High-Density Genetic Linkage Map Construction and QTL Mapping of Grain Shape and Size in the Wheat Population Yanda1817 × Beinong6

High-density genetic linkage maps are necessary for precisely mapping quantitative trait loci (QTLs) controlling grain shape and size in wheat. By applying the Infinium iSelect 9K SNP assay, we have constructed a high-density genetic linkage map with 269 F ₈ recombinant inbred lines (RILs) developed between a Chinese cornerstone wheat breeding parental line Yanda1817 and a high-yielding line Beinong6. The map contains 2431 SNPs and 128 SSR & EST-SSR markers in a total coverage of 3213.2 cM with an average interval of 1.26 cM per marker. Eighty-eight QTLs for thousand-grain weight (TGW), grain length (GL), grain width (GW) and grain thickness (GT) were detected in nine ecological environments (Beijing, Shijiazhuang and Kaifeng) during five years between 2010–2014 by inclusive composite interval mapping (ICIM) (LOD≥2.5). Among which, 17 QTLs for TGW were mapped on chromosomes 1A, 1B, 2A, 2B, 3A, 3B, 3D, 4A, 4D, 5A, 5B and 6B with phenotypic variations ranging from 2.62% to 12.08%. Four stable QTLs for TGW could be detected in five and seven environments, respectively. Thirty-two QTLs for GL were mapped on chromosomes 1B, 1D, 2A, 2B, 2D, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6B, 7A and 7B, with phenotypic variations ranging from 2.62% to 44.39%. QGl.cau-2A.2 can be detected in all the environments with the largest phenotypic variations, indicating that it is a major and stable QTL. For GW, 12 QTLs were identified with phenotypic variations range from 3.69% to 12.30%. We found 27 QTLs for GT with phenotypic variations ranged from 2.55% to 36.42%. In particular, QTL QGt.cau-5A.1 with phenotypic variations of 6.82–23.59% was detected in all the nine environments. Moreover, pleiotropic effects were detected for several QTL loci responsible for grain shape and size that could serve as target regions for fine mapping and marker assisted selection in wheat breeding programs.     

Genome-Wide Association Studies Identify the Loci for 5 Exterior Traits in a Large White × Minzhu Pig Population

As one of the main breeding selection criteria, external appearance has special economic importance in the hog industry. In this study, an Illumina Porcine SNP60 BeadChip was used to conduct a genome-wide association study (GWAS) in 605 pigs of the F₂ generation derived from a Large White × Minzhu intercross. Traits under study were abdominal circumference (AC), body height (BH), body length (BL), cannon bone circumference (CBC), chest depth (CD), chest width (CW), rump circumference (RC), rump width (RW), scapula width (SW), and waist width (WW). A total of 138 SNPs (the most significant being MARC0033464) on chromosome 7 were found to be associated with BH, BL, CBC, and RC (P-value  = 4.15E-6). One SNP on chromosome 1 was found to be associated with CD at genome-wide significance levels. The percentage phenotypic variance of these significant SNPs ranged from 0.1–25.48%. Moreover, a conditional analysis revealed that the significant SNPs were derived from a single quantitative trait locus (QTL) and indicated additional chromosome-wide significant association for 25 SNPs on SSC4 (BL, CBC) and 9 SNPs on SSC7 (RC). Linkage analysis revealed two complete linkage disequilibrium haplotype blocks that contained seven and four SNPs, respectively. In block 1, the most significant SNP, MARC0033464, was present. Annotations from pig reference genome suggested six genes (GRM4, HMGA1, NUDT3, RPS10, SPDEF and PACSIN1) in block 1 (495 kb), and one gene (SCUBE3) in block 3 (124 kb). Functional analysis indicated that HMGA1 and SCUBE3 genes are the potential genes controlling BH, BL, and RC in pigs, with an application in breeding programs. We screened several candidate intervals and genes based on SNP location and gene function, and predicted their function using bioinformatics analyses.     

