Potential Quantitative Trait Loci Research Articles

Mapping QTL controlling count traits with excess zeros and ones using a zero-and-one-inflated generalized Poisson regression model.

The research on the quantitative trait locus (QTL) mapping of count data has aroused the wide attention of researchers. There are frequent problems in applied research that limit the application of the conventional Poisson model in the analysis of count phenotypes, which include the overdispersion and excess zeros and ones. In this article, a novel model, that is, the zero-and-one-inflated generalized Poisson (ZOIGP) model, is proposed to deal with these problems. Based on the proposed model, a score test is performed for the inflation parameter, in which the ZOIGP model with a constant proportion of excess zeros and ones is compared with a standard generalized Poisson model. To illustrate the practicability of the ZOIGP model, we extend it to the QTL interval mapping application that underpins count phenotype with excess zeros and excess ones. The genetic effects are estimated utilizing the expectation-maximization algorithm embedded with the Newton-Raphson algorithm, and the genome-wide scan and likelihood ratio test is performed to map and test the potential QTLs. The statistical properties exhibited by the proposed method are investigated through simulation. Finally, a real data analysis example is used to illustrate the utility of the proposed method for QTLmapping.

Mutations in the FOXO3 Gene and Their Effects on Meat Traits in Gannan Yaks.

The FOXO3 gene, a prominent member of the FOXO family, has been identified as a potential quantitative trait locus for muscle atrophy and lipid metabolism in livestock. It is also considered a promising candidate gene for meat quality traits such as Warner-Bratzler shear force (WBSF) and water holding capacity (WHC). The aim of this study was to identify sequence mutations in the FOXO3 gene of yaks and to analyze the association of genotypes and haplotypes with meat traits such as WBSF and WHC. Quantitative reverse-transcriptase PCR (RT-qPCR) was applied to determine the expression levels of FOXO3 in yak tissues, with the results revealing a high expression in the yak longissimus dorsi muscle. Exons of the FOXO3 gene were then sequenced in 572 yaks using hybrid pool sequencing. Five single nucleotide polymorphisms were identified. Additionally, four effective haplotypes and four combined haplotypes were constructed. Two mutations of the FOXO3 gene, namely C>G at exon g.636 and A>G at exon g.1296, were associated with cooked meat percentage (CMP) (p < 0.05) and WBSF (p < 0.05), respectively. Furthermore, the WBSF of the H2H3 haplotype combination was significantly lower than that of other combinations (p < 0.05). The findings of this study suggest that genetic variations in FOXO3 could be a promising biomarker for improving yak meat traits.

Genome-wide SNP discovery and genotyping delineates potential QTLs underlying major yield-attributing traits in buckwheat.

Buckwheat (Fagopyrum spp.) is an important nutritional and nutraceutical-rich pseudo-cereal crop. Despite its obvious potential as a functional food, buckwheat has not been fully harnessed due to its low yield, self-incompatibility, increased seed cracking, limited seed set, lodging, and frost susceptibility. The inadequate availability of genomics resources in buckwheat is one of the major reasons for this. In the present study, genome-wide association mapping (GWAS) was conducted to identify loci associated with various morphological and yield-related traits in buckwheat. High throughput genotyping by sequencing led to the identification of 34,978 single nucleotide polymorphisms that were distributed across eight chromosomes. Population structure analysis grouped the genotypes into three sub-populations. The genotypes were also characterized for various qualitative and quantitative traits at two diverse locations, the analysis of which revealed a significant difference in the mean values. The association analysis revealed a total of 71 significant marker-trait associations across eight chromosomes. The candidate genes were identified near 100 Kb of quantitative trait loci (QTLs), providing insights into several metabolic and biosynthetic pathways. The integration of phenology and GWAS in the present study is useful to uncover the consistent genomic regions, related markers associated with various yield-related traits, and potential candidate genes having implications for being utilized in molecular breeding for the improvement of economically important traits in buckwheat. Moreover, the identified QTLs will assist in tracking the desirable alleles of target genes within the buckwheat breeding populations/germplasm.

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.

