Genotype selection identified elite lines through quantitative trait loci mapping of agronomically important traits in wheat.

Wheat is one of the most important staple foods in the world. Genetic characterization of wheat agronomically important traits is crucial for yield improvement through molecular breeding. In this study, a recombinant inbred line (RIL) population was developed by crossing a local adapted high yield variety Jimai 22 (JM22) with an external variety Cunmai no.1 (CM1). A high-density genetic map containing 7,359 single nucleotide polymorphism (SNP) markers was constructed. Quantitative trait loci (QTL) mapping identified 61 QTL for eight yield-related traits under six environments (years). Among them, 17 QTL affecting spike number per plant, grain number per spike and thousand grain weight showed high predictability for theoretical yield per plant (TYP), of which, 12 QTL alleles positively contributed to TYP. Nine promising candidate genes for seven of the 12 QTL were identified including three known wheat genes and six rice orthologs. Four elite lines with TYP increased by 5.6%-15.2% were identified through genotype selection which carried 7-9 favorable alleles from JM22 and 2-3 favorable alleles from CM1 of the 12 QTL. Moreover, the linked SNPs of the 12 QTL were converted to high-throughput kompetitive allele-specific PCR (KASP) markers and validated in the population. The mapped QTL, identified promising candidate genes, developed elite lines and KASP markers are highly valuable in future genotype selection to improve wheat yield. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01496-3.

Association between mandibular prognathism and Matrilin-1, bone morphogenic protein, Tyr67Asn, homeobox protein hox-A2, Rho-GTPase activating protein, and Myosin 1H genes in the Indian population.

INTRODUCTION: Mandibular prognathism (MP) patients present with aesthetic concerns and functional issues, including difficulties in mastication and pronunciation. Studies revealed that mandibular prognathism had definitive Mendelian inheritance patterns. This study aimed to ascertain distinct genetic markers associated with mandibular prognathism in individuals of Indian descent, focusing on exploring the prevalent genetic variations associated with certain genes. This study sought to identify the association of the following gene markers with mandibular prognathism: 1) Matrilin-1 (MATN1) (rs1065755), 2) Bone morphogenic protein 3 (BMP-3) (Tyr67Asn), 3) Homeobox protein hox-A2 (HOXA2) (Val327Ile), 4) Rho-GTPase activating protein (ARHGAP 21) (Gly1121Ser), 5) Myosin 1H (MYO1H) (rs10850110).

GWAS Enhances Genomic Prediction Accuracy of Caviar Yield, Caviar Color and Body Weight Traits in Sturgeons Using Whole-Genome Sequencing Data.

Caviar yield, caviar color, and body weight are crucial economic traits in sturgeon breeding. Understanding the molecular mechanisms behind these traits is essential for their genetic improvement. In this study, we performed whole-genome sequencing on 673 Russian sturgeons, renowned for their high-quality caviar. With an average sequencing depth of 13.69×, we obtained approximately 10.41 million high-quality single nucleotide polymorphisms (SNPs). Using a genome-wide association study (GWAS) with a single-marker regression model, we identified SNPs and genes associated with these traits. Our findings revealed several candidate genes for each trait: caviar yield: TFAP2A, RPS6KA3, CRB3, TUBB, H2AFX, morc3, BAG1, RANBP2, PLA2G1B, and NYAP1; caviar color: NFX1, OTULIN, SRFBP1, PLEK, INHBA, and NARS; body weight: ACVR1, HTR4, fmnl2, INSIG2, GPD2, ACVR1C, TANC1, KCNH7, SLC16A13, XKR4, GALR2, RPL39, ACVR2A, ADCY10, and ZEB2. Additionally, using the genomic feature BLUP (GFBLUP) method, which combines linkage disequilibrium (LD) pruning markers with GWAS prior information, we improved genomic prediction accuracy by 2%, 1.9%, and 3.1% for caviar yield, caviar color, and body weight traits, respectively, compared to the GBLUP method. In conclusion, this study enhances our understanding of the genetic mechanisms underlying caviar yield, caviar color, and body weight traits in sturgeons, providing opportunities for genetic improvement of these traits through genomic selection.

Prioritization of candidate genes for major QTLs governing yield traits employing integrated multi-omics approach in rice (Oryza sativa L.).