Development and Molecular Cytogenetic Identification of a Novel Wheat–Leymus mollis Lm#7Ns (7D) Disomic Substitution Line with Stripe Rust Resistance

Leymus mollis (2n = 4x = 28, NsNsXmXm) possesses novel and important genes for resistance against multi-fungal diseases. The development of new wheat—L. mollis introgression lines is of great significance for wheat disease resistance breeding. M11003-3-1-15-8, a novel disomic substitution line of common wheat cv. 7182 –L. mollis, developed and selected from the BC₁F₅ progeny between wheat cv. 7182 and octoploid Tritileymus M47 (2n = 8x = 56, AABBDDNsNs), was characterized by morphological and cytogenetic identification, analysis of functional molecular markers, genomic in situ hybridization (GISH), sequential fluorescence in situ hybridization (FISH)—genomic in situ hybridization (GISH) and disease resistance evaluation. Cytological observations suggested that M11003-3-1-15-8 contained 42 chromosomes and formed 21 bivalents at meiotic metaphase I. The GISH investigations showed that line contained 40 wheat chromosomes and a pair of L. mollis chromosomes. EST-STS multiple loci markers and PLUG (PCR-based Landmark Unique Gene) markers confirmed that the introduced L. mollis chromosomes belonged to homoeologous group 7, it was designated as Lm#7Ns. While nulli-tetrasomic and sequential FISH-GISH analysis using the oligonucleotide Oligo-pSc119.2 and Oligo-pTa535 as probes revealed that the wheat 7D chromosomes were absent in M11003-3-1-15-8. Therefore, it was deduced that M11003-3-1-15-8 was a wheat–L. mollis Lm#7Ns (7D) disomic substitution line. Field disease resistance demonstrated that the introduced L. mollis chromosomes Lm#7Ns were responsible for the stripe rust resistance at the adult stage. Moreover, M11003-3-1-15-8 had a superior numbers of florets. The novel disomic substitution line M11003-3-1-15-8, could be exploited as an important genetic material in wheat resistance breeding programs and genetic resources.     

Molecular Cytogenetic Characterization of a Wheat - Leymus mollis 3D（3Ns） Substitution Line with Resistance to Leaf Rust

Leymus mollis （Trin.） Pilger （NsNsXmXm, 2n = 28）, a wild relative of common wheat, possesses many potentially valuable traits that could be transferred to common wheat during breeding programs. In this study, the karyotypic constitution of a wheat - L. mollis 3D（3Ns#1） disomic substitution line isolated from the F5 progeny of octoploid Tritileymus M842-16 x Triticum durum cv. D4286, which was designated as 10DM57, was determined using genomic in situ hybridization （GISH）, fluorescent in situ hybridization （FISH）, SSR markers, and EST- STS markers. Screening of mitosis and meiosis showed that 10DM57 had a chromosome karyotype of 2n = 42 =21Ⅱ. GISH indicated that 10DM57 was a line with 40 chromosomes from wheat and two of the Ns chromosomes from L. mollis, which formed a ring bivalent in pollen mother cells at metaphase I. FISH analysis showed that the chromosome 3D may be replaced by 3Ns#1 in 10DM57. DNA markers, including SSR and EST-STS primers, showed that the pair of wheat chromosome 3D in 10DM57 was substituted by the pair of chromosome 3Ns#t from L. mollis. Evaluation of the agronomic traits showed that, compared with its common wheat relative 7182, 10DM57 was resistant to leaf rust while the spike length and number of spikes per plant were improved significantly, which correlated with a higher wheat yield. The new germplasm, 10DM57, could be exploited as an intermediate material in wheat genetic and breeding programs.     

Mapping QTL associated with photoperiod sensitivity and assessing the importance of QTL×environment interaction for flowering time in maize

Background

An understanding of the genetic determinism of photoperiod response of flowering is a prerequisite for the successful exchange of germplasm across different latitudes. In order to contribute to resolve the genetic basis of photoperiod sensitivity in maize, a set of 201 recombinant inbred lines (RIL), derived from a temperate and tropical inbred line cross were evaluated in 5 field trials spread in short- and long-day environments.

