QTL Genes Research Articles

QTL and candidate genes for heterophylly in soybean based on two populations of recombinant inbred lines.

Heterophylly, the existence of different leaf shapes and sizes on the same plant, has been observed in many flowering plant species. Yet, the genetic characteristics and genetic basis of heterophylly in soybean remain unknown. Here, two populations of recombinant inbred lines (RILs) with distinctly different leaf shapes were used to identify loci controlling heterophylly in two environments. The ratio of apical leaf shape (LSUP) to basal leaf shape (LSDOWN) at the reproductive growth stage (RLS) was used as a parameter for classifying heterophylly. A total of eight QTL were detected for RLS between the two populations and four of them were stably identified in both environments. Among them, qRLS20 had the largest effect in the JS population, with a maximum LOD value of 46.9 explaining up to 47.2% of phenotypic variance. This locus was located in the same genomic region as the basal leaf shape QTL qLSDOWN20 on chromosome 20. The locus qRLS19 had the largest effect in the JJ population, with a maximum LOD value of 15.2 explaining up to 27.0% of phenotypic variance. This locus was located in the same genomic region as the apical leaf shape QTL qLSUP19 on chromosome 19. Four candidate genes for heterophylly were identified based on sequence differences among the three parents of the two mapping populations, RT-qPCR analysis, and gene functional annotation analysis. The QTL and candidate genes detected in this study lay a foundation for further understanding the genetic mechanism of heterophylly and are invaluable in marker-assisted breeding.

Identification of single major QTL and candidate gene(s) governing hull-less seed trait in pumpkin.

The hull-less pumpkin (Cucurbita pepo) seed does not require de-hulling before use for human consumption, as a result highly preferred by the oil, nut, and baking industries. In hull-less seeds, a single recessive gene is responsible for the absence of outer thick seed coat layers; however, the genomic region and gene(s) controlling the trait are unclear to date. In this study, four crosses attempted to derive F2 and backcross populations confirmed the single recessive gene inheritance of hull-less seed trait in populations adapted to the sub-tropical climate. The candidate genomic region for hull-less seed trait was identified through the BSA-QTLseq approach using bulks of F2:3 progenies from a cross of HP111 (hulled) and HLP36 (hull-less). A novel genomic region on chromosome 12 ranging from 1.80 to 3.86 Mb was associated with the hull-less seed trait. The re-sequencing data identified a total of 396 SNPs within this region and eight were successfully converted into polymorphic KASP assays. The genotyping of segregating F2 (n = 160) with polymorphic KASP assays resulted in a 40.3 cM partial linkage map and identified Cp_3430407 (10 cM) and Cp_3498687 (16.1 cM) as flanking markers for hull-less locus (Cphl-1). These flanking markers correspond to the 68.28 kb region in the reference genome, and the marker, Cp_3430407 successfully predicted the genotype in 93.33% of the C. pepo hull-less germplasm lines, thus can be used for marker-assisted selection in parents polymorphic for the hull-less seed trait. The Cphl-1-linked genomic region (2.06 Mb) encompasses a total of 182 genes, including secondary cell wall and lignin biosynthesis-related transcriptional factors viz., “NAC” (Cp4.1LG12g04350) and “MYB” (Cp4.1LG12g03120). These genes were differentially expressed in the seeds of hulled and hull-less genotypes, and therefore could be the potential candidate genes governing the hull-less seed trait in pumpkin.

Genetic detection and identification of the candidate resistance gene for a major QTL resistant to Puccinia polysora in maize

Southern corn rust (SCR) is a major foliar disease in maize. Identification the major QTL and candidate resistance gene is prerequisite in maize resistance breeding programs. To identify major resistance loci/gene(s) resistant to SCR, a recombinant inbred line (RIL) population derived from a cross between 975 and 12 (resistant) and Lx9801 (susceptible) was analyzed. In total four QTLs were identified, which were located on chromosomes 5, 9 and 10, respectively. Among them, a major QTL on chromosome 10 (qSCR3), were detected in all the environments, which can explain 70.3–78.4% of the total phenotypic variation. Fine-mapping of qSCR3 delimited the QTL to an interval of ∼225 Kb. Using transcripts assembly of the 975–12 and a susceptible mutant (975-12S), an NLR gene, Zm00025ab420970, was identified as the candidate gene for qSCR3, which is a new allele/gene resistant to SCR in maize. Since qSCR3 is a major QTL resistant to SCR, it can be used as a desirable resistance source in maize resistance breeding programs.

