Confidence Intervals Of Quantitative Trait Loci Research Articles

Meta-QTL s and haplotypes for efficient zinc biofortification of rice.

Biofortification of rice with improved grain zinc (Zn)content is the most sustainable and cost-effective approach to address Zn malnutrition in Asia. Genomics-assisted breeding using precise and consistent Zn quantitative trait loci (QTLs), genes, and haplotypes can fast-track the development of Zn biofortified rice varieties. We conducted the meta-analysis of 155 Zn QTLs reported from 26 different studies. Results revealed 57 meta-QTLs with a significant reduction of 63.2% and 80% in the number and confidence interval of the Zn QTLs, respectively. Meta-quantitative trait loci (MQTLs) regions were found to be enriched with diverse metal homeostasis genes; at least 11 MQTLs were colocated with 20 known major genes involved in the production of root exudates, metal uptake, transport, partitioning, and loading into grains in rice. These genes were differentially expressed in vegetative and reproductive tissues, and a complex web of interactions were observed among them. We identified superior haplotypes and their combinations for nine candidate genes (CGs), and the frequency and allelic effects of superior haplotypes varied in different subgroups. The precise MQTLs with high phenotypic variance, CGs, and superior haplotypes identified in our study are useful for an efficient Zn biofortification of rice and to ensure Zn as an essential component of all the future rice varieties through mainstreaming of Zn breeding.

Identification of candidate genes regulating seed oil content by QTL mapping and transcriptome sequencing in Brassica napus.

Increasing oil production is a major goal in rapeseed (Brassica napus) molecular breeding programs. Identifying seed oil content (SOC)-related candidate genes is an important step towards achieving this goal. We performed quantitative trait locus (QTL) mapping of SOC in B. napus using a high-density SNP genetic map constructed from recombinant inbred lines and the Illumina InfiniumTM 60K SNP array. A total of 26 QTLs were detected in three years on A01, A03, A05, A06, A09, C01, C03 and C05, which accounted for 3.69%~18.47% of the phenotypic variation in SOC. Of these, 13 QTLs are reported here for the first time. 1713 candidate genes in the 26 QTLs confidence interval were obtained. We then identified differentially expressed genes (DEGs) between the high- and low-SOC accessions, to narrow down our focus to 21 candidate genes (Y1-Y21) related to SOC, and we will focus on 11 (Y1-Y11) candidate genes that contribute to the formation of high-SOC. In addition to providing insight into the genetic basis of SOC in B. napus, the loci identified and candidate genes in this study can be used in molecular breeding strategies to increase SOC in this important seed crop.

Genetic Architecture of Maize Stalk Diameter and Rind Penetrometer Resistance in a Recombinant Inbred Line Population.

Stalk lodging presents a major constraint on maize (Zea mays L.) quantity and quality and hampers mechanized grain harvesting. Stalk diameter (SD) and rind penetrometer resistance (RPR) are crucial indicators of stalk lodging. To dissect the genetic architecture of these indicators, we constructed a recombinant inbred line (RIL) population derived from a cross between maize inbred lines LDC-1 and YS501 to identify quantitative trait loci (QTLs) controlling SD and RPR. Corresponding phenotypes of basal second, third, and fourth internodes in four environments were determined. By integrating QTL mapping results based on individual environments and best linear unbiased prediction (BLUP) values, we identified 12, 12, and 13 QTLs associated with SD and 17, 14, and 17 associated with RPR. Each QTL accounted for 3.83–21.72% of phenotypic variation. For SD-related QTLs, 30 of 37 were enriched in 12 QTL clusters; similarly, RPR-related QTLs had 38 of 48 enriched in 12 QTL clusters. The stable QTL qSD9-2 for SD on chromosome 9 was validated and delimited within a physical region of 9.97 Mb. Confidence intervals of RPR-related QTLs contained 169 genes involved in lignin and polysaccharide biosynthesis, with 12 of these less than 500 kb from the peak of the corresponding QTL. Our results deepen our understanding of the genetic mechanism of maize stalk strength and provide a basis for breeding lodging resistance.

Genetic analysis of the early bud flush trait of tea plants (Camellia sinensis) in the cultivar 'Emei Wenchun' and its open-pollinated offspring.