Methodology/Principal Findings

Firstly, QTL analyses for flowering time and photoperiod sensitivity in maize were conducted in individual photoperiod environments separately, and then, the total genetic effect was partitioned into additive effect (A) and additive-by-environment interaction effect (AE) by using a mixed-model-based composite interval mapping (MCIM) method.

Conclusions/Significance

Seven putative QTL were found associated with DPS thermal time based on the data estimated in individual environments. Nine putative QTL were found associated with DPS thermal time across environments and six of them showed significant QTL×enviroment (QE) interactions. Three QTL for photoperiod sensitivity were identified on chromosome 4, 9 and 10, which had the similar position to QTL for DPS thermal time in the two long-day environment. The major photoperiod sensitive loci qDPS10 responded to both short and long-day photoperiod environments and had opposite effects in different photoperiod environment. The QTL qDPS3, which had the greatest additive effect exclusively in the short-day environment, were photoperiod independent and should be classified in autonomous promotion pathway.     

QTL Analysis for Grain Pentosans and Hardness Index in a Chinese 1RS.1BL × non-1RS.1BL Wheat Cross

Pentosans are quantitatively minor constituents of wheat (Triticum aestivum L.), but they influence the end-use and nutritional qualities of grain cereals. Although several studies on the physicochemical properties and genetic basis of pentosans and pentosan-associated traits have been reported, the genetic architecture and determinants of pentosans remained ambiguous. In this research, 107 QTLs for pentosans and pentosan-associated traits were detected based on a population of recombinant inbred lines (RILs) derived from a 1RS/1BL translocation line?×?non-1RS/1BL translocation line. We identified seven stable expression QTLs for pentosans and one major QTL (Q.HI.scau-7D linked to xwmc634-7D) for hardness index (HI). Q.HI.scau-7D may be the gene responsible for the bimodal HI distribution map. More than one genetic location harbored QTLs for water-soluble pentosan (WSP), and the ratio of WSP content to water-insoluble pentosans (WIP) content (RWW) varied simultaneously, meaning that these loci harbored pleiotropic genes for WSP and RWW. WSP was the main factor in pentosans affecting wheat HI. This study gives a better understanding of the molecular genetics of pentosans and pentosan-related traits, and provides a certain theoretical basis for molecular genetics and breeding for pentosans.     

Gene Network and Database for Genes of Wheat’s Resistance to Pathogenic Fungi

An overview describing a gene network that controls the formation of plant responses to diseases caused by pathogenic fungi (http://wwwmgs.bionet.nsc.ru/mgs/gnw/genenet//viewer/Plant%20fungus%20pathogen.html) is presented. The gene network represents the coordinated interactions of genes, proteins, and regulatory molecules, including integrated defense mechanisms that prevent the development of infection, localize the lesion, and minimize damage. The gene network was reconstructed on the basis of literature data, and the elements of the gene network were associated with the records of the PGR database (Pathogenesis-Related Genes, http://srs6.bionet.nsc.ru/srs6bin/cgi-bin/wgetz?-page+top+-newId), where information on plant genes resistant to pathogenic fungi is accumulated. Reconstruction of the gene network allows us to formalize, visualize, and systematize possible mechanisms for the response of plant cells to fungal infection, which may be useful for the planning of experiments and interpretation of experimental data in this field of science.     