Development of Gossypium hirsutum-Gossypium raimondii introgression lines and its usages in QTL mapping of agricultural traits

Gossypium raimondii (2n=2x=26, D5), an untapped wild species, is the putative progenitor of the D-subgenome of G. hirsutum (2n=4x=52, AD1), an extensively cultivated species. Here, we developed a G. hirsutum (recipient)-G. raimondii (donor) introgression population to exploit favorable QTLs/genes and mapped potential quantitative trait loci (QTLs) from wild cotton species. The introgression population consists of 256 lines with an introgression rate of 52.33% of the genome G. raimondii. The range of introgression segment length was 0.03-19.12 Mb, with an average of 1.22 Mb. The coverage of total introgression fragments was 386.98 Mb from G. raimondii. Further genome-wide association analysis (Q+K+MLM) and QTL mapping (RSTEP-LRT) identified 59 common QTLs, including 14 stable QTLs and 6 common QTL (co-QTL) clusters, and one hotspot of MIC. The common QTLs for seed index showed all positive additive effects, while the common QTLs for boll weight were all negative additive effects, indicating that the linkage between seed index and boll weight could be broken. QTLs for lint percentage showed positive effect and could be beneficial for improving cotton yield. Most QTLs for fiber quality had negative additive effects, implying these QTLs were domesticated/improved in G. hirsutum. A few fiber quality QTLs showed positive additive effects, which could be used to improve cotton fiber quality. These introgression lines developed would be useful for molecular marker-assisted breeding and facilitate us to map QTLs precisely for mining desirable genes from the wild species G. raimondii to improve cultivated cotton in future via a design-breeding approach.

Maize and heat stress: Physiological, genetic, and molecular insights.

Global mean temperature is increasing at a rapid pace due to the rapid emission of greenhouse gases majorly from anthropogenic practices and predicted to rise up to 1.5°C above the pre-industrial level by the year 2050. The warming climate is affecting global crop production by altering biochemical, physiological, and metabolic processes resulting in poor growth, development, and reduced yield. Maize is susceptible to heat stress, particularly at the reproductive and early grain filling stages. Interestingly, heat stress impact on crops is closely regulated by associated environmental covariables such as humidity, vapor pressure deficit, soil moisture content, and solar radiation. Therefore, heat stress tolerance is considered as a complex trait, which requires multiple levels of regulations in plants. Exploring genetic diversity from landraces and wild accessions of maize is a promising approach to identify novel donors, traits, quantitative trait loci (QTLs), and genes, which can be introgressed into the elite cultivars. Indeed, genome wide association studies (GWAS) for mining of potential QTL(s) and dominant gene(s) is a major route of crop improvement. Conversely, mutation breeding is being utilized for generating variation in existing populations with narrow genetic background. Besides breeding approaches, augmented production of heat shock factors (HSFs) and heat shock proteins (HSPs) have been reported in transgenic maize to provide heat stress tolerance. Recent advancements in molecular techniques including clustered regularly interspaced short palindromic repeats (CRISPR) would expedite the process for developing thermotolerant maize genotypes.

Physiological specialization of Puccinia triticina and genome-wide association mapping provide insights into the genetics of wheat leaf rust resistance in Iran

Leaf rust caused by Puccinia triticina Erikss. (Pt) is the most widely distributed and important wheat disease worldwide. The objective of the present study was to determine the frequency of Iranian Pt races, their virulence to key resistance genes and map quantitative trait loci (QTL) for resistance to different Pt races from 185 globally diverse wheat genotypes using a genome-wide association study (GWAS) approach. The virulence pattern of the 33 Pt isolates from various wheat-growing areas of Iran on 55 wheat differentials showed that the FKTPS and FKTTS were relatively frequent pathotypes among the 18 identified races. The weighted average frequency of virulence on the resistance genes Lrb, Lr3bg, Lr14b, Lr16, Lr24, Lr3ka, Lr11 and Lr20 were high (> 90%). However, low virulence on the resistant genes Lr2a, Lr9, Lr19, Lr25, Lr28 and Lr29 indicates that these genes are still effective against the pathogen population in Iran at present. GWAS on a panel of 185 wheat genotypes against 10 Pt races resulted into 62 significant marker-trait associations (MTAs) belonged to 34 quantitative trait loci (QTL) across 16 chromosomes. Among them, 10 QTLs on chromosomes 1A, 1B, 3B, 3D, 4A, 6D, 7A and 7D were identified as potential novel QTLs, of which four QTLs (QLr.iau-3B-2, QLr.iau-7A-2, QLr.iau-7A-3 and QLr.iau-7D-2) are more interesting, as they are associated with resistance to two or more Pt races. The known and novel QTLs associated with different Pt races found here, can be used in future wheat breeding programs to recombine different loci for durable resistance against leaf rust races.