The timing of bud flush (TBF) in the spring is one of the most important agronomic traits of tea plants (Camellia sinensis). In this study, we designed an open-pollination breeding program using ‘Emei Wenchun’ (EW, a clonal tea cultivar with extra-early TBF) as a female parent. A half-sib population (n = 388) was selected for genotyping using specific-locus amplified fragment sequencing. The results enabled the identification of paternity for 294 (75.8%) of the offspring, including 11 (2.8%) from EW selfing and 217 (55.9%) assigned to a common father, ‘Chuanmu 217’ (CM). The putative EW × CM full-sib population was used to construct a linkage map. The map has 4244 markers distributed in 15 linkage groups, with an average marker distance of 0.34 cM. A high degree of collinearity between the linkage map and physical map was observed. Sprouting index, a trait closely related to TBF, was recorded for the offspring population in 2020 and 2021. The trait had moderate variation, with coefficients of variation of 18.5 and 17.6% in 2020 and 2021, respectively. Quantitative trait locus (QTL) mapping that was performed using the linkage map identified two major QTLs and three minor QTLs related to the sprouting index. These QTLs are distributed on Chr3, Chr4, Chr5, Chr9, and Chr14 of the reference genome. A total of 1960 predicted genes were found within the confidence intervals of QTLs, and 22 key candidate genes that underlie these QTLs were preliminarily screened. These results are important for breeding and understanding the genetic base of the TBF trait of tea plants.

Identification of genes for drought resistance and prediction of gene candidates in soybean seedlings based on linkage and association mapping

Drought is one of the primary abiotic stress factors affecting the yield, growth, and development of soybeans. In extreme cases, drought can reduce yield by more than 50%. The seedling stage is an important determinant of soybean growth: the number and vigor of seedlings will affect growth and yield at harvest. Therefore, it is important to study the drought resistance of soybean seedlings. In this study, a recombinant inbred line (RIL) population comprising 234 F6:10 lines (derived from Zhonghuang 35 × Jindou 21) and a panel of 259 soybean accessions was subjected to drought conditions to identify the effects on phenotypic traits under these conditions. Using a genetic map constructed by single nucleotide polymorphism (SNPs) markers, 18 quantitative trait loci (QTL) on 7 soybean chromosomes were identified in two environments. This included 9 QTL clusters identified in the RIL population. Fifty-three QTL were identified in 19 soybean chromosomes by genome-wide association analysis (GWAS) in the panel of accessions, including 69 significant SNPs (−log10 (P) ≥ 3.97). A combination of the two populations revealed that two SNPs (−log10 (P) ≥ 3.0) fell within two of the QTL (qPH7-4 and qPH7-6) confidence intervals. We not only re-located several previously reported drought-resistance genes in soybean and other crops but also identified several non-synonymous stress-related mutation site differences between the two parents, involving Glyma.07g093000, Glyma.07g093200, Glyma.07g094100 and Glyma.07g094200. One previously unreported new gene related to drought stress, Glyma.07g094200, was found by regional association analysis. The significant SNP CHR7-17619 (G/T) was within an exon of the Glyma.07g094200 gene. In the RIL population, the DSP value of the “T” allele of CHR7-17619 was significantly (P < 0.05) larger than the “G” allele in different environments. The results of our study lay the groundwork for cloning and molecular marker-assisted selection of drought-resistance genes in soybeans at the seedling stage.

Genetic mapping of novel modifiers for ApcMin induced intestinal polyps\u2019 development using the genetic architecture power of the collaborative cross mice

BackgroundFamilial adenomatous polyposis is an inherited genetic disease, characterized by colorectal polyps. It is caused by inactivating mutations in the Adenomatous polyposis coli (Apc) gene. Mice carrying a nonsense mutation in the Apc gene at R850, which is designated ApcMin/+ (Multiple intestinal neoplasia), develop intestinal adenomas. Several genetic modifier loci of Min (Mom) were previously mapped, but so far, most of the underlying genes have not been identified. To identify novel modifier loci associated with ApcMin/+, we performed quantitative trait loci (QTL) analysis for polyp development using 49 F1 crosses between different Collaborative Cross (CC) lines and C57BL/6 J-ApcMin/+mice. The CC population is a genetic reference panel of recombinant inbred lines, each line independently descended from eight genetically diverse founder strains. C57BL/6 J-ApcMin/+ males were mated with females from 49 CC lines. F1 offspring were terminated at 23 weeks and polyp counts from three sub-regions (SB1–3) of small intestinal and colon were recorded.ResultsThe number of polyps in all these sub-regions and colon varied significantly between the different CC lines. At 95% genome-wide significance, we mapped nine novel QTL for variation in polyp number, with distinct QTL associated with each intestinal sub-region. QTL confidence intervals varied in width between 2.63–17.79 Mb. We extracted all genes in the mapped QTL at 90 and 95% CI levels using the BioInfoMiner online platform to extract, significantly enriched pathways and key linker genes, that act as regulatory and orchestrators of the phenotypic landscape associated with the ApcMin/+ mutation.ConclusionsGenomic structure of the CC lines has allowed us to identify novel modifiers and confirmed some of the previously mapped modifiers. Key genes involved mainly in metabolic and immunological processes were identified. Future steps in this analysis will be to identify regulatory elements – and possible epistatic effects – located in the mapped QTL.