Mapping and characterisation of QTL × E interactions for traits determining grain and stover yield in pearl millet

A mapping population of 104 F(3) lines of pearl millet, derived from a cross between two inbred lines H 77/833-2 x PRLT 2/89-33, was evaluated, as testcrosses on a common tester, for traits determining grain and stover yield in seven different field trials, distributed over 3 years and two seasons. The total genetic variation was partitioned into effects due to season (S), genotype (G), genotype x season interaction (G x S), and genotype x environment-within-season interaction [G x E(S)]. QTLs were determined for traits for their G, G x S, and G x E(S) effects, to assess the magnitude and the nature (cross over/non-crossover) of environmental interaction effects on individual QTLs. QTLs for some traits were associated with G effects only, while others were associated with the effects of both G and G x S and/or G, G x S and G x E(S) effects. The major G x S QTLs detected were for flowering time (on LG 4 and LG 6), and mapped to the same intervals as G x S QTLs for several other traits (including stover yield, harvest index, biomass yield and panicle number m(-2)). All three QTLs detected for grain yield were unaffected by G x S interaction however. All three QTLs for stover yield (mapping on LG 2, LG 4 and LG 6) and one of the three QTLs for grain yield (mapping on LG 4) were also free of QTL x E(S) interactions. The grain yield QTLs that were affected by QTL x E(S) interactions (mapping on LG 2 and LG 6), appeared to be linked to parallel QTL x E(S) interactions of the QTLs for panicle number m(-2) on (LG 2) and of QTLs for both panicle number m(-2) and harvest index (LG 6). In general, QTL x E(S) interactions were more frequently observed for component traits of grain and stover yield, than for grain or stover yield per se.     

Mapping and fine mapping of quantitative trait loci for the number of vertebrae in a White Duroc × Chinese Erhualian intercross resource population

The number of vertebrae is associated with body size and meat production in pigs. To identify quantitative trait loci (QTL) for the number of vertebrae, phenotypic values were measured in 1029 individuals from a White Duroc × Chinese Erhualian intercross F₂ population. A whole genome scan was performed with 194 microsatellite markers in the F₂ population. Four genome‐wide significant QTL and eight chromosome‐wide significant QTL for the number of vertebrae were identified on pig chromosomes (SSC) 1, 2, 6, 7, 10 and 12. The most significant QTL was detected on SSC7 with a confidence interval of 1 cM, explaining 42.32% of the phenotypic variance in the thoracic vertebral number. The significant QTL on SSC1, 2 and 7 confirmed previous reports. A panel of 276 animals representing seven Western and Chinese breeds was genotyped with 34 microsatellite markers in the SSC7 QTL region. No obvious selective sweep effect was observed in the tested breeds, indicating that intensive selection for enlarged body size in Western commercial breeds did not wipe out the genetic variability in the QTL region. The Q alleles for increased vertebral number originated from both Chinese Erhualian and White Duroc founder animals. A haplotype block of approximately 900 kb was found to be shared by all Q‐bearing chromosomes of F₁ sires except for one distinct Q chromosome. The critical region harbours the newly reported VRTN gene associated with vertebral number. Further investigations are required to confirm whether VRTN or two other positional candidate genes, PROX2 and FOS, cause the QTL effect.     

Identification and Characterization of Phosphorus Use Efficiency in a Doubled Haploid Population of Chinese Spring×Lovrin No.10

