Identification of QTL for maize grain yield and kernel-related traits

Grain yield (GY) is one of the most important and complex quantitative traits in maize (Zea mays L.) breeding practice. Quantitative trait loci (QTLs) for GY and three kernel-related traits were detected in a set of recombinant inbred lines (RILs). One hundred and seven simple sequence repeats (SSRs) and 168 insertion/deletion polymorphism markers (Indels) were used to genotype RILs. Eight QTLs were found to be associated with four yield-related traits: GY, 100-kernel weight (HKW), 10-kernel length (KL), and 10-kernel length width (KW). Each QTL explained between 5.96 (qKL2-1) and 13.05 (qKL1-1) per cent of the phenotypic variance. Notably, one common QTL, located at the marker interval between bnlg1893 and chr2-236477 (chromosomal bin 2.09) simultaneously controlled GY and HKW; another common QTL, at bin 2.03 was simultaneously responsible for HKW and KW. Of the QTLs identified, only one pair of significant epistatic interaction involved in chromosomal region at bin 2.03 was detected for HKW; no significant QTL × environment interactions were observed. These results provide the common QTLs and for marker-assisted breeding.     

Mapping QTLs controlling kernel dimensions in a wheat inter-varietal RIL mapping population

Key message

Seven kernel dimension QTLs were identified in wheat, and kernel thickness was found to be the most important dimension for grain weight improvement.

Abstract

Kernel morphology and weight of wheat (Triticum aestivum L.) affect both yield and quality; however, the genetic basis of these traits and their interactions has not been fully understood. In this study, to investigate the genetic factors affecting kernel morphology and the association of kernel morphology traits with kernel weight, kernel length (KL), width (KW) and thickness (KT) were evaluated, together with hundred-grain weight (HGW), in a recombinant inbred line population derived from Nanda2419?×?Wangshuibai, with data from five trials (two different locations over 3 years). The results showed that HGW was more closely correlated with KT and KW than with KL. A whole genome scan revealed four QTLs for KL, one for KW and two for KT, distributed on five different chromosomes. Of them, QKl.nau-2D for KL, and QKt.nau-4B and QKt.nau-5A for KT were newly identified major QTLs for the respective traits, explaining up to 32.6 and 41.5% of the phenotypic variations, respectively. Increase of KW and KT and reduction of KL/KT and KW/KT ratios always resulted in significant higher grain weight. Lines combining the Nanda 2419 alleles of the 4B and 5A intervals had wider, thicker, rounder kernels and a 14% higher grain weight in the genotype-based analysis. A strong, negative linear relationship of the KW/KT ratio with grain weight was observed. It thus appears that kernel thickness is the most important kernel dimension factor in wheat improvement for higher yield. Mapping and marker identification of the kernel dimension-related QTLs definitely help realize the breeding goals.

     

Genetic Dissection of Wheat Kernel Hardness Using Conditional QTL Mapping of Kernel Size and Protein-Related Traits

Kernel hardness (KH) is one of the primary quality parameters for common wheat (Triticum aestivum L.) and has a major impact on milling, flour quality, and end-product properties. In addition to Puroindoline (Pin) mutations and differences in Pin expression, other factors, such as kernel size and protein-related traits, play noticeable roles in determining hardness, but at the quantitative trait locus (QTL) level, the influence of these factors remains unclear. In this study, genetic relationships between KH and kernel size traits and between KH and protein-related traits were demonstrated by unconditional and conditional mapping using a wheat 90K genotyping assay with a segregating population of 173 recombinant inbred lines in four environments. Eight additive QTL for KH were detected using unconditional QTL mapping analysis; these QTL were primarily distributed on chromosomes 4B, 5A, 5B, and 6D, with phenotypic variation that ranged from 0.2 to 17.7%. In addition, one pair of epistatic QTL (QKH3B.4-65/QKH4B.6-2) was identified by unconditional mapping, and this pair accounted for 1.6% of the phenotypic variation. Through conditional mapping, after excluding the influences of kernel size and protein-related traits, 14 QTL were discovered and accounted for 0.6–18.5% of the phenotypic variation. Of them, the stable QTL QKH4B.4-17 made the largest contribution, which was partially contributed by the kernel length (KL), kernel thickness (KT), and dry gluten content (DGC). Furthermore, QKH4B.4-17 was crucially contributed by the kernel width (KW), kernel diameter (KD), kernel protein content (KPC), and wet gluten content (WGC) and was independent of the sedimentation volume (SV) and gluten index (GI). Another major QTL, QKH5B.10-63, was independent of the KW and KT; partly due to the variations in KL, KD, DGC, and WGC; and conclusively contributed by the KPC, SV, and GI. Seven additional QTL were only detected in the conditional analysis and were crucially contributed by kernel size or protein-related traits. These results demonstrated that kernel size and protein-related traits play significant roles in determining KH. The present study increases the understanding of the relationships between KH and kernel size and between KH and protein-related traits at the QTL level.     