Multi-year analyses on three populations reveal the first stable QTLs for tolerance to rain-induced fruit cracking in sweet cherry (Prunus avium L.)

Rain-induced fruit cracking is a major problem in sweet cherry cultivation. Basic research has been conducted to disentangle the physiological and mechanistic bases of this complex phenomenon, whereas genetic studies have lagged behind. The objective of this work was to disentangle the genetic determinism of rain-induced fruit cracking. We hypothesized that a large genetic variation would be revealed, by visual field observations conducted on mapping populations derived from well-contrasted cultivars for cracking tolerance. Three populations were evaluated over 7–8 years by estimating the proportion of cracked fruits for each genotype at maturity, at three different areas of the sweet cherry fruit: pistillar end, stem end, and fruit side. An original approach was adopted to integrate, within simple linear models, covariates potentially related to cracking, such as rainfall accumulation before harvest, fruit weight, and firmness. We found the first stable quantitative trait loci (QTLs) for cherry fruit cracking, explaining percentages of phenotypic variance above 20%, for each of these three types of cracking tolerance, in different linkage groups, confirming the high complexity of this trait. For these and other QTLs, further analyses suggested the existence of at least two-linked QTLs in each linkage group, some of which showed confidence intervals close to 5 cM. These promising results open the possibility of developing marker-assisted selection strategies to select cracking-tolerant sweet cherry cultivars. Further studies are needed to confirm the stability of the reported QTLs over different genetic backgrounds and environments and to narrow down the QTL confidence intervals, allowing the exploration of underlying candidate genes.

Genetic mapping identifies a rice naringenin O-glucosyltransferase that influences insect resistance.

Naringenin, the biochemical precursor for predominant flavonoids in grasses, provides protection against UV damage, pathogen infection and insect feeding. To identify previously unknown loci influencing naringenin accumulation in rice (Oryza sativa), recombinant inbred lines derived from the Nipponbare and IR64 cultivars were used to map a quantitative trait locus (QTL) for naringenin abundance to a region of 50 genes on rice chromosome 7. Examination of candidate genes in the QTL confidence interval identified four predicted uridine diphosphate-dependent glucosyltransferases (Os07g31960, Os07g32010, Os07g32020 and Os07g32060). In vitro assays demonstrated that one of these genes, Os07g32020 (UGT707A3), encodes a glucosyltransferase that converts naringenin and uridine diphosphate-glucose to naringenin-7-O-β-d-glucoside. The function of Os07g32020 was verified with CRISPR/Cas9 mutant lines, which accumulated more naringenin and less naringenin-7-O-β-d-glucoside and apigenin-7-O-β-d-glucoside than wild-type Nipponbare. Expression of Os12g13800, which encodes a naringenin 7-O-methyltransferase that produces sakuranetin, was elevated in the mutant lines after treatment with methyl jasmonate and insect pests, Spodoptera litura (cotton leafworm), Oxya hyla intricata (rice grasshopper) and Nilaparvata lugens (brown planthopper), leading to a higher accumulation of sakuranetin. Feeding damage from O. hyla intricata and N. lugens was reduced on the Os07g32020 mutant lines relative to Nipponbare. Modification of the Os07g32020 gene could be used to increase the production of naringenin and sakuranetin rice flavonoids in a more targeted manner. These findings may open up new opportunities for selective breeding of this important rice metabolic trait.

A combination of linkage mapping and GWAS brings new elements on the genetic basis of yield-related traits in maize across multiple environments.