It is reported that chromosome 1R of rye (Secale cereale L.) convey phosphorus use efficient gene (s), and 1RS/1BL translocation genotype Lovrin No.10 is P use efficient. So we hypothesized whether P efficient gene(s) locate on 1RS, and the high P efficiency of Lovrin No.10 is from 1RS? To test this hypothesis, we investigated the P use efficiency (PUE) of a doubled haploid (DH) population with 61 lines derived from anther culture of F₁ hybrid between Lovrin No.10 and phosphorus uptake inefficient genotype Chinese Spring to see whether PUE differs between DH line with and without 1RS/1BL translocation. Acidic polyacrylamide-gel electrophoresis (A-PAGE) of gliadin and genomic DNA in situ hybridization (GISH) were employed to discriminate 1RS/1BL translocation DH lines from the normal 1B DH lines. Among the 61 DH lines investigated, A-PAGE analysis showed that 34 lines contained the 1RS/1BL translocation chromosome, which was characterized by the presence of a 1RS-specific Sec-1 marker bands. Further verification with GISH proved that 33 in the 34 lines contained a pair of homozygous 1RS/1BL translocation chromosomes, only one line was a 1RS/1BL monosomic line. A field experiment was carried out on P deficient soil to investigate grain yield, biomass, numbers of spikes per plant (SPP), P uptake efficiency (PUpE), and P utilization efficiency (PUtE) of the DH lines and their parents under -P (nil P applied) and +P (60 kg P/hm² applied) at maturity. Results showed soil P deficiency decreased the values of the first four traits in Lovrin No.10, but were more severe for Chinese Spring. Lovrin No.10 had higher values of all the above tested traits at both -P and +P than Chinese Spring did, but had similar PUtE with Chinese Spring. These five traits segregated, and differed greatly among DH lines under both -P and +P conditions. Although the variations among DH lines exceeded the difference between the two parents, the average values of the DH lines were between the two parents. The average of the above five traits, and P deficiency tolerance (PDT) (measured by relative grain yield of -P/+P) were not different between the DH lines with and without 1RS/1BL translocation. This indicated that there was no association between 1RS and PUE and PDT in Lovrin No.10, and 1RS may not have P efficient gene(s). Therefore, in the offspring of Lovrin No.10, it is possible to combine high PUE and PDT with good quality without the negative effect of 1RS on flour quality.     

Mapping QTLs with epistatic effects and QTL×environment interactions for plant height using a doubled haploid population in cultivated wheat

Quantitative trait loci (QTLs) for plant height in wheat (Triticum aestivum L.) were studied using a set of 168 doubled haploid (DH) lines, which were derived from the cross Huapei 3/Yumai 57. A genetic linkage map was constructed using 283 SSR and 22 EST-SSR markers. The DH population and the parents were evaluated for wheat plant height in 2005 and 2006 in Tai'an and 2006 in Suzhou. QTL analyses were performed using the software of QTLNetwork version 2.0 based on the mixed linear model. Four additive QTLs and five pairs of epistatic effects were detected, which were distributed on chromosomes 3A, 4B, 4D, 5A, 6A, 7B, and 7D. Among them, three additive QTLs and three pairs of epistatic QTLs showed QTLxenvironment interactions (QEs). Two major QTLs, QphAB and Qph4D, which accounted for 14.51 % and 20.22% of the phenotypic variation, were located similar to the reported locations of the dwarfing genes Rhtl and Rht2, respectively. The Qph3A-2 with additive effect was not reported in previous linkage mapping studies. The total QTL ef fects detected for the plant height explained 85.04% of the phenotypic variation, with additive effects 46.07%, epistatic effects 19.89%, and QEs 19.09%. The results showed that both additive effects and epistatic effects were important genetic bases of wheat plant height, which were subjected to environmental modifications, and caused dramatic changes in phenotypic effects. The information obtained in this study will be useful for manipulating the QTLs for wheat plant height by molecular marker-assisted selection (MAS).     

Mapping QTLs with epistatic effects and QTL×environment interactions for plant height using a doubled haploid population in cultivated wheat

Quantitative trait loci (QTLs) for plant height in wheat (Triticum aestivum L.) were studied using a set of 168 doubled haploid (DH) lines, which were derived from the cross Huapei 3/Yumai 57. A genetic linkage map was constructed using 283 SSR and 22 EST-SSR markers. The DH population and the parents were evaluated for wheat plant height in 2005 and 2006 in Tai’an and 2006 in Suzhou. QTL analyses were performed using the software of QTLNetwork version 2.0 based on the mixed linear model. Four additive QTLs and five pairs of epistatic effects were detected, which were distributed on chromosomes 3A, 4B, 4D, 5A, 6A, 7B, and 7D. Among them, three additive QTLs and three pairs of epistatic QTLs showed QTL×environment interactions (QEs). Two major QTLs, Qph4B and Qph4D, which accounted for 14.51% and 20.22% of the phenotypic variation, were located similar to the reported locations of the dwarfing genes Rht1 and Rht2, respectively. The Qph3A-2 with additive effect was not reported in previous linkage mapping studies. The total QTL effects detected for the plant height explained 85.04% of the phenotypic variation, with additive effects 46.07%, epistatic effects 19.89%, and QEs 19.09%. The results showed that both additive effects and epistatic effects were important genetic bases of wheat plant height, which were subjected to environmental modifications, and caused dramatic changes in phenotypic effects. The information obtained in this study will be useful for manipulating the QTLs for wheat plant height by molecular marker-assisted selection (MAS).     