Whole-Genome Sequencing of KMR3 and Oryza rufipogon-Derived Introgression Line IL50-13 (Chinsurah Nona 2/Gosaba 6) Identifies Candidate Genes for High Yield and Salinity Tolerance in Rice.

The genomes of an elite rice restorer line KMR3 (salinity-sensitive) and its salinity-tolerant introgression line IL50-13, a popular variety of coastal West Bengal, India, were sequenced. High-quality paired-end reads were obtained for KMR3 (147.6 million) and IL50-13 (131.4 million) with a sequencing coverage of 30X-39X. Scaffolds generated from the pre-assembled contigs of each sequenced genome were mapped separately onto the reference genome of Oryza sativa ssp. japonica cultivar Nipponbare to identify genomic variants in terms of SNPs and InDels. The SNPs and InDels identified for KMR3 and IL50-13 were then compared with each other to identify polymorphic SNPs and InDels unique and common to both the genomes. Functional enrichment analysis of the protein-coding genes with unique InDels identified GO terms involved in protein modification, ubiquitination, deubiquitination, peroxidase activity, and antioxidant activity in IL50-13. Linoleic acid metabolism, circadian rhythm, and alpha-linolenic acid metabolism pathways were enriched in IL50-13. These GO terms and pathways are involved in reducing oxidative damage, thus suggesting their role in stress responses. Sequence analysis of QTL markers or genes known to be associated with grain yield and salinity tolerance showed polymorphism in 20 genes, out of which nine were not previously reported. These candidate genes encoded Nucleotide-binding adaptor shared by APAF-1, R proteins, and CED-4 (NB-ARC) domain-containing protein, cyclase, receptor-like kinase, topoisomerase II-associated protein PAT1 domain-containing protein, ion channel regulatory protein, UNC-93 domain-containing protein, subunit A of the heteromeric ATP-citrate lyase, and three conserved hypothetical genes. Polymorphism was observed in the coding, intron, and untranslated regions of the genes on chromosomes 1, 2, 4, 7, 11, and 12. Genes showing polymorphism between the two genomes were considered as sequence-based new candidates derived from Oryza rufipogon for conferring high yield and salinity tolerance in IL50-13 for further functional studies.

Mapping of QTL and candidate genes associated with powdery mildew resistance in triticale (× Triticosecale Wittm.)

Mapping of QTL and candidate genes associated with powdery mildew resistance in triticale (× Triticosecale Wittm.)

Unraveling the Genetic Architecture for Low Temperature Germinability-Related Traits in Rice Using Genome-Wide Association Study

Rice is frequently affected by cold weather at high altitudes in temperate and subtropical regions. With the popularity of direct seeding, a better understanding of the genetic mechanisms regulating cold tolerance will enable breeders to develop varieties with strong low temperature germinability (LTG). In this study, six indices including low temperature germination percentage (LTGP), relative germination percentage (RGP), relative plumule length (RPL), plumule length after 6-day recovery (PLR), plumule length recovery rate (PLRR) and recovery ability of plumule length after cold stress (RAPL) were measured to assess LTG, and carried out a genome-wide association study (GWAS) to identify QTL and candidate genes related to LTG by using a natural population comprising 211 rice accessions. A total of 18 QTL including two for LTGP, three for RGP, five for PLR, four for PLRR, two for RPL and two for RAPL were uncovered on 12 chromosome regions located in chromosome 1, 2, 4, 5, 6, 9, 10 and 12. On chromosome 2, qLTGP2 and qRGP2 were co-localized at 3.3 Mb, and qPLR2 and qPLRR2 were co-localized at 5.5 Mb; qLTGP5, qPLR5 and qPLR5 were co-localized at 27.8 Mb on chromosome 5; qPLR6 and qPLRR6 were co-localized at 5.7 Mb on chromosome 6; and qPLR12 and qPLRR12 were co-localized at 23.5 Mb on chromosome 12. These results indicated that some LTG-related traits may share the same genetic pathway. For the 18 LTG-related QTL, seven QTL (qLTGP2, qRGP2, qPLR2, qPLRR2, qLTGP5, qPLR5 and qPLR5) were reported for the first time. According to candidate gene analysis, fourteen genes from five QTL (qLTGP2, qPLR2, qLTGP5, qRAPL10 and qPLR12) were considered as candidate genes and will be further functionally validated in subsequent experiments. QTL with superior candidate genes identified in this study will be useful in improving cold tolerance in rice cultivars. The rice varieties with strong LTG identified in this study will enrich the resources of rice cultivation project.