Using GWAS and QTL mapping identified 100 QTL and 138 SNPs, which control yield-related traits in maize. The candidate gene GRMZM2G098557 was further validated to regulate ear row number by using a segregation population. Understanding the genetic basis of yield-related traits contributes to the improvement of grain yield in maize. This study used an inter-mated B73 × Mo17 (IBM) Syn10 doubled-haploid (DH) population and an association panel to identify the genetic loci responsible for nine yield-related traits in maize. Using quantitative trait loci (QTL) mapping, 100 QTL influencing these traits were detected across different environments in the IBM Syn10 DH population, with 25 co-detected in multiple environments. Using a genome-wide association study (GWAS), 138 single-nucleotide polymorphisms (SNPs) were identified as correlated with these traits (P < 2.04E-06) in the association panel. Twenty-one pleiotropic QTL/SNPs were identified to control different traits in both populations. A combination of QTL mapping and GWAS uncovered eight significant SNPs (PZE-101097575, PZE-103169263, ZM011204-0763, PZE-104044017, PZE-104123110, SYN8062, PZE-108060911, and PZE-102043341) that were co-located within seven QTL confidence intervals. According to the eight co-localized SNPs by the two populations, 52 candidate genes were identified, among which the ear row number (ERN)-associated SNP SYN8062 was closely linked to SBP-transcription factor 7 (GRMZM2G098557). Several SBP-transcription factors were previously demonstrated to modulate maize ERN. We then validated the phenotypic effects of SYN8062 in the IBM Syn10 DH population, indicating that the ERN of the lines with the A-allele in SYN8062 was significantly (P < 0.05) larger than that of the lines with the G-allele in SYN8062 in each environment. These findings provide valuable information for understanding the genetic mechanisms of maize grain yield formation and for improving molecular marker-assisted selection for the high-yield breeding of maize.

Distinguishing pleiotropy from linked QTL between milk production traits and mastitis resistance in Nordic Holstein cattle

BackgroundProduction and health traits are central in cattle breeding. Advances in next-generation sequencing technologies and genotype imputation have increased the resolution of gene mapping based on genome-wide association studies (GWAS). Thus, numerous candidate genes that affect milk yield, milk composition, and mastitis resistance in dairy cattle are reported in the literature. Effect-bearing variants often affect multiple traits. Because the detection of overlapping quantitative trait loci (QTL) regions from single-trait GWAS is too inaccurate and subjective, multi-trait analysis is a better approach to detect pleiotropic effects of variants in candidate genes. However, large sample sizes are required to achieve sufficient power. Multi-trait meta-analysis is one approach to deal with this problem. Thus, we performed two multi-trait meta-analyses, one for three milk production traits (milk yield, protein yield and fat yield), and one for milk yield and mastitis resistance.ResultsFor highly correlated traits, the power to detect pleiotropy was increased by multi-trait meta-analysis compared with the subjective assessment of overlapping of single-trait QTL confidence intervals. Pleiotropic effects of lead single nucleotide polymorphisms (SNPs) that were detected from the multi-trait meta-analysis were confirmed by bivariate association analysis. The previously reported pleiotropic effects of variants within the DGAT1 and MGST1 genes on three milk production traits, and pleiotropic effects of variants in GHR on milk yield and fat yield were confirmed. Furthermore, our results suggested that variants in KCTD16, KCNK18 and ENSBTAG00000023629 had pleiotropic effects on milk production traits. For milk yield and mastitis resistance, we identified possible pleiotropic effects of variants in two genes, GC and DGAT1.ConclusionsMulti-trait meta-analysis improves our ability to detect pleiotropic interactions between milk production traits and identifies variants with pleiotropic effects on milk production traits and mastitis resistance. In particular, this should contribute to better understand the biological mechanisms that underlie the unfavorable genetic correlation between milk yield and mastitis.

Genetic Variation for Protein Content and Yield-Related Traits in a Durum Population Derived From an Inter-Specific Cross Between Hexaploid and Tetraploid Wheat Cultivars.