A multi-locus linear mixed model methodology for detecting small-effect QTLs for quantitative traits in MAGIC, NAM, and ROAM populations

Although multi-parent populations (MPPs) integrate the advantages of linkage and association mapping populations in the genetic dissection of complex traits and especially combine genetic analysis with crop breeding, it is difficult to detect small-effect quantitative trait loci (QTL) for complex traits in multiparent advanced generation intercross (MAGIC), nested association mapping (NAM), and random-open-parent association mapping (ROAM) populations. To address this issue, here we proposed a multi-locus linear mixed model method, namely mppQTL, to detect QTLs, especially small-effect QTLs, in these MPPs. The new method includes two steps. The first is genome-wide scanning based on a single-locus linear mixed model; the P-values are obtained from likelihood-ratio test, the peaks of negative logarithm P-value curve are selected by group-lasso, and all the selected peaks are regarded as potential QTLs. In the second step, all the potential QTLs are placed on a multi-locus linear mixed model, all the effects are estimated using expectation-maximization empirical Bayes algorithm, and all the non-zero effect vectors are further evaluated via likelihood-ratio test for significant QTLs. In Monte Carlo simulation studies, the new method has higher power in QTL detection, lower false positive rate, lower mean absolute deviation for QTL position estimate, and lower mean squared error for the estimate of QTL size (r2) than existing methods because the new method increases the power of detecting small-effect QTLs. In real dataset analysis, the new method (19) identified five more known genes than the existing three methods (14). This study provides an effective method for detecting small-effect QTLs in any MPPs.

Identification and Genetic Mapping of Potential QTLs Conferring Heat Tolerance in Cotton (Gossypium hirsutum L.) by Using Micro Satellite Marker’s Approach

High-temperature stress can cause serious abiotic damage that limits the yield and quality of cotton plants. Heat Tolerance (HT) during the different developmental stages of cotton can guarantee a high yield under heat stress. HT is a complex trait that is regulated by multiple quantitative trait loci (QTLs). In this study, the F2 population derived from a cross between MNH-886, a heat-tolerant cultivar, and MNH-814, a heat-sensitive variety, was used to map HT QTLs during different morphological stages in cotton. A genetic map covering 4402.7 cm, with 175 marker loci and 26 linkage groups, was constructed by using this F2 population (94 individuals). This population was evaluated for different 23 morpho-physiological HT contributing traits QTL analysis via composite interval mapping detected 17 QTLs: three QTLs each for Total Number of Sympodes (TNS), Length of Bract (LOB), and Length of Staminal-column (LOS); two QTLs for First Sympodial Node Height (FSH), and one QTL each for Sympodial Node Height (SNH), Percent Boll set on second position along Sympodia (PBS), Total Number of Nodes (TNN), Number of Bolls (NOB), Total Number of Buds (TNB), and Length of Petal (LOP). Individually, the QTLs accounted for 7.76%–36.62% of phenotypic variation. QTLs identified linked with heat tolerance traits can facilitate marker-assisted breeding for heat tolerance in cotton.

Natural Genotypic Variation Underpins Root System Response to Drought Stress in Bambara Groundnut [Vigna subterranea (L.) Verdc.

