) population of cross EC538828 x JS97-52 was phenotyped for 100-seed weight (100-SW), seed number/plant (SNPP) and seed yield/plant (SYPP) for identifying quantitative trait loci (QTL) governing these traits. Linkage analysis using SSRs from reported QTL hotspots for 100-SW identified a consistent but pleiotropic QTL on chromosome 10. The QTL showed pleiotropy for SNPP with opposite phenotypic effect, while the pleotropic QTL doesn’t affect seed yield in consistent manner.

Amoeba predation of Cryptococcus: A quantitative and population genomic evaluation of the accidental pathogen hypothesis.

The "Amoeboid Predator-Fungal Animal Virulence Hypothesis" posits that interactions with environmental phagocytes shape the evolution of virulence traits in fungal pathogens. In this hypothesis, selection to avoid predation by amoeba inadvertently selects for traits that contribute to fungal escape from phagocytic immune cells. Here, we investigate this hypothesis in the human fungal pathogens Cryptococcus neoformans and Cryptococcus deneoformans. Applying quantitative trait locus (QTL) mapping and comparative genomics, we discovered a cross-species QTL region that is responsible for variation in resistance to amoeba predation. In C. neoformans, this same QTL was found to have pleiotropic effects on melanization, an established virulence factor. Through fine mapping and population genomic comparisons, we identified the gene encoding the transcription factor Bzp4 that underlies this pleiotropic QTL and we show that decreased expression of this gene reduces melanization and increases susceptibility to amoeba predation. Despite the joint effects of BZP4 on amoeba resistance and melanin production, we find no relationship between BZP4 genotype and escape from macrophages or virulence in murine models of disease. Our findings provide new perspectives on how microbial ecology shapes the genetic architecture of fungal virulence, and suggests the need for more nuanced models for the evolution of pathogenesis that account for the complexities of both microbe-microbe and microbe-host interactions.

Mapping QTL for Yield and Its Component Traits Using Wheat (Triticum aestivum L.) RIL Mapping Population from TAM 113 × Gallagher

Understanding genetic architectures of yield and yield-related traits of wheat (Triticum aestivum L.) grown under dryland or irrigated conditions is pivotal for developing modern high-yielding germplasm and cultivars. The objectives of this study were to detect quantitative trait loci (QTL) linked to yield and yield components using a mapping population derived from ‘TAM 113’/‘Gallagher’, including 191 recombinant inbred lines (RILs). The population was grown in McGregor, College Station, and Bushland, Texas, for three consecutive years from 2019 to 2021. A high-density genetic map covering all 21 chromosomes was constructed using a set of 8,075 single nucleotide polymorphisms (SNPs) obtained using genotyping-by-sequencing (GBS). A total of 147 QTLs for 16 yield-related traits were identified, which included 16 QTLs consistently detected in multiple experiments and 8 QTLs that showed pleiotropic effects. Of them, five pleiotropic QTLs overlapped with the consistent QTL. They increased grain yield (YLD) up to 37.64 g m−2, thousand kernel weight (TKW) up to 1.33 g, harvest (HI) up to 0.97%, kernel length up to 0.08 mm, and kernel width up to 0.04 mm with Gallagher alleles and increased YLD up to 22.21 g m−2, kernels spike−1 up to 1.77, TKW up to 1.14 g, and HI up to 3.72% with TAM 113 alleles. One major and consistent QTL on chromosome 2D at 34.4 Mbp overlapped with the major photoperiod gene Ppd-D1 and was affected by multiple traits, including kernel diameter (DIAM), TKW, kernel hardness index (KHI), heading date (HD), and plant height (PH). Another QTL cluster region on 7D between 52 and 66 Mbp, encompassing one consistent and three pleiotropic QTLs. One of the pleiotropic QTLs at 52 Mbp increased YLD up to 24.16 g m−2, HI up to 1%, and DIAM up to 0.03 mm. This study dissected genetic loci associated with yield and yield-related traits, providing valuable information on wheat improvement using marker-assisted selection (MAS).