Inheritance and Gene Mapping of Resistance to Soybean Mosaic Virus Strain SC14 in Soybean

Soybean mosaic virus (SMV) is one of the most broadly distributed diseases worldwide. It causes severe yield loss and seed quality deficiency in soybean (Glycine max (L.) Merr.). SMV Strain SC14 isolated from Shanxi Province, China, was a newly identified virulent strain and can infect Kefeng No. 1, a source with wide spectrum resistance. In the present study, soybean accessions, PI96983, Qihuang No. 1 and Qihuang No. 22 were identified to be resistant (R) and Nannong 1138‐2, Pixianchadou susceptible (S) to SC14. Segregation analysis of PI96983 x Nannong 1138‐2 indicated that a single dominant gene (designated as R_SC14) controlled the resistance to SC14 at both V₂ and R₁ developmental stages. The same results were obtained for the crosses of Qihuang No. 1 × Nannong 1138‐2 and Qihuang No. 22 × Nannong 1138‐2 as in PI96983 × Nannong 1138‐2 at V₂ stage, but at R₁ stage, the F₁ performed as necrosis (a susceptible symptom other than mosaic), F₂ segregated in a ratio of 1R:2N:1S, and the progenies of necrotic (N) F₂ individuals segregated also in R, N and S. It indicated that a single gene (designated as R_SC14Q, to be different from that of PI96983) controlled the resistance to SC14, its dominance was the same as in PI96983 × Nannong 1138‐2 (without symptoms) at V₂ stage and not the same at R₁ stage. The tightly linked co‐dominant simple sequence repeat (SSR) marker Satt334 indicated that all the heterozygous bands were completely corresponding to the necrotic F₂ individuals, or all the necrotic F₂ individuals were heterozygotes. It was inferred that necrosis might be due to the interaction among SMV strains, resistance genes, genetic background of the resistance genes, and plant development stage. Furthermore, the bulked segregant analysis (BSA) of SSR markers was conducted to map the resistance genes. In F2of PI96983 × Nannong 1138‐2, five SSR markers, Sat_297, Sat_234, Sat_154, Sct_033 and Sat_120, were found closely linked to RSC14, with genetic distances of 14.5 cM, 11.3cM, 4.3cM,3.2cM and 6cM, respectively. In F₂ of Qihuang No. 1 × Nannong 1138‐2, three SSR markers, Sat_234, Satt334 and Sct_033, tightly linked to R_SC14Q with genetic distances of 7.2 cM, 1.4 cM and 2.8 cM, respectively. Based on the integrated joint map by Cregan et al. (1999), both RScMand R_SC14Q were located between Sat_234 and Sct_033 on linkage with group F of soybean, with their distances from Sct_033 at the same side being 3.2 cM and 2.8 cM, respectively. Therefore, RSC14and R_SC14Q might be on a same locus. The obtained information provides a basic knowledge for marker‐assisted selection of the resistance gene in soybean breeding programs and fine mapping and map‐based cloning of the resistance gene. (Managing editor: Li‐Hui Zhao)     

Genetic Variants in GAPDH Confer Susceptibility to Sporadic Parkinson’s Disease in a Chinese Han Population

Background

Accumulating evidence has demonstrated that the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a part of Lewy body inclusions and involves the pathogenesis of Parkinson’s disease (PD). However, it remains unknown whether or not genetic variation at the GAPDH locus contributes to the risk for PD.