Rapidly identifying candidate genes underlying major QTLs is crucial for improving rice (Oryza sativa L.). In this study, we developed a workflow to rapidly prioritize candidate genes underpinning 99 major QTLs governing yield component traits. This workflow integrates multiomics databases, including sequence variation, gene expression, gene ontology, co-expression analysis, and protein-protein interaction. We predicted 206 candidate genes for 99 reported QTLs governing ten economically important yield-contributing traits using this approach. Among these, transcription factors belonging to families of MADS-box, WRKY, helix-loop-helix, TCP, MYB, GRAS, auxin response factor, and nuclear transcription factor Y subunit were promising. Validation of key prioritized candidate genes in contrasting rice genotypes for sequence variation and differential expression identified Leucine-Rich Repeat family protein (LOC_Os03g28270) and cytochrome P450 (LOC_Os02g57290) as candidate genes for the major QTLs GL1 and pl2.1, which govern grain length and panicle length, respectively. In conclusion, this study demonstrates that our workflow can significantly narrow down a large number of annotated genes in a QTL to a very small number of the most probable candidates, achieving approximately a 21-fold reduction. These candidate genes have potential implications for enhancing rice yield.

Genome-wide association studies reveal the genetic basis of growth and carcass traits in Sichuan Shelduck.

China has abundant local duck resource populations, and evaluating the characteristics of these breeds will help improve development and utilization. In this study, we conducted the first investigations of growth and slaughter performance on Sichuan Shelduck (n = 240), an endangered duck local breed. The average body weight is 1497.91 g at 90 d of age. According to the growth curve through data recorded every 2 wk, we observed a low relative growth rate (RGR) for the early growth stage. The RGR shows a decreasing trend with age increasing in the stage from 0 to 56 d of age. The SNP-based heritability estimation showed the growth rate has a relatively high heritability, indicating high genetic stability for this trait. In the correlation analysis, the percentage of leg muscle is positively correlated with the absolute growth rate (AGR) at 28 to 42 d of age, whereas it is negatively correlated with the earlier stages, exhibiting a time-specific correlation result. Additionally, genome-wide association studies (GWAS) identified PCSK6, TOX2, and TOMM7 as potential candidate genes influencing AGR (42-56) and AGR (56-90), while the candidate genes of slaughter traits were PTP4A2, FAM110B, TOX, UBXN2B, and FCHSD2. These results provide an important reference for further understanding the genetic basis of growth and meat production performance of Sichuan Shelduck.

Identification of Dwarfing Candidate Genes in Brassica napus L. LSW2018 through BSA-Seq and Genetic Mapping.

Plant height, as a crucial component of plant architecture, exerts a significant influence on rapeseed (Brassica napus L.) lodging resistance, photosynthetic efficiency, yield, and mechanized harvest level. A previous study identified dwarf rapeseed LSW2018. In this study, LSW2018 (dwarf parent (PD)) was crossed with 389 (high parent (PH)) to establish the F2 population, and 30 extremely dwarf (bulk-D) and high (bulk-H) plants in the F2 population were respectively selected to construct two bulked DNA pools. Whole-genome sequencing and variation analysis (BSA-seq) were performed on these four DNA pools (PD, PH, bulk-D, and bulk-H). The BSA-seq results revealed that the genomic region responsible for the dwarf trait spanned from 19.30 to 22.19 Mb on chromosome A03, with a length of 2.89 Mb. After fine mapping with simple sequence repeat (SSR) markers, the gene was narrowed to a 0.71 Mb interval. Within this region, a total of 113 genes were identified, 42 of which contained large-effect variants. According to reference genome annotation and qRT-PCR analysis, there are 17 differentially expressed genes in this region between high and dwarf individuals. This study preliminarily reveals the genetic basis of LSW2018 dwarfing and provides a theoretical foundation for the molecular marker-assisted breeding of dwarf rapeseed.

Application of GWAS and mGWAS in Livestock and Poultry Breeding.

In recent years, genome-wide association studies (GWAS) and metabolome genome-wide association studies (mGWAS) have emerged as crucial methods for investigating complex traits in animals and plants. These have played pivotal roles in research on livestock and poultry breeding, facilitating a deeper understanding of genetic diversity, the relationship between genes, and genetic bases in livestock and poultry. This article provides a review of the applications of GWAS and mGWAS in animal genetic breeding, aiming to offer reference and inspiration for relevant researchers, promote innovation in animal genetic improvement and breeding methods, and contribute to the sustainable development of animal husbandry.