Bambara groundnut [Vigna subterranea (L.) Verdc.] is grown in rainfed production systems and suffers from periodic drought stress (DS), leading to yield reductions. Natural genotypic variation for root traits is essential for adaptation to water deficit conditions. However, root traits have not been fully utilised as selection criteria to improve DS in bambara groundnut. The present study explored the natural genotypic variation found in single genotypes of bambara groundnut derived from landraces to identify adaptive differences in tap root length (TRL) and root length density (RLD) in response to DS. A diverse core collection of eight bambara groundnut genotypes from various locations (namely, Gresik, LunT, IITA-686, DodR, S19-3, Tiga nicuru, and Ankpa-4, DipC1), were grown for two seasons (2018 and 2019) in polyvinyl chloride (PVC) columns with well-watered (WW) and 30-day DS treatments. Plant samples were collected at 55 days after emergence (DAE) (30 days of DS) and at 105 DAE (30 days of DS plus 50 days of recovery). Under DS, differential TRL among genotypes at 55 DAE was observed, with DodR recording the longest among genotypes with an increase (1% in 2018) in TRL under DS compared to WW, whereas LunT and IITA-686 showed significant (p < 0.001) decrease in TRL (27 and 25%, respectively, in 2018). Average RLD was observed to have the highest reduction under DS in the 90–110 cm layer (42 and 58%, respectively, in 2018 and 2019). Rainy habitat LunT had limited roots in 2018 and recorded the least (0.06 ± 0.013 cm–3) RLD in 2019. However, dry-habitat DodR showed an increase in the RLD (60–90 cm) under DS compared to WW, while dry-habitat S19-3 densely occupied all depths with RLD of 0.16 ± 0.05 and 0.18 ± 0.01 cm cm–3 in the deepest layer in both seasons, respectively. Reduced RLD under DS showed recovery when the plants were re-watered. These plants were additionally observed to have RLD that surpasses the density in WW at all soil depths at 105 DAE. Also, recovery was shown in Tiga nicuru and DodR (0–30 cm) and IITA-686 (90–110 cm) in 2019. Average RLD under DS treatment was associated with substantial grain yield advantage (R2 = 0.27 and R2 = 0.49, respectively) in 2018 and 2019. An increase in TRL allowed DodR to quickly explore water at a deeper soil depth in response to gradually declining soil water availability. High RLD in genotypes such as DodR, DipC1 and S19-3 also offered adaptive advantage over other genotypes under DS. Variation in intrinsic RLD in deeper soil depths in the studied genotypes determines root foraging capacity when facing DS. This suggests that different agroecological environments to which bambara groundnut is subjected in its natural habitat have promoted a phenotypic differentiation in root systems to adapt to ecotypic conditions, which may help offset the impact of DS. The natural genotypic variation exhibited, especially by DodR, could be exploited to identify potential quantitative trait loci (QTLs) that control deep rooting and root length density.

Berry Anthocyanin, Acid, and Volatile Trait Analyses in a Grapevine-Interspecific F2 Population Using an Integrated GBS and rhAmpSeq Genetic Map.

Increased map density and transferability of markers are essential for the genetic analysis of fruit quality and stress tolerance in interspecific grapevine populations. We used 1449 GBS and 2000 rhAmpSeq markers to develop a dense map for an interspecific F2 population (VRS-F2) that was derived by selfing a single F1 from a Vitis riparia x ‘Seyval blanc’ cross. The resultant map contained 2519 markers spanning 1131.3 cM and was highly collinear with the Vitis vinifera ‘PN40024’ genome. Quantitative trait loci (QTL) for berry skin color and flower type were used to validate the map. Four rhAmpSeq transferable markers were identified that can be used in pairs (one pistillate and one hermaphroditic) to predict pistillate and hermaphrodite flower type with ≥99.7% accuracy. Total and individual anthocyanin diglucoside QTL mapped to chromosome 9 near a 5-O-GLUCOSYLTRANSFERASE candidate gene. Malic acid QTL were observed on chromosome 1 and 6 with two MALATE DEHYRDROGENASE CYTOPLASMIC 1 and ALUMINUM-ACTIVATED MALATE TRANSPORTER 2-LIKE (ALMT) candidate genes, respectively. Modeling malic acid identified a potential QTL on chromosome 8 with peak position in proximity of another ALMT. A first-ever reported QTL for the grassy smelling volatile (E)-2-hexenal was found on chromosome 2 with a PHOSPHOLIPID HYDROPEROXIDE GLUTATHIONE PEROXIDASE candidate gene near peak markers.

QTL-seq analysis of the seed size trait in grape provides new molecular insights on seedlessness

Seedlessness in grape (Vitis vinifera) is an important commercial trait for both the fresh and drying markets. However, despite numerous studies, the mechanisms and key genes regulating grape seedlessness are mostly unknown. In this study, we sequenced the genomes of the V. vinifera seeded cultivar ‘Red Globe’, the seedless cultivar 'Centennial Seedless’, and the derived hybrids. Nonsynonymous single nucleotide polymorphisms (SNPs) were identified by genome sequencing and analyzed using published transcriptome data. Nonsynonymous SNPs occurred in genes related to seed development, which were identified as protein kinases, transcription factors, and cytochrome P450s and showed differential expression during ovule development in both seeded and seedless grapes. These nonsynonymous SNP-associated genes were mainly involved in biological processes such as hormone balance, seed coat and endosperm development, reproductive organ development, oxidation and reduction, senescence and cell death. A potential quantitative trait locus (QTL) region associated with seed size was characterized based on the SNP-index, and expression analysis of candidate genes in the QTL region during ovule development in multiple seeded and seedless grape cultivars were conducted. Three SNPs were further subjected to SNaPshot analysis and one SNP in G8 showed 67.5% efficiency in the grape progeny validation. Overall, the data obtained in this study shed light on the differences in seed development between seeded and seedless progeny at the genomic level, which provides valuable resources for future functional studies and grape breeding.