An intron-located single nucleotide variation of TaGS5-3D is related to wheat grain size through accumulating intron retention transcripts.

Thirty-three stable QTL for 13 yield-related traits across ten environments were identified in the PD34/MY47 RIL population, and a candidate gene TaGS5-3D in Qmt.nwafu.3D was preliminarily identified to affect grain-related traits through accumulation of specific transcripts. Dissecting the genetic basis of yield-related traits is pivotal for improvement of wheat yield potential. In this study, a recombinant inbred line (RIL) population genotyped by SNP markers was used to detect quantitative trait loci (QTL) related to yield-related traits in ten environments. A total of 102 QTL were detected, including 33 environmentally stable QTL and 69 putative QTL. Among them, Qmt.nwafu.3D was identified as a pleiotropic QTL in the physical interval of 149.77-154.11Mb containing a potential candidate gene TaGS5-3D. An SNP (T > C) was detected in its ninth intron, and TaGS5-3D-C was validated as a superior allele associated with larger grains using a CAPS marker. Interestingly, we found that TaGS5-3D-C was closely related to significantly up-regulated expression of intron-retained transcript (TaGS5-3D-PD34.1), while TaGS5-3D-T was related to dominant expression of normal splicing transcript (TaGS5-3D-MY47.1). Our results indicated that alternative splicing associated with the SNP T/C could be involved in the regulation of grain-related traits, laying a foundation for the functional analysis of TaGS5-3D and its greater potential application in high-yield wheat breeding.

Deciphering genetic basis of developmental and agronomic traits by integrating high-throughput optical phenotyping and genome-wide association studies in wheat.

Dissecting the genetic basis of complex traits such as dynamic growth and yield potential is a major challenge in crops. Monitoring the growth throughout growing season in a large wheat population to uncover the temporal genetic controls for plant growth and yield-related traits has so far not been explored. In this study, a diverse wheat panel composed of 288 lines was monitored by a non-invasive and high-throughput phenotyping platform to collect growth traits from seedling to grain filling stage and their relationship with yield-related traits was further explored. Whole genome re-sequencing of the panel provided 12.64 million markers for a high-resolution genome-wide association analysis using 190 image-based traits and 17 agronomic traits. A total of 8327 marker-trait associations were detected and clustered into 1605 quantitative trait loci (QTLs) including a number of known genes or QTLs. We identified 277 pleiotropic QTLs controlling multiple traits at different growth stages which revealed temporal dynamics of QTLs action on plant development and yield production in wheat. A candidate gene related to plant growth that was detected by image traits was further validated. Particularly, our study demonstrated that the yield-related traits are largely predictable using models developed based on i-traits and provide possibility for high-throughput early selection, thus to accelerate breeding process. Our study explored the genetic architecture of growth and yield-related traits by combining high-throughput phenotyping and genotyping, which further unravelled the complex and stage-specific contributions of genetic loci to optimize growth and yield in wheat.

QTL Analysis of Yield and End-Use Quality Traits in Texas Hard Red Winter Wheat

Genetic dissection of complex traits by quantitative trait locus (QTL) analysis permits the understanding of the genotypic effects of QTL, interactions between QTLs, and QTL-by-environment interactions in wheat. This study aimed to identify the QTL linked to yield, its components, end-use quality traits including kernel, flour, and dough rheology, and related agronomic traits under dryland and irrigated conditions. A mapping population of 179 F2:6 recombinant inbred lines (RILs) derived from ‘TAM 111’/‘TX05A001822’ was evaluated for these traits to investigate their genetic stability and phenotypic plasticity using 2658 single nucleotide polymorphisms (SNPs) with 35 linkage groups. Traits associated with chromosome regions were detected for individual and across-environment QTL by inclusive composite interval mapping. A total of 30 QTL regions were identified, including 14 consistent QTLs mapped on 11 chromosomes and six pleiotropic QTLs mapped on 5 chromosomes. Three consistent QTLs in chromosomes 1A, 3B, and 6D might be novel. Three major QTLs with both consistent and pleiotropic effects were co-localized with known genes. The first QTL for dough mixing properties was physically clustered around Glu-D1 and had an phenotypic variation explained (PVE) up to 31.3%. The second QTL for kernel-related traits was physically close to the TaCWI-4A (cell wall invertase) gene, which influences the thousand kernel weight, heading date, and harvest index, with a PVE of up to 12.3%. The third QTL, which was colocalized with the TaCWI-5D gene for kernel traits, was identified with a PVE of 6.7%. Epistasis was also detected, but major QTLs were not involved in significant epistasis or interactions with environmental effects. The current study provided new information that is useful for enhanced wheat breeding, which will benefit from the deployment of the favorable alleles for end-use quality, yield, and other agronomic traits in wheat-breeding programs through marker-assisted selection.