Densification of Genetic Map and Stable Quantitative Trait Locus Analysis for Amino Acid Content of Seed in Soybean (Glycine max L.).

Soybean, a primary vegetable protein source, boasts favorable amino acid profiles; however, its composition still falls short of meeting human nutritional demands. The soybean amino acid content is a quantitative trait controlled by multiple genes. In this study, an F2 population of 186 individual plants derived from the cross between ChangJiangChun2 and JiYu166 served as the mapping population. Based on the previously published genetic map of our lab, we increased the density of the genetic map and constructed a new genetic map containing 518 SSR (simple sequence repeats) markers and 64 InDel (insertion-deletion) markers, with an average distance of 5.27 cm and a total length of 2881.2 cm. The content of eight essential amino acids was evaluated in the F2:5, F2:6, and BLUP (best linear unbiased prediction). A total of 52 QTLs (quantitative trait loci) were identified, and 13 QTL clusters were identified, among which loci02.1 and loci11.1 emerged as stable QTL clusters, exploring candidate genes within these regions. Through GO enrichment and gene annotation, 16 candidate genes associated with soybean essential amino acid content were predicted. This study would lay the foundation for elucidating the regulatory mechanisms of essential amino acid content and contribute to germplasm innovation in soybeans.

Good parent-child relationship protects against alcohol use in maltreated adolescent females carrying the MAOA-uVNTR susceptibility allele.

Introduction: Risk-allele carriers of a Monoamine oxidase A (MAOA) gene, short-allele (MAOA-S) in males and long-allele (MAOA-L) in females, in the presence of a negative environment, are associated with alcohol misuse. Whether MAOA-S/L alleles also present susceptibility to a positive environment to mitigate the risk of alcohol misuse is unknown. Thus, we assessed the association of the three-way interaction of MAOA, maltreatment, and positive parent-child relationship with alcohol consumption among adolescents. Methods: This prospective study included 1416 adolescents (females: 59.88%) aged 16 - 19 years from Sweden, enrolled in the "Survey of Adolescent Life in Västmanland" in 2012. Adolescents self-reported alcohol consumption, maltreatment by a family (FM) or non-family member (NFM), parent-child relationship, and left saliva for MAOA genotyping. Results and discussion: We observed sex-dependent results. Females carrying MAOA-L with FM or NFM and a good parent-child relationship reported lower alcohol consumption than those with an average or poor parent-child relationship. In males, the interactions were not significant. Results suggest MAOA-L in females, conventionally regarded as a "risk", is a "plasticity" allele as it is differentially susceptible to negative and positive environments. Results highlight the importance of a good parent-child relationship in mitigating the risk of alcohol misuse in maltreated individuals carrying genetic risk. However, the interactions were not significant after adjusting to several environmental and behavioural covariates, especially parent's alcohol use, negative parent-child relationship, and nicotine use (smoking and/or snus), suggesting predictor and outcome intersection. Future studies and frameworks for preventive strategies should consider these covariates together with alcohol consumption. More studies with larger sample sizes are needed to replicate the findings.

Discovery of candidate genes involved in ethylene biosynthesis and signal transduction pathways related to peach bud cold resistance.

Background: Low temperature pose significant challenges to peach cultivation, causing severe damage to peach buds and restricting production and distribution. Ethylene, an important phytohormone, plays a critical role in enhancing plant cold resistance. Structural genes and transcription factors involved in ethylene biosynthesis and signal transduction pathways are associated with cold resistance. However, no research has specifically addressed their roles in peach cold resistance. Methods: In this study, we aimed for cold-resistance gene discovery in cold-sensitive peach cultivar "21Shiji" (21SJ) and cold-resistance cultivar "Shijizhixing" (SJZX) using RNA-seq and gas chromatography. Results: The findings revealed that under cold stress conditions, ethylene biosynthesis in "SJZX" was significantly induced. Subsequently, a structural gene, PpACO1-1, involved in ethylene biosynthesis in peach buds was significantly upregulated and showed a higher correlation with ethylene release rate. To identify potential transcription factors associated with PpACO1-1 expression and ethylene signal transduction, weighted gene co-expression network analysis was conducted using RNA-seq data. Four transcription factors: PpERF2, PpNAC078, PpWRKY65 and PpbHLH112, were identified. Conclusion: These findings provide valuable theoretical insights for investigating the regulatory mechanisms of peach cold resistance and guiding breeding strategies.