An association study in the Taiwan Biobank elicits the GABAA receptor genes GABRB3, GABRA5, and GABRG3 as candidate loci for sleep duration in the Taiwanese population

BackgroundGamma-aminobutyric acid type A (GABAA) receptors mainly mediate the effects of gamma-aminobutyric acid, which is the primary inhibitory neurotransmitter in the central nervous system. Abundant evidence suggests that GABAA receptors play a key role in sleep-regulating processes. No genetic association study has explored the relationships between GABAA receptor genes and sleep duration, sleep quality, and sleep timing in humans.MethodsWe determined the association between single-nucleotide polymorphisms (SNPs) in the GABAA receptor genes GABRA1, GABRA2, GABRB3, GABRA5, and GABRG3 and sleep duration, sleep quality, and sleep timing in the Taiwan Biobank with a sample of 10,127 Taiwanese subjects. There were 10,142 subjects in the original study cohort. We excluded 15 subjects with a medication history of sedative-hypnotics.ResultsOur data revealed an association of the GABRB3-GABRA5-GABRG3 gene cluster with sleep duration, which has not been previously identified: rs79333046 (beta = − 0.07; P = 1.21 × 10–3) in GABRB3, rs189790076 (beta = 0.92; P = 1.04 × 10–3) in GABRA5, and rs147619342 (beta = − 0.72; P = 3.97 × 10–3) in GABRG3. The association between rs189790076 in GABRA5 and sleep duration remained significant after Bonferroni correction. A variant (rs12438141) in GABRB3 was also found to act as a potential expression quantitative trait locus. Additionally, we discovered interactions between variants in the GABRB3-GABRA5-GABRG3 gene cluster and lifestyle factors, such as tea and coffee consumption, smoking, and physical activity, that influenced sleep duration, although some interactions became nonsignificant after Bonferroni correction. We also found interactions among GABRB3, GABRA5, and GABRG3 that affected sleep duration. Furthermore, we identified an association of rs7165524 (beta = − 0.06; P = 2.20 × 10–3) in GABRA5 with sleep quality and an association of rs79465949 (beta = − 0.12; P = 3.95 × 10–3) in GABRB3 with sleep timing, although these associations became nonsignificant after Bonferroni correction. However, we detected no evidence of an association of individual SNPs in GABRA1 and GABRA2.ConclusionsOur results indicate that rs189790076 in GABRA5 and gene–gene interactions among GABRB3, GABRA5, and GABRG3 may contribute to sleep duration in the Taiwanese population.

Genome-wide association study identifies QTL for eight fruit traits in cultivated tomato (Solanum lycopersicum L.)

Genome-wide association study (GWAS) is effective in identifying favorable alleles for traits of interest with high mapping resolution in crop species. In this study, we conducted GWAS to explore quantitative trait loci (QTL) for eight fruit traits using 162 tomato accessions with diverse genetic backgrounds. The eight traits included fruit weight, fruit width, fruit height, fruit shape index, pericarp thickness, locule number, fruit firmness, and brix. Phenotypic variations of these traits in the tomato collection were evaluated with three replicates in field trials over three years. We filtered 34,550 confident SNPs from the 51 K Axiom® tomato array based on < 10% of missing data and > 5% of minor allele frequency for association analysis. The 162 tomato accessions were divided into seven clusters and their membership coefficients were used to account for population structure along with a kinship matrix. To identify marker-trait associations (MTAs), four phenotypic data sets representing each of three years and combined were independently analyzed in the multilocus mixed model (MLMM). A total of 30 significant MTAs was detected over data sets for eight fruit traits at P < 0.0005. The number of MTA per trait ranged from one (brix) to seven (fruit weight and fruit width). Two SNP markers on chromosomes 1 and 2 were significantly associated with multiple traits, suggesting pleiotropic effects of QTL. Furthermore, 16 of 30 MTAs suggest potential novel QTL for eight fruit traits. These results facilitate genetic dissection of tomato fruit traits and provide a useful resource to develop molecular tools for improving fruit traits via marker-assisted selection and genomic selection in tomato breeding programs.