Identification of genetic loci for grain yield-related traits in the wheat population Zhongmai 578/Jimai 22

The identification of stable quantitative trait locus (QTL) for yield-related traits and tightly linked molecular markers is important for improving wheat grain yield. In the present study, six yield-related traits in a recombinant inbred line (RIL) population derived from the Zhongmai 578/Jimai 22 cross were phenotyped in five environments. The parents and 262 RILs were genotyped using the wheat 50K single nucleotide polymorphism (SNP) array. A high-density genetic map was constructed with 1 501 non-redundant bin markers, spanning 2 384.95 cM. Fifty-three QTLs for six yield-related traits were mapped on chromosomes 1D (2), 2A (9), 2B (6), 2D, 3A (2), 3B (2), 4A (5), 4D, 5B (8), 5D (2), 7A (7), 7B (3) and 7D (5), which explained 2.7–25.5% of the phenotypic variances. Among the 53 QTLs, 23 were detected in at least three environments, including seven for thousand-kernel weight (TKW), four for kernel length (KL), four for kernel width (KW), three for average grain filling rate (GFR), one for kernel number per spike (KNS) and four for plant height (PH). The stable QTLs QKl.caas-2A.1, QKl.caas-7D, QKw.caas-7D, QGfr.caas-2B.1, QGfr.caas-4A, QGfr.caas-7A and QPh.caas-2A.1 are likely to be new loci. Six QTL-rich regions on 2A, 2B, 4A, 5B, 7A and 7D, showed pleiotropic effects on various yield traits. TaSus2-2B and WAPO-A1 are potential candidate genes for the pleiotropic regions on 2B and 7A, respectively. The pleiotropic QTL on 7D for TKW, KL, KW and PH was verified in a natural population. The results of this study enrich our knowledge of the genetic basis underlying yield-related traits and provide molecular markers for high-yield wheat breeding.

QTL mapping of yield components and kernel traits in wheat cultivars TAM 112 and Duster.

In the Southern Great Plains, wheat cultivars have been selected for a combination of outstanding yield and drought tolerance as a long-term breeding goal. To understand the underlying genetic mechanisms, this study aimed to dissect the quantitative trait loci (QTL) associated with yield components and kernel traits in two wheat cultivars `TAM 112' and `Duster' under both irrigated and dryland environments. A set of 182 recombined inbred lines (RIL) derived from the cross of TAM 112/Duster were planted in 13 diverse environments for evaluation of 18 yield and kernel related traits. High-density genetic linkage map was constructed using 5,081 single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing (GBS). QTL mapping analysis detected 134 QTL regions on all 21 wheat chromosomes, including 30 pleiotropic QTL regions and 21 consistent QTL regions, with 10 QTL regions in common. Three major pleiotropic QTL on the short arms of chromosomes 2B (57.5 - 61.6 Mbps), 2D (37.1 - 38.7 Mbps), and 7D (66.0 - 69.2 Mbps) colocalized with genes Ppd-B1, Ppd-D1, and FT-D1, respectively. And four consistent QTL associated with kernel length (KLEN), thousand kernel weight (TKW), plot grain yield (YLD), and kernel spike-1 (KPS) (Qklen.tamu.1A.325, Qtkw.tamu.2B.137, Qyld.tamu.2D.3, and Qkps.tamu.6A.113) explained more than 5% of the phenotypic variation. QTL Qklen.tamu.1A.325 is a novel QTL with consistent effects under all tested environments. Marker haplotype analysis indicated the QTL combinations significantly increased yield and kernel traits. QTL and the linked markers identified in this study will facilitate future marker-assisted selection (MAS) for pyramiding the favorable alleles and QTL map-based cloning.