中国重要玉米自交系种质资源子粒性状特征分析

玉米子粒性状是决定玉米产量的重要因素。为了解析中国重要玉米种质资源子粒性状的遗传变异基础,本研究以具有广泛遗传多样性的627份重要玉米自交系为材料,运用相关分析与逐步回归的方法,探讨了我国玉米自交系种质资源的子粒性状特征。结果表明,百粒体积与百粒重存在极显著正相关。逐步回归分析表明,百粒体积对百粒重表型变异的贡献高达78%。针对不同杂种优势群的子粒性状特征分析表明,粒宽对百粒体积的贡献率在瑞德、旅大红骨、兰卡斯特和P群中均为最大,贡献率在54%~71%之间。而在塘四平头类群中,粒厚和粒长的贡献率分别为45%和22%。该研究旨在为利用不同类型种质资源开展子粒性状遗传解析提供参考和依据。     

Single nucleotide polymorphism tightly linked to a major QTL on chromosome 7A for both kernel length and kernel weight in wheat

Thousand-kernel weight (TKW) is one of the major components of grain yield in wheat (Triticum aestivum). Identifying major quantitative trait loci (QTLs) for TKW and developing effective markers are prerequisite for success in marker-assisted selection (MAS) to improve wheat yield through breeding. This study mapped a major QTL, designated as TaTKW-7AL, for increasing TKW on the long arm of chromosome 7A of ‘Clark’ to a 1.3-cM interval between single nucleotide polymorphism (SNP) markers IWB13913 and IWA5913. This QTL explained 19.7 % of the phenotypic variation for TKW. A QTL for increasing kernel length (KL), one of the major components of TKW, was mapped in the same interval as TaTKW-7AL, suggesting that increased TKW by the QTL in ‘Clark’ is most likely due to the increased KL. Association analysis on a diversity panel of 200 US winter wheat accessions also identified a haplotype of three SNP markers (IWB13913, IWB6693 and IWA5913) that were tightly associated with the both KL and TKW. The analysis of allele frequencies of the haplotype in the diversity panel suggested that the favorable allele of TaTKW-7AL has not been strongly selected for in practice and has potential to be used to improve grain yield in US hard winter wheat breeding. Two user-friendly flanking KASPar markers, IWB13913 and IWA5913, were developed for MAS of TaTKW-7AL.     

Genetic diversity near the <Emphasis Type="Italic">DGAT1-2</Emphasis> gene for high oleic acid content and kernel trait variation in a maize breeding collection

Previous studies in maize have identified three quantitative trait loci (QTLs) coding for high oleic acid content (HOAC) (QTLs oleic6-1, oleic6-2, and oleic6-3) at bins 6.04–6.05, proximal to the DGAT1-2 gene. The aims of this work were (i) to discover new markers for linkage disequilibrium (LD) and haplotype analysis distal to DGAT1-2, (ii) to develop a new DGAT1-2 PCR probe to detect the allele determining HOAC (F469 insertion), (iii) to conduct cluster analysis for kernel traits, and (iv) to assess genetic diversity, LD, and association analysis for kernel traits with the DGAT1-2 PCR probe and 13 markers previously mapped near DGAT1-2 in the Argentine temperate maize collection of 111 inbred lines. The results showed high haplotype diversity distal to DGAT1-2 and relatedness between the inbred line LP199 (with HOAC) and the Non-Stiff Stalk line W22 (reference genome). The frequency of F469 was low (20%). F469 was clustered with flint-grain type characteristics, whereas HOAC was associated with F469 across linear models. Genetic diversity at bins 6.04–6.05 was high (0.62), whereas LD extent was low (r²?≤?0.45). This low extent of LD indicates a high level of recombination and no LD between DGAT1-2 and markers flanking QTLs oleic6-1 to 3. Nevertheless, the significant LD between markers flanking those QTLs and the cosegregation of F469 with nc009 (markers flanking QTLs oleic6-1 and 2) during inbred line conversion suggest that these QTLs might contribute to HOAC in the breeding collection. However, further studies are needed to precise mapping at bins 6.04–6.05 for breeding purposes.     