Identification and characterization of An-4, a potential quantitative trait locus for awn development in rice

BackgroundAwn of rice is an important domestication trait closely associated with yield traits. Therefore, the identification of genes for awn development is of great significance for the elucidation of molecular mechanism of awn development and the genetic improvement of yield traits in rice.ResultsIn this study, using chromosome segment substitution lines (CSSLs) derived from a long-awned Guangxi common wild rice (GXCWR, Oryza rufipogon Griff.) and a short-awned indica cultivar 9311, we identified An-4, a potential quantitative trait locus (QTL) for awn development. Then, An-4 was fine mapped into a 56-kb region of chromosome 2, which contained four annotated genes. Among these four annotated genes, Os02g0594800 was concluded to be the potential candidate gene for An-4. An-4 exhibited pleiotropic effects on awn development and several yield traits. Scanning electron microscopy (SEM) analysis showed that An-4 significantly promoted awn development at Sp7 and Sp8 stage of spikelet development. Transcriptome analysis suggested that An-4 might influence the development of awn by regulating the expression of genes related to growth, developmental process, channel regulation and extracellular region. By contrast to those of 9311, the expression level of OsRR5 in CSSL128 was significantly down-regulated, whereas the expression levels of OsCKX2 and OsGA2ox5 in CSSL128 were significantly up-regulated. In addition, our study showed that An-4 had additive effects with other genes for awn development, such as An-1, An-2/LABA1 and An-3/GAD1/RAE2.ConclusionsThe identification of An-4 lays a foundation for cloning of An-4 and further elucidation of the molecular mechanism of awn development. Moreover, the identification of favorable allelic variation of An-4 from 9311 will be useful to improve rice yield traits.

Selection of F2 homozygous plants over the QTL9 related to rice panicle structure by using CAPS markers

QTL9 is a new potential quantitative trait locus related to rice panicle structure, identified through a GWAS analysis of Vietnamese local rice panel. To validate the QTL9, a biparental population was developed using the low branching (G6) and the high branching (G189) accessions from two haplotypes characterised by a contrasting phenotype for the secondary branch number and spikelet number traits. In parallel, using Gene capture technology combined with new generation sequencing identified 1,002 genetic variants in the QTL9 region between two parents, of which 12 SNPs were found in the cleavage site of 5 restriction enzyme. In this study, 12 primer pairs were tested to amplify the CAPS markers, based on the 12 SNPs, in order to be applied to select homozygous F2 lines over the QTL9 region for both haplotypes. 4 CAPS markers were selected distributing over the QTL9 region and displaying polymorphism between two parents. 275 F2plants were genotyped using 3 CAPS markers leading to the selection of 74 homozygotes plants over the QTL9region for haplotype 1, 66 homozygotes plants over the QTL9 region for haplotype 2, and 153 heterozygous plants. Homozygous lines will be used to develop the F3population, phenotyping of two F3 haplotypes will lead to discovering the role of QTL9 related to rice panicle structure.

Genetic Control Diversity Drives Differences Between Cadmium Distribution and Tolerance in Rice.

Rice, a staple crop for nearly half the planet’s population, tends to absorb and accumulate excessive cadmium (Cd) when grown in Cd-contaminated fields. Low levels of Cd can degrade the quality of rice grains, while high levels can inhibit the growth of rice plants. There is genotypic diversity in Cd distribution and Cd tolerance in different rice varieties, but their underlying genetic mechanisms are far from elucidated, which hinders genetic improvements. In this study, a joint study of phenotypic investigation with quantitative trait loci (QTLs) analyses of genetic patterns of Cd distribution and Cd tolerance was performed using a biparent population derived from japonica and indica rice varieties. We identified multiple QTLs for each trait and revealed that additive effects from various loci drive the inheritance of Cd distribution, while epistatic effects between various loci contribute to differences in Cd tolerance. One pleiotropic locus, qCddis8, was found to affect the Cd distribution from both roots to shoots and from leaf sheaths to leaf blades. The results expand our understanding of the diversity of genetic control over Cd distribution and Cd tolerance in rice. The findings provide information on potential QTLs for genetic improvement of Cd distribution in rice varieties.