Methods

A total of 302 sporadic PD patients and 377 control subjects were recruited in our study for assessing two single nucleotide polymorphisms (rs3741918 and rs1060619) in the GAPDH gene. Both allelic association and additive models were used to analyze association between GAPDH variants and risk for PD.

Results

Both polymorphisms were significantly associated with risk for PD after correction by Bonferroni multiple testing. The minor allele of rs3741918 was associated with decreased risk of sporadic PD (allelic contrast, OR = 0.74, 95% CI: 0.59–0.93, corrected P = 0.028; additive model, OR = 0.73, 95% CI: 0.58–0.92, corrected P = 0.018). While for the rs1060619 locus, the minor allele conferred increased risk for PD (allelic contrast, OR = 1.41, 95% CI: 1.14–1.75, corrected P = 0.007; additive model, OR = 1.43, 95% CI: 1.15–1.79, corrected P = 0.002).

Conclusion

Our study indicates that GAPDH variants confer susceptibility to sporadic PD in a Chinese Han population, which is consistent with the role of GAPDH protein in neuronal apoptosis. To our knowledge, this is the first study of genetic association between GAPDH locus and risk for PD in the Chinese population.     

An update of the Courtot × Chinese Spring intervarietal molecular marker linkage map for the QTL detection of agronomic traits in wheat

We made an update of the intervarietal molecular marker linkage map of the wheat genome developed using a doubled-haploid (DH) population derived from the cross between the cultivars "Courtot" and "Chinese Spring". This map was constructed using 187 DH lines and 659 markers. The genome was well covered (more than 95%) except for chromosomes from homoeologous group 4 and chromosomes 5D and 7D, which had gaps slightly larger than 50 cM. A core-map based on a set of 200 anchor loci (one marker each 18.4 cM) was developed. The total length of this map was 3,685 cM which is similar to the size of the international reference map of the ITMI population (3,551 cM). Map coverage was identical for the three genomes (A, B and D) and for the number of anchor loci, as well as for the size of the map. Using this map, QTLs for several agronomic traits were detected on phenotypic data from the population grown in Clermont-Ferrand (France) under natural field conditions over 6 years, and in Norwich (UK) in controlled conditions and under natural field conditions in 1 year. Almost all of the 21 chromosomes were involved in at least one trait. However, several regions seemed to contain gene clusters either for grain traits (and thus bread-making quality) or plant development traits.     

QTL for fibre-related traits in grain × sweet sorghum as a tool for the enhancement of sorghum as a biomass crop

Compared to maize and temperate grasses, sorghum has received less attention in terms of improving cell wall components. The objectives of this study were to identify quantitative trait loci (QTL) with main effects, epistatic and pleiotropic effects along with QTL × environment (QE) interactions controlling fibre-related traits in sorghum. Neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent lignin (ADL), cellulose, hemicellulose, fresh leaf mass, stripped stalk mass, dry stalk mass, fresh biomass and dry biomass were analysed from a population of 188 grain × sweet sorghum recombinant inbred lines. A genetic map consisting of 157 DNA markers was constructed, and QTL were detected using composite interval mapping (CIM). CIM detected more than 5 additive QTL per trait explaining 7.1–24.7% of the phenotypic variation. Abundant co-localization of these QTL was observed across all chromosomes, and the highest cluster was identified on chromosome 6. Searching for candidate genes using the confidence interval of our QTL clusters reveals that these clusters might comprise a set of genes that are tightly linked. Some QTL showed multiple effects; however, the allele for each trait was favouring the parent with the increasing effect. QE interactions were observed for QTL showing multiple effects. Additive × additive interaction was observed for 7 out of 10 traits, indicating the importance of epistatic analysis. However, the phenotypic variation explained by digenic interactions was lower compared to the individual QTL. Our results indicate that various genetic components contribute to fibre-related traits and should be considered during the enhancement of sorghum for lignocellulosic biomass.