Identification of a pleiotropic QTL cluster for Fusarium head blight resistance, spikelet compactness, grain number per spike and thousand-grain weight in common wheat

Simultaneously improving Fusarium head blight (FHB) resistance and grain yield is challenging in wheat breeding. The correlations between spikelet compactness (SC), grain number per spike (GNS), thousand-grain weight (TGW) and FHB resistance remains unclear in common wheat. Identification of major quantitative trait loci (QTL) conferring FHB resistance and yield components, and development of breeder-friendly markers for the QTL are prerequisites for marker-assisted selection (MAS). Here, a recombinant inbred line (RIL) population derived from a cross between a resistant cultivar Yangmai 12 (YM12) and a susceptible cultivar Yanzhan 1 (YZ1) was used to map QTL for FHB resistance and yield components. A total of 22 QTL were identified; among these, six are likely to be new for corresponding traits. A QTL cluster (Qclu.yas-2D) for FHB type II resistance, SC, GNS, and TGW was detected on chromosome 2D. Breeder-friendly kompetitive allele-specific PCR (KASP) markers flanking the interval of Qclu.yas-2D were developed and validated in a diverse panel of 166 wheat cultivars and advanced lines. The YM12 alleles of Qclu.yas-2D significantly increased FHB resistance, SC, and GNS but decreased TGW in the validation population. The KASP markers developed for Qclu.yas-2D have great potential for breeding high-yielding wheat cultivars with enhanced FHB resistance.

Separation of the effects of two reduced height (Rht) genes and genomic background to select for less Fusarium head blight of short-strawed winter wheat (Triticum aestivum L.) varieties.

FHB resistance shared pleiotropic loci with plant height and anther retention. Genomic prediction allows to select for genomic background reducing FHB susceptibility in the presence of the dwarfing allele Rht-D1b. With the high interest for semi-dwarf cultivars in wheat, finding locally adapted resistance sources against Fusarium head blight (FHB) and FHB-neutral reduced height (Rht) genes is of utmost relevance. In this study, 401 genotypes of European origin without/with dwarfing alleles of Rht-D1 and/or Rht24 were analysed across five environments on FHB severity and the morphological traits such as plant height(PH), anther retention(AR), number of spikelets per ear, ear length and ear density. Data were analysed by combined correlation and path analyses, association mapping and coupling single- and multi-trait genome-wide association studies (ST-GWAS and MT-GWAS, respectively) and genomic prediction (GP). All FHB data were corrected for flowering date or heading stage. High genotypic correlation (rg = 0.74) and direct path effect (0.57) were detected between FHB severity and anther retention (AR). Moderate correlation (rg = -0.55) was found between FHB severity and plant height (PH) with a high indirect path via AR (-0.31). Indirect selection for FHB resistance should concentrate on AR and PH. ST-GWAS identified 25 quantitative trait loci (QTL) for FHB severity, PH and AR, while MT-GWAS detected six QTL across chromosomes 2A, 4D, 5A, 6B and 7B conveying pleiotropic effects on the traits. Rht-D1b was associated with high AR and FHB susceptibility. Our study identified a promising positively acting pleiotropic QTL on chromosome 7B which can be utilized to improve FHB resistance while reducing PH and AR. Rht-D1b genotypes having a high resistance genomic background exhibited lower FHB severity and AR. The use of GP for estimating the genomic background was more effective than selection of GWAS-detected markers. We demonstrated that GP has a great potential and should be exploited by selecting for semi-dwarf winter wheat genotypes with higher FHB resistance due to their genomic background.

A Pleiotropic Flowering Time QTL Exhibits Gene-by-Environment Interaction for Fitness in a Perennial Grass.