Dwarfing gene Rht24 does not affect Fusarium head blight resistance in a large European winter wheat diversity panel

Reduced height (Rht) genes are widely used in modern wheat breeding although some confer higher susceptibility to Fusarium head blight (FHB) caused by F. graminearum and other species. Our objective was to test whether the recently identified Rht24b dwarfing allele has a neutral effect on FHB response as reported previously from a single mapping population when unrelated winter wheat cultivars were analyzed. We artificially infected a panel of 420 cultivars divided into four genotypic groups (Rht24a + Rht-D1a, Rht24b + Rht-D1a, Rht24a + Rht-D1b, Rht24b + Rht-D1b) with Fusarium culmorum in five location-year combinations. High and significant (P ≤ 0.001) genetic variance for FHB severity and plant height (PH) was found in the entire panel as well as within the four Rht groups and both traits showed high entry-mean heritabilities of 0.92 and 0.98, respectively. Rht24b had no significant effect on FHB severity whereas Rht-D1b increased FHB susceptibility by 37%. The 29 most resistant cultivars either had the tallness alleles of the above mentioned Rht-D1 gene or Rht24b alone. The Rht24b + Rht-D1b combination had no significantly higher FHB severity than Rht-D1b alone. However, Rht24b reduced average PH only by 6.8 cm, whereas Rht-D1b conferred a reduction of 13.6 cm. For breeding short, FHB-resistant germplasm the neutral Rht24 gene must be complemented by further QTL or other FHB-neutral Rht genes.

Development and Application of a Target Capture Sequencing SNP-Genotyping Platform in Rice.

The development of efficient, robust, and high-throughput SNP genotyping platforms is pivotal for crop genetics and breeding. Recently, SNP genotyping platforms based on target capture sequencing, which is very flexible in terms of the number of SNP markers, have been developed for maize, cassava, and fava bean. We aimed to develop a target capture sequencing SNP genotyping platform for rice. A target capture sequencing panel containing 2565 SNPs, including 1225 SNPs informative for japonica and 1339 SNPs informative for indica, was developed. This platform was used in diversity analysis of 50 rice varieties. Of the 2565 SNP markers, 2341 (91.3%) produced useful polymorphic genotype data, enabling the production of a phylogenetic tree of the 50 varieties. The mean number of markers polymorphic between any two varieties was 854. The platform was used for QTL mapping of preharvest sprouting (PHS) resistance in an F8 recombinant inbred line population derived from the cross Odae × Joun. A genetic map comprising 475 markers was constructed, and two QTLs for PHS resistance were identified on chromosomes 4 and 11. This system is a powerful tool for rice genetics and breeding and will facilitate QTL studies and gene mapping, germplasm diversity analysis, and marker-assisted selection.

A Genetic Resource for Rice Improvement: Introgression Library of Agronomic Traits for All AA Genome Oryza Species.