Mapping of QTLs associated with resistance to common bunt,tan spot,leaf rust,and stripe rust in a spring wheat population

Spring wheat (Triticum aestivum L.) breeding goals in western Canada include good agronomic characteristics and good end-use quality, and also moderate to elevated resistance to diseases of economic importance. In this study, we aimed to identify quantitative trait loci (QTL) associated with resistance to common bunt (Tilletia tritici and Tilletia laevis), tan spot (Pyrenophora tritici-repentis), leaf rust (Puccinia triticina), and stripe rust (Puccinia striiformis f. sp. tritici). A total of 167 recombinant inbred lines (RILs) derived from a cross between two spring wheat cultivars, ‘Attila’ and ‘CDC Go’, were evaluated for reactions to the four diseases in nurseries from three to eight environments, and genotyped with the Wheat 90K SNP array and three gene-specific markers (Ppd-D1, Vrn-A1, and Rht-B1). The RILs exhibited transgressive segregation for all four diseases, and we observed several lines either superior or inferior to the parents. Broad-sense heritability varied from 0.25 for leaf rust to 0.48 for common bunt. Using a subset of 1203 informative markers (1200 SNPs and 3 gene-specific markers) and average disease scores across all environments, we identified two QTLs (QCbt.dms-1B.2 and QCbt.dms-3A) for common bunt, and three QTLs each for tan spot (QTs.dms-2B, QTs.dms-2D, and QTs.dms-6B), leaf rust (QLr.dms-2D.1, QLr.dms-2D.2, and QLr.dms-3A), and stripe rust (QYr.dms-3A, QYr.dms-4A, and QYr.dms-5B). Each QTL individually explained between 5.9 and 18.7% of the phenotypic variation, and altogether explained from 21.5 to 26.5% of phenotypic and from 52.2 to 86.0% of the genetic variation. The resistance alleles for all QTLs except one for stripe rust (QYr.dms-5B) were from CDC Go. Some of the QTLs are novel, while others mapped close to QTLs and/or genes reported in other studies.     

Quantitative trait loci mapping of yield and related traits using a high-density genetic map of maize

Improving grain yield is the ultimate goal of the maize-breeding programs. In this study, analyses of conditional and unconditional quantitative trait locus (QTL) and epistatic interactions were used to elucidate the genetic architecture of yield and its related traits. A total of 15 traits of a recombinant inbred line population, including yield per plant (YPP), seven ear-related traits, and seven kernel-related traits, were measured in six different environments. Based on the genetic linkage map constructed using 2091 bins as markers, 56 main-effect QTLs for these traits were identified. These QTLs were distributed across eight genomic regions (bin 1.06, bin 4.02/4.05/4.08, bin 5.04, bin 7.04, bin 8.08, and bin 9.04), within the marker intervals of 85.45–6260.66 kb, and the phenotypic variance explained ranging from 5.69 to 11.56 %. One gene (GRMZM2G168229) encoding SBP-box domain protein was located in the small interval of qKRN4-3 and may be involved in patterning of kernel row number. Seventeen conditional QTLs identified for YPP were conditioned on its related traits and explained 6.18–23.15 % of the phenotypic variance. Conditional mapping analysis revealed that qYPP4-1, qYPP6-1, and qYPP8-1 are partially influenced by YPP-related traits at the individual QTL level. Digenic epistatic analysis identified 12 digenic interactions involving 22 loci across the whole genome. In addition, conditional digenic epistatic analysis identified 14 digenic interactions involving 21 loci. This study provides valuable information for understanding the genetic relationship between YPP and related traits and constitutes the first step toward the cloning of the relevant genes.     