Appropriate flowering time is a crucial adaptation impacting fitness in natural plant populations. Although the genetic basis of flowering variation has been extensively studied, its mechanisms in nonmodel organisms and its adaptive value in the field are still poorly understood. Here, we report new insights into the genetic basis of flowering time and its effect on fitness in Panicum hallii, a native perennial grass. Genetic mapping in populations derived from inland and coastal ecotypes identified flowering time quantitative trait loci (QTL) and many exhibited extensive QTL-by-environment interactions. Patterns of segregation within recombinant hybrids provide strong support for directional selection driving ecotypic divergence in flowering time. A major QTL on chromosome 5 (q-FT5) was detected in all experiments. Fine-mapping and expression studies identified a gene with orthology to a rice FLOWERING LOCUS T-like 9 (PhFTL9) as the candidate underlying q-FT5. We used a reciprocal transplant experiment to test for local adaptation and the specific impact of q-FT5 on performance. We did not observe local adaptation in terms of fitness tradeoffs when contrasting ecotypes in home versus away habitats. However, we observed that the coastal allele of q-FT5 conferred a fitness advantage only in its local habitat but not at the inland site. Sequence analyses identified an excess of low-frequency polymorphisms at the PhFTL9 promoter in the inland lineage, suggesting a role for either selection or population expansion on promoter evolution. Together, our findings demonstrate the genetic basis of flowering variation in a perennial grass and provide evidence for conditional neutrality underlying flowering time divergence.

QTL analysis of the developmental changes in cell wall components and forage digestibility in maize (Zea mays L.)

Cell wall architecture plays a key role in stalk strength and forage digestibility. Lignin, cellulose, and hemicellulose are the three main components of plant cell walls, and they can impact stalk quality by affecting the structure and strength of the cell wall. To explore cell wall development during secondary cell wall lignification in maize stalks, conventional and conditional genetic mapping were used to identify the dynamic quantitative trait loci (QTLs) of the cell wall components and digestibility traits during five growth stages after silking. Acid detergent lignin (ADL), cellulose (CEL), acid detergent fiber (ADF), neutral detergent fiber (NDF), and in vitro dry matter digestibility (IVDMD) were evaluated in a maize recombinant inbred line (RIL) population. ADL, CEL, ADF, and NDF gradually increased from 10 to 40 days after silking (DAS), and then they decreased. IVDMD initially decreased until 40 DAS, and then it increased slightly. Seventy-two QTLs were identified for the five traits, and each accounted for 3.48–24.04% of the phenotypic variation. Six QTL hotspots were found, and they were localized in the 1.08, 2.04, 2.07, 7.03, 8.05, and 9.03 bins of the maize genome. Within the interval of the pleiotropic QTL identified in bin 1.08 of the maize genome, six genes associated with cell wall component biosynthesis were identified as potential candidate genes for stalk strength as well as cell wall-related traits. In addition, 26 conditional QTLs were detected in the five stages for all of the investigated traits. Twenty-two of the 26 conditional QTLs were found at 30 DAS conditioned using the values of 20 DAS, and at 50 DAS conditioned using the values of 40 DAS. These results indicated that cell wall-related traits are regulated by many genes, which are specifically expressed at different stages after silking. Simultaneous improvements in both forage digestibility and lodging resistance could be achieved by pyramiding multiple beneficial QTL alleles identified in this study.

QTLs Controlling Physiological and Morphological Traits of Barley (Hordeum vulgare L.) Seedlings under Salinity, Drought, and Normal Conditions