Rice improvement depends on the availability of genetic variation, and AA genome Oryza species are the natural reservoir of favorable alleles that are useful for rice breeding. To systematically evaluate and utilize potentially valuable traits of new QTLs or genes for the Asian cultivated rice improvement from all AA genome Oryza species, 6,372 agronomic trait introgression lines (ILs) from BC2 to BC6 were screened and raised based on the variations in agronomic traits by crossing 170 accessions of 7 AA genome species and 160 upland rice accessions of O. sativa as the donor parents, with three elite cultivars of O. sativa, Dianjingyou 1 (a japonica variety), Yundao 1 (a japonica variety), and RD23 (an indica variety) as the recurrent parents, respectively. The agronomic traits, such as spreading panicle, erect panicle, dense panicle, lax panicle, awn, prostrate growth, plant height, pericarp color, kernel color, glabrous hull, grain size, 1,000-grain weight, drought resistance and aerobic adaption, and blast resistance, were derived from more than one species. Further, 1,401 agronomic trait ILs in the Dianjingyou 1 background were genotyped using 168 SSR markers distributed on the whole genome. A total of twenty-two novel allelic variations were identified to be highly related to the traits of grain length (GL) and grain width (GW), respectively. In addition, allelic variations for the same locus were detected from the different donor species, which suggest that these QTLs or genes were conserved and the different haplotypes of a QTL (gene) were valuable resources for broadening the genetic basis in Asian cultivated rice. Thus, this agronomic trait introgression library from multiple species and accessions provided a powerful resource for future rice improvement and genetic dissection of agronomic traits.

Detecting QTL and Candidate Genes for Plant Height in Soybean via Linkage Analysis and GWAS.

Soybean is an important global crop for edible protein and oil, and plant height is a main breeding goal which is closely related to its plant shape and yield. In this research, a high-density genetic linkage map was constructed by 1996 SNP-bin markers on the basis of a recombinant inbred line population derived from Dongnong L13 × Henong 60. A total of 33 QTL related to plant height were identified, of which five were repeatedly detected in multiple environments. In addition, a 455-germplasm population with 63,306 SNP markers was used for multi-locus association analysis. A total of 62 plant height QTN were detected, of which 26 were detected repeatedly under multiple methods. Two candidate genes, Glyma.02G133000 and Glyma.05G240600, involving in plant height were predicted by pathway analysis in the regions identified by multiple environments and backgrounds, and validated by qRT-PCR. These results enriched the soybean plant height regulatory network and contributed to molecular selection-assisted breeding.

Ukrainian Holstein cattle DNA polymorphism study

The aim of the research was to evaluate the genetic structure of Ukrainian Holstein cattle (n = 150) of the state enterprise Chayka (Kiev region, Ukraine) on the basis of the analysis of 12 microsatellite DNA loci and 3 QTL genes: k-casein (CSN3), prolactin (PRL), and fatty acid synthase (FASN). A total of 93 allelic variants were identified, and the largest number of alleles were found for TGLA53, TGLA122 and TGLA227 loci, the mean PIC = 0.693, and the heterozygosity index for all loci was 0.7314. The greatest number of effective alleles per locus were found for the BM1824 locus. Based on association analyses, complex genotypes were established for the three genes (CSN3, PRL, FASN). It was found that the AAPRL AACSN3 AAFASN genotype determined the highest milk yield (8351 kg / lactation) and the protein content in milk (3.10%), whereas the AAPRL ABCSN3 GGFASN genotype determined the highest level of fat content in milk (3.80%).

Candidate genes for congenital malformations in pigs

Candidate genes for congenital malformations in pigs

Genetic dissection of grain architecture-related traits in a winter wheat population

BackgroundThe future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. Thousand kernel weight (TKW) in wheat is closely associated with grain architecture-related traits, e.g. kernel length (KL), kernel width (KW), kernel area (KA), kernel diameter ratio (KDR), and factor form density (FFD). Discovering the genetic architecture of natural variation in these traits, identifying QTL and candidate genes are the main aims of this study. Therefore, grain architecture-related traits in 261 worldwide winter accessions over three field-year experiments were evaluated.ResultsGenome-wide association analysis using 90K SNP array in FarmCPU model revealed several interesting genomic regions including 17 significant SNPs passing false discovery rate threshold and strongly associated with the studied traits. Four of associated SNPs were physically located inside candidate genes within LD interval e.g. BobWhite_c5872_589 (602,710,399 bp) found to be inside TraesCS6A01G383800 (602,699,767–602,711,726 bp). Further analysis reveals the four novel candidate genes potentially involved in more than one grain architecture-related traits with a pleiotropic effects e.g. TraesCS6A01G383800 gene on 6A encoding oxidoreductase activity was associated with TKW and KA. The allelic variation at the associated SNPs showed significant differences betweeen the accessions carying the wild and mutated alleles e.g. accessions carying C allele of BobWhite_c5872_589, TraesCS6A01G383800 had significantly higher TKW than the accessions carying T allele. Interestingly, these genes were highly expressed in the grain-tissues, demonstrating their pivotal role in controlling the grain architecture.ConclusionsThese results are valuable for identifying regions associated with kernel weight and dimensions and potentially help breeders in improving kernel weight and architecture-related traits in order to increase wheat yield potential and end-use quality.

Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle

BackgroundFourier-transform mid-infrared (FT-MIR) spectroscopy provides a high-throughput and inexpensive method for predicting milk composition and other novel traits from milk samples. While there have been many genome-wide association studies (GWAS) conducted on FT-MIR predicted traits, there have been few GWAS for individual FT-MIR wavenumbers. Using imputed whole-genome sequence for 38,085 mixed-breed New Zealand dairy cattle, we conducted GWAS on 895 individual FT-MIR wavenumber phenotypes, and assessed the value of these direct phenotypes for identifying candidate causal genes and variants, and improving our understanding of the physico-chemical properties of milk.ResultsSeparate GWAS conducted for each of 895 individual FT-MIR wavenumber phenotypes, identified 450 1-Mbp genomic regions with significant FT-MIR wavenumber QTL, compared to 246 1-Mbp genomic regions with QTL identified for FT-MIR predicted milk composition traits. Use of mammary RNA-seq data and gene annotation information identified 38 co-localized and co-segregating expression QTL (eQTL), and 31 protein-sequence mutations for FT-MIR wavenumber phenotypes, the latter including a null mutation in the ABO gene that has a potential role in changing milk oligosaccharide profiles. For the candidate causative genes implicated in these analyses, we examined the strength of association between relevant loci and each wavenumber across the mid-infrared spectrum. This revealed shared association patterns for groups of genomically-distant loci, highlighting clusters of loci linked through their biological roles in lactation and their presumed impacts on the chemical composition of milk.ConclusionsThis study demonstrates the utility of FT-MIR wavenumber phenotypes for improving our understanding of milk composition, presenting a larger number of QTL and putative causative genes and variants than found from FT-MIR predicted composition traits. Examining patterns of significance across the mid-infrared spectrum for loci of interest further highlighted commonalities of association, which likely reflects the physico-chemical properties of milk constituents.

Identification of QTL related to anther color and hull color by RAD sequencing in a RIL population of Setaria italica

BackgroundFoxtail millet (Setaria italica) is one of the oldest domesticated crops and has been considered as an ideal model plant for C4 grasses. It has abundant type of anther and hull colors which is not only a most intuitive morphological marker for color selection in seed production, but also has very important biological significance for the study of molecular mechanism of regulating the synthesis and metabolism of flavonoids and lignin. However, only a few genetic studies have been reported for anther color and hull color in foxtail millet.ResultsQuantitative trait loci (QTL) analysis for anther color and hull color was conducted using 400 F6 and F7 recombinant inbreed lines (RILs) derived from a cross between parents Yugu18 and Jigu19. Using restriction-site associated DNA sequencing, 43,001 single-nucleotide polymorphisms (SNPs) and 3,022 indels were identified between both the parents and the RILs. A total of 1,304 bin markers developed from the SNPs and indels were used to construct a genetic map that spanned 2196 cM of the foxtail millet genome with an average of 1.68 cM/bin. Combined with this genetic map and the phenotypic data observed in two locations for two years, two QTL located on chromosome 6 (Chr6) in a 1.215-Mb interval (33,627,819–34,877,940 bp) for anther color (yellow - white) and three QTL located on Chr1 in a 6.23-Mb interval (1–6,229,734 bp) for hull color (gold-reddish brown) were detected. To narrow the QTL regions identified from the genetic map and QTL analysis, we developed a new method named “inconsistent rate analysis” and efficiently narrowed the QTL regions of anther color into a 60-kb interval (34.13–34.19 Mb) in Chr6, and narrowed the QTL regions of hull color into 70-kb (5.43–5.50 Mb) and 30-kb (5.69–5.72 Mb) intervals in Chr1. Two genes (Seita.6G228600.v2.2 and Seita.6G228700.v2.2) and a cinnamyl alcohol dehydrogenase (CAD) gene (Seita.1G057300.v2.2) with amino acid changes between the parents detected by whole-genome resequencing were identified as candidate genes for anther and hull color, respectively.ConclusionsThis work presents the related QTL and candidate genes of anther and hull color in foxtail millet and developed a new method named inconsistent rate analysis to detect the chromosome fragments linked with the quality trait in RILs. This is the first study of the QTL related to hull color in foxtail millet and clarifying that the CAD gene (Seita.1G057300.v2.2) is the key gene responsible for this trait. It lays the foundation for further cloning of the functional genes and provides a powerful tool to detect the chromosome fragments linked with quality traits in RILs.