Identification of QTLs and candidate genes for water-soluble protein content in soybean seeds.

Soybean represents a vital source of premium plant-based proteins for human nutrition. Importantly, the level of water-soluble protein (WSP) is crucial for determining the overall quality and nutritional value of such crops. Enhancing WSP levels in soybean plants is a high-priority goal in crop improvement. This study aimed to elucidate the genetic basis of WSP content in soybean seeds by identifying quantitative trait loci (QTLs) and set the foundation for subsequent gene cloning and functional analysis. Using 180 F10 recombinant inbred lines generated by crossing the high-protein soybean cultivar JiDou 12 with the wild variety Ye 9, our researcher team mapped the QTLs influencing protein levels, integrating Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene expression profiling to identify candidate genes. During the 2020 and 2022 growing seasons, a standard bell-shaped distribution of protein content trait data was observed in these soybean lines. Eight QTLs affecting protein content were found across eight chromosomes, with LOD scores ranging from 2.59 to 7.30, explaining 4.15-11.74% of the phenotypic variance. Notably, two QTLs were newly discovered, one with a elite allele at qWSPC-15 from Ye 9. The major QTL, qWSPC-19, on chromosome 19 was stable across conditions and contained genes involved in nitrogen metabolism, amino acid biosynthesis, and signaling. Two genes from this QTL, Glyma.19G185700 and Glyma.19G186000, exhibited distinct expression patterns at maturity, highlighting the influence of these genes on protein content. This research revealed eight QTLs for WSP content in soybean seeds and proposed a gene for the key QTL qWSPC-19, laying groundwork for gene isolation and enhanced soybean breeding through the use of molecular markers. These insights are instrumental for developing protein-rich soybean cultivars.

Mapping of dynamic quantitative trait loci for plant height in a RIL population of foxtail millet (Setaria italica L.).

Plant height (PH) is a crucial trait for strengthening lodging resistance and boosting yield in foxtail millet. To identify quantitative trait loci (QTL) and candidate genes associated with PH, we first developed a genetic map using a recombinant inbred line (RIL) population derived from a cross between Aininghuang and Jingu 21. Then, PH phenotyping data and four variations of best linear unbiased prediction (BLUP) were collected from nine environments and three development stages. Next, QTL mapping was conducted using both unconditional and conditional QTL methods. Subsequently, candidate genes were predicted via transcriptome analysis of parental samples at three developmental stages. The results revealed that the genetic map, based on re-sequencing, consisted of 4,360 bin markers spanning 1,016.06 cM with an average genetic distance of 0.23 cM. A total of 19 unconditional QTL, accounting for 5.23%-35.36% of the phenotypic variation explained (PVE), which included 7 major and 4 stable QTL, were identified. Meanwhile, 13 conditional QTL, explaining 5.88%-40.35% of PVE, including 5 major and 3 stable QTL, were discovered. Furthermore, four consistent and stable QTL were identified. Finally, eight candidate genes were predicted through RNA-seq and weighted gene co-expression network analysis (WGCNA). Those findings provide a crucial foundation for understanding the genetic mechanisms underlying PH development and facilitate molecular marker-assisted breeding of ideal plant types in foxtail millet.

Linkage Mapping and Discovery of Candidate Genes for Drought Tolerance in Rice During the Vegetative Growth Period.