Identification and validation of quantitative trait loci controlling seed isoflavone content across multiple environments and backgrounds in soybean

Soybean is important throughout the world not only due to the high seed protein and oil but also owing to the seed isoflavone. To improve the isoflavone concentration in seeds, detecting and mining the stable and reliable quantitative trait loci (QTLs) and related genes in multiple environments and genetic backgrounds become more and more important. In view of this, a F_6:7 recombinant inbred line (RIL) population of 345 lines derived from a cross between Zheng 92116 and Liaodou14 (ZL) was genotyped using 1739 polymorphic SNP and 127 SSR markers in this study and was phenotyped for individual and total seed isoflavone in four environments over 2 years. In total, 48 additive QTLs, which explained 3.00–29.83% of seed isoflavone variation, were identified. Of them, eight QTLs (qDA1_1, qGA1_1, qTIA1_1, qDA1_2, qGA1_2, qTIA1_2, qDA1_3, qTIA1_3) with phenotypic variation explained (PVE) ranging from 14.09 to 28.59% for daidzin, genistin, and total isoflavone were located on the same region of linkage group (LG) A1. These QTLs were further verified in another RIL population derived from Zheng 92116 × Qihuang 30 (ZQ). Meanwhile, the other four overlapping QTLs on linkage group B1, which were associated with glycitin content (qGLB1_1, qGLB1_2, qGLB1_3, qGLB1_4) and explained 16.52 to 29.83% of phenotypic variation, were also verified using the ZQ population. Moreover, the individuals with different genotypes at the common flanking SNP markers for these QTLs on LGs A1 and B1 in the two mapping populations showed significant different isoflavone content, which further validate the QTL mapping results. And also, some candidate genes might participate in the isoflavone biosynthesis processes were found in these stable QTL regions. Thus, the novel and stable QTLs identified and verified in this study could be applied in marker-assisted selection breeding or map-based candidate genes cloning in soybean seed isoflavone genetic improvement in future.     

Genetic mapping and confirmation of quantitative trait loci for grain chalkiness in rice

Grain chalkiness is a highly undesirable trait affecting rice grain quality and milled rice yield. In order to clarify the genetic basis of chalkiness, a recombinant inbred line population (RIL) derived from a cross between Beilu130 (a japonica cultivar with high chalkiness) and Jin23B (an indica cultivar with low chalkiness) was developed for quantitative trait locus (QTL) mapping. A total of 10 QTLs for white belly rate (WBR) and white core rate (WCR) were detected on eight different chromosomes over 2 years. Two QTLs for WBR (qWBR2 and qWBR5) showed similar chromosomal locations with GW2 and qSW5/GW5, which have been cloned previously to control the grain width and should be the right candidate genes. Three novel minor QTLs controlling WCR, qWCR1, qWCR3, and qWCR4 were further validated in near isogenic F₂ populations (NIL-F₂) and explained 26.1, 18.3, and 21.1% of the phenotypic variation, respectively. These QTLs could be targets for map-based cloning of the candidate genes to elucidate the molecular mechanism of chalkiness and for marker-assisted selection (MAS) in rice grain quality improvement.     

Identification of quantitative trait loci for resistance to rice black-streaked dwarf virus disease and small brown planthopper in rice

Small brown planthopper (SBPH) and its transmitted rice black-streaked dwarf virus disease (RBSDVD) cause serious damage to rice (Oryza sativa L.) production. Though breeding of resistant cultivars is believed to be one of the most important strategies for RBSDVD management, few high-resistance lines have been found to date. In the present study, we identified an indica variety, 9194, that is highly resistant to RBSDVD and analyzed the quantitative trait loci (QTLs) underlying this resistance . In total, four QTLs for RBSDVD resistance, viz. qRBSDV3, qRBSDV6, qRBSDV9, and qRBSDV11, were identified. Among them, qRBSDV6, qRBSDV9, and qRBSDV11 with LOD (logarithm [base 10] of odds) scores of 4.42–4.48, 2.11–7.26, and 5.01–7.16 were repeatedly detected in 2 years, accounting for 10.3–16.7%, 8.3–35.5%, and 20.0–31.1% of the total phenotypic variation, respectively. Further, introgression of single- or multiple-resistance QTLs into a susceptible rice variety by marker-assisted selection (MAS) indicated that stacking the QTLs could progressively enhance RBSDVD resistance, suggesting that these QTLs act additively. The same population was also used for QTL mapping of SBPH resistance. Four QTLs, viz. qSBPH1, qSBPH5, qSBPH8, and qSBPH9, with LOD scores of 2.72, 2.78, 2.15, and 2.85 were detected, explaining 13.7%, 11.0%, 12.0%, and 21.0% of the phenotypic variation, respectively. The identification of RBSDVD and SBPH resistance QTLs, and the development of single and multiple genes with pyramided lines, in this study provides innovative resources for molecular breeding of resistant rice cultivars.     