To identify the genomic regions for the physiological and morphological traits of barley genotypes under normal salinity and drought, a set of 103 recombinant inbred line (RIL) populations, developed between Badia and Kavir crosses, was evaluated under phytotron conditions in a completely randomized design in 2019. Linkage maps were prepared using 152 SSR markers, 72 ISSR, 7 IRAP, 29 CAAT, 27 SCoT, and 15 iPBS alleles. The markers were assigned to seven barley chromosomes and covered 999.29 centimorgans (cM) of the barley genome. In addition, composite interval mapping showed 8, 9, and 26 quantitative trait loci (QTLs) under normal, drought, and salinity stress conditions, respectively. Our results indicate the importance of chromosomes 1, 4, 5, and 7 in salinity stress. These regions were involved in genes controlling stomata length (LR), leaf number (LN), leaf weight (LW), and genetic score (SCR). Three major stable pleiotropic QTLs (i.e., qSCS-1, qRLS-1, and qLNN-1) were associated with SCR, root length (RL), and root number (RN) in both treatments (i.e., normal and salinity), and two major stable pleiotropic QTLs (i.e., qSNN-3 and qLWS-3) associated with the stomata number (SN) and LW appeared to be promising for marker-assisted selection (MAS). Two major-effect QTLs (i.e., SCot8-B-CAAT5-D and HVM54-Bmag0571) on chromosomes 1 and 2 were characterized for their positive allele effect, which can be used to develop barley varieties concerning drought conditions. The new alleles (i.e., qLWS-4a, qSLS-4, qLNS-7b, qSCS-7, and qLNS-7a) identified in this study are useful in pyramiding elite alleles for molecular breeding and marker assisted selection for improving salinity tolerance in barley.

High-Density Mapping of Quantitative Trait Loci Controlling Agronomically Important Traits in Quinoa (Chenopodium quinoa Willd.).

Quinoa is a pseudocereal originating from the Andean regions. Despite quinoa’s long cultivation history, genetic analysis of this crop is still in its infancy. We aimed to localize quantitative trait loci (QTL) contributing to the phenotypic variation of agronomically important traits. We crossed the Chilean accession PI-614889 and the Peruvian accession CHEN-109, which depicted significant differences in days to flowering, days to maturity, plant height, panicle length, and thousand kernel weight (TKW), saponin content, and mildew susceptibility. We observed sizeable phenotypic variation across F2 plants and F3 families grown in the greenhouse and the field, respectively. We used Skim-seq to genotype the F2 population and constructed a high-density genetic map with 133,923 single nucleotide polymorphism (SNPs). Fifteen QTL were found for ten traits. Two significant QTL, common in F2 and F3 generations, depicted pleiotropy for days to flowering, plant height, and TKW. The pleiotropic QTL harbored several putative candidate genes involved in photoperiod response and flowering time regulation. This study presents the first high-density genetic map of quinoa that incorporates QTL for several important agronomical traits. The pleiotropic loci can facilitate marker-assisted selection in quinoa breeding programs.

Genetic Dissection of Rice Ratooning Ability Using an Introgression Line Population and Substitution Mapping of a Pleiotropic Quantitative Trait Locus qRA5.

Ratooning ability is a key factor that influences ratoon rice yield, in the area where light and temperature are not enough for second season rice. In the present study, an introgression line population derived from Minghui 63 as the recipient parent and 02428 as the donor parent was developed, and a high-density bin map containing 4568 bins was constructed. Nine ratooning-ability-related traits were measured, including maximum tiller number, panicle number, and grain yield per plant in the first season and ratoon season, as well as three secondary traits, maximum tiller number ratio, panicle number ratio, and grain yield ratio. A total of 22 main-effect QTLs were identified and explained for 3.26–18.63% of the phenotypic variations in the introgression line population. Three genomic regions, including 14.12–14.65 Mb on chromosome 5, 4.64–5.76 Mb on chromosome 8, and 10.64–15.52 Mb on chromosome 11, were identified to simultaneously control different ratooning-ability-related traits. Among them, qRA5 in the region of 14.12–14.65 Mb on chromosome 5 was validated for its pleiotropic effects on maximum tiller number and panicle number in the first season, as well as its maximum tiller number ratio, panicle number ratio, and grain yield ratio. Moreover, qRA5 was independent of genetic background and delimited into a 311.16 kb region by a substitution mapping approach. These results will help us better understand the genetic basis of rice ratooning ability and provide a valuable gene resource for breeding high-yield ratoon rice varieties.