Drought is a major abiotic stress affecting crop yields. Mapping quantitative trait loci (QTLs) and mining genes for drought tolerance in rice are important for identifying gene functions and targets for molecular breeding. Here, we performed linkage analysis of drought tolerance using a recombinant inbred line population derived from Jileng 1 (drought sensitive) and Milyang 23 (drought tolerant). An ultra-high-density genetic map, previously constructed by our research team using genotype data from whole-genome sequencing, was used in combination with phenotypic data for rice grown under drought stress conditions in the field in 2017-2019. Thirty-nine QTLs related to leaf rolling index and leaf withering degree were identified, and QTLs were found on all chromosomes except chromosomes 6, 10, and 11. qLWD4-1 was detected after 32 days and 46 days of drought stress in 2017 and explained 7.07-8.19% of the phenotypic variation. Two loci, qLRI2-2 and qLWD4-2, were identified after 29, 42, and 57 days of drought stress in 2018. These loci explained 10.59-17.04% and 5.14-5.71% of the phenotypic variation, respectively. There were 281 genes within the QTL interval. Through gene functional annotation and expression analysis, two candidate genes, Os04g0574600 and OsCHR731, were found. Quantitative reverse transcription PCR analysis showed that the expression levels of these genes were significantly higher under drought stress than under normal conditions, indicating positive regulation. Notably, Os04g0574600 was a newly discovered drought tolerance gene. Haplotype analysis showed that the RIL population carried two haplotypes (Hap1 and Hap2) of both genes. Lines carrying Hap2 exhibited significantly or extremely stronger drought tolerance than those carrying Hap1, indicating that Hap2 is an excellent haplotype. Among rice germplasm resources, there were two and three haplotypes of Os04g0574600 and OsCHR731, respectively. A high proportion of local rice resources in Sichuan, Yunnan, Anhui, Guangdong and Fujian provinces had Hap of both genes. In wild rice, 50% of accessions contained Hap1 of Os04g0574600 and 50% carried Hap4; 13.51%, 59.46% and 27.03% of wild rice accessions contained Hap1, Hap2, and Hap3, respectively. Hap2 of Os04g0574600 was found in more indica rice resources than in japonica rice. Therefore, Hap2 has more potential for utilization in future drought tolerance breeding of japonica rice.

Whole genome resequencing reveals the adaptability of native chickens to drought, tropical and frigid environments in Xinjiang.

Chickens exhibit extensive genetic diversity and are distributed worldwide. Different chicken breeds have evolved to thrive in diverse environmental conditions. However, research on the genetic mechanisms underlying chicken adaptation to extreme environments, such as tropical, frigid and drought-prone regions, remains limited. In this study, we conducted whole-genome sequencing of 240 individuals from six native chicken breeds in Xinjiang, China, as well as 4 publicly available chicken breeds inhabiting regions with varying annual precipitations, temperatures, and altitudes. Our analysis revealed several genetic variants among the examined breeds. Furthermore, we investigated the genetic diversity and population structure of breeds residing in extreme drought and temperature environments by comparing them. Notably, native chicken breeds exhibited different genetic diversity and population structures. Moreover, we identified candidate genes associated with chicken adaptability to the environment, such as CORO2A, CTNNA3, AGMO, GRID2, BBOX1, COL3A1, INSR, SOX5, MAP2 and PLPPR1. Additionally, pathways such as lysosome, cysteine and methionine metabolism, glycosaminoglycan degradation, and Wnt signaling may be play crucial roles in regulating chicken adaptation to drought environments. Overall, these findings contribute to our understanding of the genetic mechanisms governing chicken adaptation to extreme environments, and also offer insights for enhancing the resilience of chicken breeds to different climatic conditions.

Genome-wide association study identified candidate genes for egg production traits in the Longyan Shan-ma duck.

Egg production is an important economic trait in layer ducks and understanding the genetics basis is important for their breeding. In this study, a genome-wide association study (GWAS) for egg production traits in 303 female Longyan Shan-ma ducks was performed based on a genotyping-by-sequencing strategy. Sixty-two single nucleotide polymorphisms (SNPs) associated with egg weight traits were identified (P < 9.48 × 10-5), including 8 SNPs at 5% linkage disequilibrium (LD)-based Bonferroni-corrected genome-wide significance level (P < 4.74 × 10-6). One hundred and nineteen SNPs were associated with egg number traits (P < 9.48 × 10-5), including 13 SNPs with 5% LD-based Bonferroni-corrected genome-wide significance (P < 4.74 × 10-6). These SNPs annotated 146 target genes which contained known candidate genes for egg production traits, such as prolactin and prolactin releasing hormone receptor. This study identified that these associated genes were significantly enriched in egg production-related pathways (P < 0.05), such as the oxytocin signaling, MAPK signaling, and calcium signaling pathways. It was notable that 18 genes were differentially expressed in ovarian tissues between higher and lower egg production in Shan-ma ducks. The identified potential candidate genes and pathways provide insight into the genetic basis underlying the egg production trait of layer ducks.