Wheat grain protein content (GPC) and yield components are complex quantitative traits influenced by a multi-factorial system consisting of both genetic and environmental factors. Although seed storage proteins represent less than 15% of mature kernels, they are crucial in determining end-use properties of wheat, as well as the nutritional value of derived products. Yield and GPC are negatively correlated, and this hampers breeding programs of commercially valuable wheat varieties. The goal of this work was the evaluation of genetic variability for quantity and composition of seed storage proteins, together with yield components [grain yield per spike (GYS) and thousand-kernel weight (TKW)] in a durum wheat population obtained by an inter-specific cross between a common wheat accession and the durum cv. Saragolla. Quantitative trait loci (QTL) analysis was conducted and closely associated markers identified on a genetic map composed of 4,366 SNP markers previously obtained in the same durum population genotyped with the 90K iSelect SNP assay. A total of 22 QTL were detected for traits related to durum wheat quality. Six genomic regions responsible for GPC control were mapped on chromosomes 2B, 3A, 4A, 4B, 5B, and 7B, with major QTL on chromosomes 2B, 4A, and 5B. Nine loci were detected for GYS: two on chromosome 5B and 7A and one on chromosomes 2A, 2B, 4A, 4B, 7B, with the strongest QTL on 2B. Eight QTL were identified for TKW, three of which located on chromosome 3A, two on 1B and one on 4B, 5A, and 5B. Only small overlapping was found among QTL for GYS, TKW, and GPC, and increasing alleles coming from both parents on different chromosomes. Good candidate genes were identified in the QTL confidence intervals for GYS and TKW.

Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping.

SummaryKernel size‐related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10−6) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10−3) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable‐effect SNPs and the co‐localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co‐localized SNPs, of which zma‐miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1,CUC2 and NAC6 in vitro. Overexpression of zma‐miR164e resulted in the down‐regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker‐assisted selection (MAS) for high‐yield breeding in maize.

Quantitative trait locus mapping for plant height and branch number in an upland cotton recombinant inbred line with an SNP-based high-density genetic map

Cotton is one of the most important cash crops around the world, providing natural fiber for the textile industry. Agronomic traits play an important role in the mechanized harvesting of cotton. Plant height (PH) and branch number (BN) are two important traits that could affect plant architecture and ultimately, economic yield of cotton. The quantitative trait locus (QTL) for PH and BN across seven environments was identified with a high-density single nucleotide polymorphism map constructed using recombinant inbred lines from upland cotton 0–153 and sGK9708. A total of 68 QTLs for PH (nine stable) and 64 QTLs for BN (eight stable) were identified. Among these stable QTLs, three (two for PH and one for BN) have been identified in previous studies. Four hundred genes for PH and 624 genes for BN were located on the confidence intervals of these stable QTLs. Among them, 134 for PH and 224 for BN were expressed in at least one tissue of root, stem and leaf. Based on the annotation information, expression pattern and the function validated on the other species, ten genes (six for PH and four for BN) could be considered as potential candidate genes. These results could contribute to understanding the mechanism of PH and branch formation, and to improving the method of cotton breeding for molecular marker-assisted selection.

Genetic variation of dynamic fiber elongation and developmental quantitative trait locus mapping of fiber length in upland cotton (Gossypium hirsutum L.)

BackgroundIn upland cotton (Gossypium hirsutum L.), genotypes with the same mature fiber length (FL) might possess different genes and exhibit differential expression of genes related to fiber elongation at different fiber developmental stages. However, there is a lack of information on the genetic variation influencing fiber length and its quantitative trait loci (QTLs) during the fiber elongation stage. In this study, a subset of upland cotton accessions was selected based on a previous GWAS conducted in China and grown in multiple environments to determine the dynamic fiber length at 10, 15, 20, and 25 days post-anthesis (DPA) and maturity. The germplasm lines were genotyped with the Cotton 63 K Illumina single-nucleotide polymorphism (SNP) array for GWAS.ResultsA total of 25, 38, 57, 89 and 88 SNPs showed significant correlations with fiber length at 10, 15, 20 and 25 DPA and maturity, respectively. In addition, 60 more promising SNPs were detected in at least two tests and two FL developmental time points, and 20 SNPs were located within the confidence intervals of QTLs identified in previous studies. The fastest fiber-length growth rates were obtained at 10 to 15 DPA in 69 upland cotton lines and at 15 to 20 DPA in 14 upland cotton accessions, and 10 SNPs showed significant correlations with the fiber-length growth rate. A combined transcriptome and qRT-PCR analysis revealed that two genes (D10G1008 and D13G2037) showed differential expression between two long-fiber genotypes and two short-fiber genotypes.ConclusionsThis study provides important new insights into the genetic basis of the time-dependent fiber-length trait and reveals candidate SNPs and genes for improving fiber length in upland cotton.