Dissection of the genetic architecture of peduncle vascular bundle-related traits in maize by a genome-wide association study.

SummaryThe peduncle vascular system of maize is critical for the transport of photosynthetic products, nutrients, and water from the roots and leaves to the ear. Accordingly, it positively affects the grain yield. However, the genetic basis of peduncle vascular bundle (PVB)‐related traits in maize remains unknown. Thus, 15 PVB‐related traits of 386 maize inbred lines were investigated at three locations (Yongcheng, 17YC; Kaifeng, 20KF; and Yuanyang, 20YY). The repeatability for the 15 traits ranged from 35.53% to 92.13%. A genome‐wide association study was performed and 69 non‐redundant quantitative trait loci (QTL) were detected, including 9, 41, and 27 QTL identified at 17YC, 20KF, and 20YY, respectively. These QTL jointly explained 4.72% (SLL) to 37.30% (NSVB) of the phenotypic variation. Eight QTL were associated with the same trait at two locations. Furthermore, four pleiotropic QTL were identified. Moreover, one QTL (qPVB44), associated with NSVB_20KF, was co‐localized with a previously reported locus related to kernel width, implying qPVB44 may affect the kernel width by modulating the number of small vascular bundles. Examinations of the 69 QTL identified 348 candidate genes that were classified in five groups. Additionally, 26 known VB‐related homologous genes (e.g. VLN2, KNOX1, and UGT72B3) were detected in 20 of the 69 QTL. A comparison of the NSVB between a Zmvln2 EMS mutant and its wild type elucidated the function of the candidate gene ZmVLN2. These results are important for clarifying the genetic basis of PVB‐related traits and may be useful for breeding new high‐yielding maize cultivars.

Advanced backcross‐quantitative trait loci mapping of grain yield, heading date, and their stability parameters in barley across multienvironmental trials in Egypt

AbstractExploring the relationship between grain yield and heading date traits and their stability parameters at phenotypic, genetic, and molecular levels is the milestone for improving yield and adaptation in barley. We evaluated a mapping population comprising 298 doubled haploid lines in multienvironmental trials in Egypt. Composite interval mapping revealed 35 quantitative trait loci (QTLs) with four pleiotropic QTLs. A major QTL bPb‐9110 (140.3 cM on 3H) with a peak LOD greater than 24 was found to be associated with the stability statistics bi and R2 of heading date. Additionally, the marker bPb‐1213 on 1H was correlated to heading date, grain yield, and the statistic bi (GYP). We also found that the gene HvFT4 (2H, 66 cM) had a significant impact on the heading date due to the presence of exotic alleles. This gene was closely linked to the photoperiod Ppd‐H1 gene by 24.9 cM, and both genes play a major role in regulating flowering time in barley. Our results provide evidence that stability statistics pinpoint genetic control and appear promising for marker‐assisted selection.

Genome-wide association studies for production, respiratory disease, and immune-related traits in Landrace pigs

Identification of a quantitative trait locus (QTL) related to a chronic respiratory disease such as Mycoplasmal pneumonia of swine (MPS) and immune-related traits is important for the genetic improvement of disease resistance in pigs. The objective of this study was to detect a novel QTL for a total of 22 production, respiratory disease, and immune-related traits in Landrace pigs. A total of 874 Landrace purebred pigs, which were selected based on MPS resistance, were genotyped using the Illumina PorcineSNP60 BeadChip. We performed single nucleotide polymorphism (SNP)-based and haplotype-based genome-wide association studies (GWAS) to detect a novel QTL and to evaluate the possibility of a pleiotropic QTL for these traits. SNP-based GWAS detected a total of six significant regions in backfat thickness, ratio of granular leucocytes to lymphatic cells, plasma concentration of cortisol at different ages, and complement alternative pathway activity in serum. The significant region detected by haplotype-based GWAS was overlapped across the region detected by SNP-based GWAS. Most of these detected QTL regions were novel regions with some candidate genes located in them. With regard to a pleiotropic QTL among traits, only three of these detected QTL regions overlapped among traits, and many detected regions independently affected the traits.