Further screening of SNP loci of eggshell translucency related genes and evaluation of genetic effects.

Eggshell translucency is a widespread issue in the field of egg quality. Previous research has established that the heritability of eggshell translucency is relatively low or moderate. Scientists have also successfully identified SNP loci related to eggshell translucency on different chromosomes by using gene chips and single-variant GWAS. However, the specific impact of single or multiple genes on the trait of eggshell translucency remains unknown. In an effort to investigate this, we examined 170 SNPs associated with eggshell translucency obtained by our research group. We selected 966 half-sibling laying hens from 2 generations in 3 pure lines: Dwarf Layer-White, Rhode Island Red-White Strain, and Rhode Island Red. Eggs were collected from each hen over a period of 5 consecutive days, and eggshell translucency was measured using a grading method in which the hens were divided into 2 groups: an opaque group and a translucent group. We collected blood samples from the laying hens and extracted DNA. Time of flight mass spectrometry (TOF-MS) was used for genotyping to identify SNP loci that influence the trait of eggshell translucency. The results of our analysis revealed that using TOF-MS in 3 chicken strains, we were able to eliminate loci with low gene polymorphism, genetic effect contribution less than 1%, and deviation from Hardy-Weinberg equilibrium. Ultimately, 5 SNPs (Affx-50362599, rs15050262, rs312943734, rs316121113, and rs317389181) were identified on chromosomes 1, 5, and 19. Additionally, nine candidate genes (DCN, BTG1, ZFP92, POU2F1, NUCB2, FTL, GGNBP2, ACACA, and TADA2A) were found to be associated with these SNPs. No linkage disequilibrium relationship was observed between the 2 pairs of SNP loci on chromosomes 1 and 19. Based on previous studies on the formation mechanism of eggshell translucency, we hypothesize that NUCB2, FTL, and ACACA genes may be affecting the eggshell structure through different mechanisms, such as increase the water permeability or make thin of eggshell membrane, which promote moisture or part of other egg contents and ultimately lead to the formation of eggshell translucency. These findings validate and identify five SNP loci that regulate the translucency trait, and provide molecular markers for breeding non-translucent populations. Furthermore, this study serves as a reference for further investigation of the genetic regulatory mechanisms underlying eggshell translucency.

QTL detection and candidate gene identification of qCTB1 for cold tolerance in the Yunnan plateau landrace rice.

Cold stress is one of the main abiotic stresses that affects rice growth and production worldwide. Dissection of the genetic basis is important for genetic improvement of cold tolerance in rice. In this study, a new source of cold-tolerant accession from the Yunnan plateau, Lijiangxiaoheigu, was used as the donor parent and crossed with a cold-sensitive cultivar, Deyou17, to develop recombinant inbred lines (RILs) for quantitative trait locus (QTL) analysis for cold tolerance at the early seedling and booting stages in rice. In total, three QTLs for cold tolerance at the early seedling stage on chromosomes 2 and 7, and four QTLs at the booting stage on chromosomes 1, 3, 5, and 7, were identified. Haplotype and linear regression analyses showed that QTL pyramiding based on the additive effect of these favorable loci has good potential for cold tolerance breeding. Effect assessment in the RIL and BC3F3 populations demonstrated that qCTB1 had a stable effect on cold tolerance at the booting stage in the genetic segregation populations. Under different cold stress conditions, qCTB1 was fine-mapped to a 341-kb interval between markers M3 and M4. Through the combination of parental sequence comparison, candidate gene-based association analysis, and tissue and cold-induced expression analyses, eight important candidate genes for qCTB1 were identified. This study will provide genetic resources for molecular breeding and gene cloning to improve cold tolerance in rice. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01488-3.

Role of MTHFR, IRF6, PAX7 and TP63 SNPs in susceptibility to non-syndromic orofacial cleft, a candidate gene study in a Portuguese population.