Haemoglobin switching modulator SNPs rs5006884 is associated with increased HbA2 in β-thalassaemia carriers.

IntroductionHaemoglobin A2 (HbA2), the tetramer of α- and δ-globin chains, is used as a diagnostic biomarker for β-thalassaemia carriers. The HbA2 levels are regulated by the presence of HPFH, δ-thalassaemia, HbA1/2 gene triplication, and variants of KLF1, β-globin gene, and HbF regulating QTLs. Saudi Arabia has a high incidence of borderline HbA2 levels, thereby making it difficult to classify the haemoglobinopathies. This study aims to investigate the association of known HbF enhancer QTL gene SNPs with HbA2 levelsMaterial and methods14 Specific SNPs in BCL11A, HMIP, OR51B6, HBBP1, and HBG2 loci were genotyped in 164 Saudi β-thalassaemia carriers by TaqMan assay to validate their role as regulators of HbA2 levels. HbA2 levels were determined using the Variant II β-Thalassemia Short Program Recorder kit. The non-random association of these SNPs was tested using HaploView software. Protein interaction was assessed using 3D structure modelling for OR51B6 (rs5006884), comparative energy minimisation, and root-mean-square deviation (RMSD) prediction.ResultsElevated HbA2 levels were associated with SNPs in HBBP1, OR51B6, and TCT haplotype from HBG2 promoter region. The bioinformatics modelling and prediction revealed that the exonic rs5006884 had RMSD value deviations and significantly varied binding energy minimisation. α-globin variations were found in 57.92% of individuals but were not associated with elevated HbA2.ConclusionsThe haemoglobin switching modulators rs2071348, rs7482144, and rs5006884 are involved in regulation of HbA2 level with rs5006884 influencing the tetramer formation. Screening for haemoglobinopathies should take these SNPs into consideration, specifically in borderline HbA2 cases. Assiduous analysis of rs5006884 as HbA2 modulator for amelioration of disease severity is recommended.

Mining of a major QTL and novel genes conferring resistance to SC3 and SC7 strains in soybean

AbstractSoybean mosaic virus (SMV) is a serious disease in soybean production, and the cultivation of resistant variety is the irreplaceable strategy to decrease the virus damage. However, the progress of SMV molecular breeding is limited partly due to the diverse types of SMV strains, solely resistance to virus strain of variety and minor genetic effects of QTLs. In the present study, one major pleiotropic additive QTL, qSMV‐D1b, with phenotypic variation explained that 27.04%–54.23% was identified on chromosome 2, and the favourable allele was from the resistant parent “Qihuang30”. Meanwhile, the allele analysis of the flanking markers showed that the favourable genotypes presented high resistance to SC3 and SC7 strains with lower disease index, while the unfavourable genotypes presented high sensitivity with higher disease index. Furthermore, six candidate genes, including four novel resistance genes, Glyma.02G121000, Glyma.02G123000, Glyma.02G123200 and Glyma.02G124700 with different expression levels between resistant and sensitive parents were discovered through transcriptome sequencing and confirmed by quantitative real‐time PCR. The resistance genes and the tightly linked molecular markers can be used for SMV breeding in soybean.

Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat.