Putative regulatory candidate genes for QTL linked to fruit traits in oil palm (Elaeis guineensis Jacq.)

Palm oil is among the most important vegetable oils, contributing to a quarter of the world’s oils and fats market. The oil palm (Elaeis guineensis Jacq.) fruitlets, which are the source of palm oil, vary from 8 to 20 g in weight. Palm oil content in the fruitlets is approximately 45–50% by weight and an increase in the percentage of mesocarp-to-fruit is likely to have a positive effect on oil yield. In this study, we report a quantitative trait loci (QTL) associated with two yield related components, namely fruit and mesocarp content in a commercial breeding population (Deli dura × Yangambi pisifera). The QTL confidence interval of about 12 cM (~ 6.7 Mbp) was fine-mapped with 31 markers (17 SNPs and 14 SSRs) consisting of 20 nuclear markers derived from the maternal parent, six paternal and five co-segregating markers. Interestingly, inheritance of the paternal alleles leads to a larger difference in both fruit and mesocarp weight, when comparing genotypes in the progeny palms. Candidate genes and transcription factors were mined from the QTL region by positioning markers on the oil palm EG5 genome build. Putative genes and transcription factors involved in various biological processes including flower organ development, flowering, photosynthesis, microtubule formation, nitrogen and lipid metabolism were identified within this QTL interval on pseudo-chromosome 3. This genome-based approach allowed us to identify a number of potential candidate gene markers associated with oil palm fruit and mesocarp weight which can be further evaluated for potential use in marker-assisted breeding.

Mapping of quantitative trait loci for microspore embryogenesis-related traits in the oilseed rape doubled haploid population DH4069 × Express 617

Oilseed rape (Brassica napus L.) is among dicotyledonous plants, a model species for microspore embryogenesis. Tremendous differences exist among oilseed rape genotypes in their embryogenic response and direct embryo to plant conversion. Despite some attempts to identify relevant genes, the genetic basis of these traits remains largely unknown. The objective of this work was to develop and to provide to the scientific community a doubled haploid (DH) population derived from a cross of the reported highly embryogenic genotype DH4079 and the low embryogenic inbred line Express 617. A population of 198 DH-lines was generated and genotyped with the Brassica 60 K Illumina Infinium™ SNP array. The parental and the F1 genotypes as well as between 81 and 107 DH-lines were characterized for their number of microspores, number of microspore-derived embryos, embryo survival rate, direct embryo to shoot conversion, and related traits. The results obtained for the F1 genotype were mostly in between the two parents. SNP markers in the DH population showed to 49% distorted segregation and of those 63% were in favor of DH4079. Significant genotypic differences were found for all traits and heritabilities ranged from 66 to 88%. Together, 13 quantitative trait loci (QTL) for the different traits were identified on linkage groups A01, A02, A05, A10, C04, and C06, and candidate genes were identified within their QTL confidence intervals.

High-Density Genetic Map Construction and Stem Total Polysaccharide Content-Related QTL Exploration for Chinese Endemic Dendrobium (Orchidaceae).

Plants of the Dendrobium genus are orchids with not only ornamental value but also high medicinal value. To understand the genetic basis of variations in active ingredients of the stem total polysaccharide contents (STPCs) among different Dendrobium species, it is of paramount importance to understand the mechanism of STPC formation and identify genes affecting its process at the whole genome level. Here, we report the first high-density single-nucleotide polymorphism (SNP) integrated genetic map with a good genome coverage of Dendrobium. The specific-locus amplified fragment sequencing (SLAF-seq) technology led to identification of 7,013,400 SNPs from 1,503,626 high-quality SLAF markers from two parents (Dendrobium moniliforme ♀ × Dendrobium officinale ♂) and their interspecific F1 hybrid population. The final genetic map contained 8, 573 SLAF markers, covering 19 linkage groups (LGs). This genetic map spanned a length of 2,737.49 cM, where the average distance between markers is 0.32 cM. In total, 5 quantitative trait loci (QTL) related to STPC were identified, 3 of which have candidate genes within the confidence intervals of these stable QTLs based on the D. officinale genome sequence. This study will build a foundation up for the mapping of other medicinal-related traits and provide an important reference for the molecular breeding of these Chinese herb.