Discovery of new genetic determinants of morphological plasticity in rice roots and shoots under phosphate starvation using GWAS

Phosphorus is an essential nutrient for plants that is often in short supply. In rice (Oryza sativa L.), inorganic phosphate (Pi) deficiency leads to various physiological disorders that consequently affect plant productivity. In this study, a large-scale phenotyping experiment using 160 Vietnamese rice landraces was performed under greenhouse conditions, by employing an alpha lattice design with three replicates, to identify quantitative trait loci (QTLs) associated with plant growth inhibition caused by Pi deficiency. Rice plantlets were grown for six weeks in the PVC sand column (16 cm diameter × 80 cm height) supplied with Pi-deficient medium (10 μM P) or full-Pi Yoshida medium (320 μM P). The effects of Pi deficiency on the number of crown roots, root length, shoot length, root weight, shoot weight and total weight were studied. From 36 significant markers identified using a genome-wide association study, 21 QTLs associated with plant growth inhibition under Pi starvation were defined. In total, 158 candidate genes co-located with the defined QTLs were identified. Interestingly, one QTL (qRST9.14) was associated with all three weight-traits. The co-located gene GLYCEROPHOSPHODIESTER PHOSPHODIESTERASE 13 was found to be potentially involved in Pi transport. Understanding the molecular mechanisms of Pi-starvation responses, and identifying the potential QTLs responsible for low-Pi stress tolerance, will provide valuable information for developing new varieties tolerant of low-Pi conditions.

Genome-Wide Association Analysis Identifies Resistance Loci for Bacterial Leaf Streak Resistance in Rice (Oryza sativa L.).

Bacterial leaf streak (BLS) caused by Xanthomonas oryzae pv. oryzicola (Xoc) is one of the most devastating diseases in rice production areas, especially in humid tropical and subtropical zones throughout Asia and worldwide. A genome-wide association study (GWAS) analysis conducted on a collection of 236 diverse rice accessions, mainly indica varieties, identified 12 quantitative trait loci (QTLs) on chromosomes 1, 2, 3, 4, 5, 8, 9 and 11, conferring resistance to five representative isolates of Thai Xoc. Of these, five QTLs conferred resistance to more than one Xoc isolates. Two QTLs, qBLS5.1 and qBLS2.3, were considered promising QTLs for broad-spectrum resistance to BLS. The xa5 gene was proposed as a potential candidate gene for qBLS5.1 and three genes, encoding pectinesterase inhibitor (OsPEI), eukaryotic zinc-binding protein (OsRAR1), and NDP epimerase function, were proposed as candidate genes for qBLS2.3. Results from this study provide an insight into the potential QTLs and candidate genes for BLS resistance in rice. The recessive xa5 gene is suggested as a potential candidate for strong influence on broad-spectrum resistance and as a focal target in rice breeding programs for BLS resistance.

Major quantitative trait loci influencing milk production and conformation traits in Guernsey dairy cattle detected on Bos taurus autosome 19

The goal of this study was to identify potential quantitative trait loci (QTL) for 27 production, fitness, and conformation traits of Guernsey cattle through genome-wide association (GWA) analyses, with extra emphasis on BTA19, where major QTL were observed for several traits. Animals' de-regressed predicted transmitting abilities (PTA) from the December 2018 traditional US evaluation were used as phenotypes. All of the Guernsey cattle included in the QTL analyses were predictor animals in the reference population, ranging from 1,077 to 1,685 animals for different traits. Single-trait GWA analyses were carried out by a mixed-model approach for all 27 traits using imputed high-density genotypes. A major QTL was detected on BTA19, influencing several milk production traits, conformation traits, and livability of Guernsey cattle, and the most significant SNP lie in the region of 26.2 to 28.3 Mb. The myosin heavy chain 10 (MYH10) gene residing within this region was found to be highly associated with milk production and body conformation traits of dairy cattle. After the initial GWA analyses, which suggested that many significant SNP are in linkage with one another, conditional analyses were used for fine mapping. The top significant SNP on BTA19 were fixed as covariables in the model, one at a time, until no more significant SNP were detected on BTA19. After this fine-mapping approach was applied, only 1 significant SNP was detected on BTA19 for most traits, but multiple, independent significant SNP were found for protein yield, dairy form, and stature. In addition, the haplotype that hosts the major QTL on BTA19 was traced to a US Guernsey born in 1954. The haplotype is common in the breed, indicating a long-term influence of this QTL on the US Guernsey population.