BACKGROUND: Non-syndromic orofacial cleft (NSOC) is a complex phenotype, involving multiple genetic and environmental factors. Association studies exploring the genetic susceptibility to this prevalent oral malformation show variability of results in different populations. Using a candidate gene approach, we aimed to verify the role of four single-nucleotide polymorphisms (SNPs) in the susceptibility to NSOC in Portuguese patients. METHODS: A total of 254 non-consanguineous individuals of Portuguese were recruited, including 120 patients with NSOC and 134 controls. About 92% of these patients had non-syndromic cleft lip with or without cleft palate (NSCL/P) and 8% had only non-syndromic cleft palate (NSCP). SNPs in the MTHFR (rs1801133), IRF6 (rs642961), PAX7 (rs742071) and TP63 (rs9332461) genes were studied, using a real-time approach with TaqMan probes. Allelic, genotypic, dominant, recessive and over-dominant models were explored using a chi-squared test. Adjusted p-value was calculated for multiple comparisons using the Benjamini-Hochberg false discovery rate (FDR). RESULTS: All SNPs were in Hardy-Weinberg equilibrium. For MTHFR, IRF6, and PAX7 SNPs, no statistically significant difference was highlighted for any of the evaluated models. For TP63 SNP, data fitted an over-dominant model, with a protective effect for heterozygotes (OR 1.897; CI 95% [1.144-3.147]; p < .016, when comparing controls vs. cases), but significance was lost when applying adjusted p-value for multiple comparisons (4 × 5 tests). CONCLUSION: In this Portuguese population, there was no evidence of an association between the evaluated SNPs and NSOC. For TP63 SNP, the possibility of a protective effect of heterozygotes should be further investigated.

Genome-wide association mapping of quantitative trait loci for chalkiness-related traits in rice (Oryza sativa L.).

Grain chalkiness directly affects the commercial value of rice. Genes related to chalkiness reported thus far have been discovered in mutants, but it has not been identified whether these genes can be used to improve rice quality by breeding. Therefore, discovering more quantitative trait loci (QTLs) or genes related to chalkiness in the rice germplasm is necessary. This study entails a genome-wide association study on the degree of endosperm chalkiness (DEC) and percentage of grains with chalkiness (PGWC) by combining 1.2 million single-nucleotide polymorphisms (SNPs) with the phenotypic data of 173 rice accessions. Thirteen QTLs for DEC and nine for PGWC were identified, of which four were detected simultaneously for both DEC and PGWC; further, qDEC11/qPGWC11 was identified as the major QTL. By combining linkage disequilibrium analysis and SNP information, LOC_Os11g10170 was identified as the candidate gene for DEC. There were significant differences among the haplotypes of LOC_Os11g10170, and the Hap 1 of LOC_Os11g10170 was observed to reduce the DEC by 6.19%. The qRT-PCR results showed that the gene expression levels in accessions with high DEC values were significantly higher than those in accessions with low DEC values during days 21-42 after flowering, with a maximum at 28 days. These results provide molecular markers and germplasm resources for genetic improvement of the chalkiness-related traits in rice.

Exploring the genetic architecture of powdery mildew resistance in wheat through QTL meta-analysis.

Powdery mildew (PM), caused by Blumeria graminis f. sp. tritici, poses a significant threat to wheat production, necessitating the development of genetically resistant varieties for long-term control. Therefore, exploring genetic architecture of PM in wheat to uncover important genomic regions is an important area of wheat research. In recent years, the utilization of meta-QTL (MQTL) analysis has gained prominence as an essential tool for unraveling the complex genetic architecture underlying complex quantitative traits. The aim of this research was to conduct a QTL meta-analysis to pinpoint the specific genomic regions in wheat responsible for governing PM resistance. This study integrated 222 QTLs from 33 linkage-based studies using a consensus map with 54,672 markers. The analysis revealed 39 MQTLs, refined to 9 high-confidence MQTLs (hcMQTLs) with confidence intervals of 0.49 to 12.94 cM. The MQTLs had an average physical interval of 41.00 Mb, ranging from 0.000048 Mb to 380.71 Mb per MQTL. Importantly, 18 MQTLs co-localized with known resistance genes like Pm2, Pm3, Pm8, Pm21, Pm38, and Pm41. The study identified 256 gene models within hcMQTLs, providing potential targets for marker-assisted breeding and genomic prediction programs to enhance PM resistance. These MQTLs would serve as a foundation for fine mapping, gene isolation, and functional genomics studies, facilitating a deeper understanding of molecular mechanisms. The identification of candidate genes opens up exciting possibilities for the development of PM-resistant wheat varieties after validation.