Identification of drought responsive QTLs during vegetative growth stage of rice using a saturated GBS-based SNP linkage map

Drought is a major abiotic constraint for rice production worldwide. The quantitative trait loci (QTLs) for drought tolerance traits identified in earlier studies have large confidence intervals due to low density linkage maps. Further, these studies largely focused on the above ground traits. Therefore, this study aims to identify QTLs for root and shoot traits at the vegetative growth stage using a genotyping by sequencing (GBS) based saturated SNP linkage map. A recombinant inbred line (RIL) population from a cross between Cocodrie and N-22 was evaluated for eight morphological traits under drought stress. Drought was imposed to plants grown in 75 cm long plastic pots at the vegetative growth stage. Using a saturated SNP linkage map, 14 additive QTLs were identified for root length, shoot length, fresh root mass, fresh shoot mass, number of tillers, dry root mass, dry shoot mass, and root-shoot ratio. Majority of the drought responsive QTLs were located on chromosome 1. The expression of QTLs varied under stress and irrigated condition. Shoot length QTLs qSL1.38 and qSL1.11 were congruent to dry shoot mass QTL qDSM1.38 and dry root mass QTL qDRM1.11, respectively. Analysis of genes present within QTL confidence intervals revealed many potential candidate genes such as laccase, Calvin cycle protein, serine threonine protein kinase, heat shock protein, and WRKY protein. Another important gene, Brevis radix, present in the root length QTL region, was known to modulate root growth through cell proliferation and elongation. The candidate genes and the QTL information will be helpful for marker-assisted pyramiding to improve drought tolerance in rice.

Genetic architecture of aerial and root traits in field-grown grafted grapevines is largely independent.

QTLs were identified for traits assessed on field-grown grafted grapevines. Root number and section had the largest phenotypic variance explained. Genetic control of root and aerial traits was independent. Breeding new rootstocks for perennial crops remains challenging, mainly because of the number of desirable traits which have to be combined, these traits include good rooting ability and root development. Consequently, the present study analyzes the genetic architecture of root traits in grapevine. A segregating progeny of 138 F1 genotypes issued from an inter-specific cross between Vitis vinifera cv. Cabernet-Sauvignon×V. riparia cv. Gloire de Montpellier, used as rootstock, was phenotyped in grafted plants grown for 2years in the field. Seven traits, related to aerial and root development, were quantified. Heritability ranged between 0.44 for aerial biomass to 0.7 for root number. Total root number was related to the number of fine roots, while root biomass was related to the number of coarse roots. Significant quantitative trait loci (QTLs) were identified for all the traits studied with some of them explaining approximately 20% of phenotypic variance. Only a single QTL co-localized for root and aerial biomass. Identified QTLs for aerial-to-root biomass ratio suggest that aerial and root traits are controlled independently. Genes known to be involved in auxin signaling pathways and phosphorus nutrition, whose orthologues were previously shown to regulate root development in Arabidopsis, were located in the confidence intervals of several QTLs. This study opens new perspectives for breeding rootstocks with improved root development capacities.

Construction of a High-Density Genetic Map from RNA-Seq Data for an Arabidopsis Bay-0 × Shahdara RIL Population.

High-density genetic maps are essential for high resolution mapping of quantitative traits. Here, we present a new genetic map for an Arabidopsis Bayreuth × Shahdara recombinant inbred line (RIL) population, built on RNA-seq data. RNA-seq analysis on 160 RILs of this population identified 30,049 single-nucleotide polymorphisms (SNPs) covering the whole genome. Based on a 100-kbp window SNP binning method, 1059 bin-markers were identified, physically anchored on the genome. The total length of the RNA-seq genetic map spans 471.70 centimorgans (cM) with an average marker distance of 0.45 cM and a maximum marker distance of 4.81 cM. This high resolution genotyping revealed new recombination breakpoints in the population. To highlight the advantages of such high-density map, we compared it to two publicly available genetic maps for the same population, comprising 69 PCR-based markers and 497 gene expression markers derived from microarray data, respectively. In this study, we show that SNP markers can effectively be derived from RNA-seq data. The new RNA-seq map closes many existing gaps in marker coverage, saturating the previously available genetic maps. Quantitative trait locus (QTL) analysis for published phenotypes using the available genetic maps showed increased QTL mapping resolution and reduced QTL confidence interval using the RNA-seq map. The new high-density map is a valuable resource that facilitates the identification of candidate genes and map-based cloning approaches.