Based on the large-scale integration of meta-QTL and Genome-WideAssociation Study, 76 high-confidence MQTL regions and 237 candidate genes that affected wheat yield and yield-related traits were discovered. Improving yield and yield-related traits are key goals in wheat breeding program. The integration of accumulated wheat genetic resources provides an opportunity to uncover important genomic regions and candidate genes that affect wheat yield. Here, a comprehensive meta-QTL analysis was conducted on 2230 QTL of yield-related traits obtained from 119 QTL studies. These QTL were refined into 145 meta-QTL (MQTL), and 89 MQTL were verified by GWAS with different natural populations. The average confidence interval (CI) of these MQTL was 2.92 times less than that of the initial QTL. Furthermore, 76 core MQTL regions with a physical distance less than 25Mb were detected. Based on the homology analysis and expression patterns, 237 candidate genes in the MQTL involved in photoperiod response, grain development, multiple plant growth regulator pathways, carbon and nitrogen metabolism and spike and flower organ development were determined. A novel candidate gene TaKAO-4A was confirmed to be significantly associated with grain size, and a CAPS marker was developed based on its dominant haplotype. In summary, this study clarified a method based on the integration of meta-QTL, GWAS and homology comparison to reveal the genomic regions and candidate genes that affect important yield-related traits in wheat. This work will help to lay a foundation for the identification, transfer and aggregation of these important QTL or candidate genes in wheat high-yield breeding.

WheatQTLdb: a QTL database for wheat.

During the last three decades, QTL analysis in wheat has been conducted for a variety of individual traits, so that thousands of QTL along with the linked markers, their genetic positions and contribution to phenotypic variation (PV) for concerned traits are now known. However, no exhaustive database for wheat QTL is currently available at a single platform. Therefore, the present database was prepared which is an exhaustive information resource for wheat QTL data from the published literature till May, 2020. QTL data from both interval mapping and genome-wide association studies (GWAS) have been included for the following classes of traits: (i) morphological traits, (ii) N and P use efficiency, (iii) traits for biofortification (Fe, K, Se, and Zn contents), (iv) tolerance to abiotic stresses including drought, water logging, heat stress, pre-harvest sprouting and salinity, (v) resistance to biotic stresses including those due to bacterial, fungal, nematode and insects, (vi) quality traits, and (vii) a variety of physiological traits, (viii) developmental traits, and (ix) yield and its related traits. For the preparation of the database, literature was searched for data on QTL/marker-trait associations (MTAs), curated and then assembled in the form of WheatQTLdb. The available information on metaQTL, epistatic QTL and candidate genes, wherever available, is also included in the database. Information on QTL in this WheatQTLdb includes QTL names, traits, associated markers, parental genotypes, crosses/mapping populations, association mapping panels and other useful information. To our knowledge, WheatQTLdb prepared by us is the largest collection of QTL (11,552), epistatic QTL (107) and metaQTL (330) data for hexaploid wheat to be used by geneticists and plant breeders for further studies involving fine mapping, cloning, and marker-assisted selection (MAS) during wheat breeding.

A large-scale genome-wide association analysis reveals QTL and candidate genes for intramuscular fat content in Duroc pigs.

This study aimed at identifying genomic regions and genes associated with intramuscular fat content (IMF) in Duroc pigs using a weighted single-step GWAS. Data from 3912 pigs, of which 3770 animals were genotyped with GeneSeek Porcine 50K Bead chip, were used for the association analysis. We identified 19 genomic regions that each explained >1% of the additive genetic variance associated with IMF. Notably, a consistent QTL on SSC7 (117.42-117.92Mb) was confirmed, explaining 3.70% of the additive genetic variance, and two genes, BDKRB2 and ATG2B, were highlighted as promising candidates for IMF. Two QTL (SSC7, 94.19-94.64Mb; SSC14, 123.25-123.75Mb), which harbored MED6 and MAP3K9 genes and TCF7L2 gene respectively, were newly identified as associated with IMF. In conclusion, we identified a consistent QTL and additional genomic regions and genes that contributed to the genetic variance of IMF using a large-scale sample size of genotyped pigs and genealogical information.