Locating QTLs controlling overwintering seedling rate in perennial glutinous rice 89-1 (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

A new cold tolerant germplasm resource named glutinous rice 89-1 (Gr89-1, Oryza sativa L.) can overwinter using axillary buds, with these buds being ratooned the following year. The overwintering seedling rate (OSR) is an important factor for evaluating cold tolerance. Many quantitative trait loci (QTLs) controlling cold tolerance at different growth stages in rice have been identified, with some of these QTLs being successfully cloned. However, no QTLs conferring to the OSR trait have been located in the perennial O. sativa L. To identify QTLs associated with OSR and to evaluate cold tolerance. 286 F₁₂ recombinant inbred lines (RILs) derived from a cross between the cold tolerant variety Gr89-1 and cold sensitive variety Shuhui527 (SH527) were used. A total of 198 polymorphic simple sequence repeat (SSR) markers that were distributed uniformly on 12 chromosomes were used to construct the linkage map. The gene ontology (GO) annotation of the major QTL was performed through the rice genome annotation project system. Three main-effect QTLs (qOSR2, qOSR3, and qOSR8) were detected and mapped on chromosomes 2, 3, and 8, respectively. These QTLs were located in the interval of RM14208 (35,160,202 base pairs (bp))–RM208 (35,520,147 bp), RM218 (8,375,236 bp)–RM232 (9,755,778 bp), and RM5891 (24,626,930 bp)–RM23608 (25,355,519 bp), and explained 19.6%, 9.3%, and 11.8% of the phenotypic variations, respectively. The qOSR2 QTL displayed the largest effect, with a logarithm of odds score (LOD) of 5.5. A total of 47 candidate genes on the qOSR2 locus were associated with 219 GO terms. Among these candidate genes, 11 were related to cell membrane, 7 were associated with cold stress, and 3 were involved in response to stress and biotic stimulus. OsPIP1;3 was the only one candidate gene related to stress, biotic stimulus, cold stress, and encoding a cell membrane protein. After QTL mapping, a total of three main-effect QTLs—qOSR2, qOSR3, and qOSR8—were detected on chromosomes 2, 3, and 8, respectively. Among these, qOSR2 explained the highest phenotypic variance. All the QTLs elite traits come from the cold resistance parent Gr89-1. OsPIP1;3 might be a candidate gene of qOSR2.     

<Emphasis Type="Italic">qRfg3</Emphasis>, a novel quantitative resistance locus against <Emphasis Type="Italic">Gibberella</Emphasis> stalk rot in maize

Key message

A quantitative trait locus  qRfg3 imparts recessive resistance to maize Gibberella stalk rot. qRfg3 has been mapped into a 350-kb interval and could reduce the disease severity index by ~26.6%.

Abstract

Gibberella stalk rot, caused by the fungal pathogen Fusarium graminearum, severely affects maize yield and grain quality worldwide. To identify more resistance quantitative trait loci (QTLs) against this disease, we analyzed a recombinant inbred line (RIL) population derived from a cross between resistant H127R and susceptible C7-2 inbred lines. Within this population, maize resistance to Gibberella stalk rot had high broad-sense heritability. A major QTL, qRfg3, on chromosome 3 was consistently detected across three field trials, accounting for 10.7–19.4% of the total phenotypic variation. Using a progeny-based sequential fine-mapping strategy, we narrowed qRfg3 down to an interval of ~350 kb. We further demonstrated that qRfg3 is a recessive resistance locus to Gibberella stalk rot that reduced the disease severity index by ~26.6%. Both the gene location and recessive genetic mode distinguish qRfg3 from other stalk rot resistance loci. Hence, qRfg3 is valuable as a complement to existing resistance QTLs to improve maize resistance to Gibberella stalk rot.

     

QTLs for heading date and plant height under multiple environments in rice

Both heading date and plant height are important traits related to grain yield in rice. In this study, a recombinant inbred lines (RILs) population was used to map quantitative trait loci (QTLs) for both traits under 3 long-day (LD) environments and 1 short-day (SD) environment. A total of eight QTLs for heading date and three QTLs for plant height were detected by composite interval mapping under LD conditions. Additional one QTL for heading date and three QTLs for plant height were identified by Two-QTL model under LD conditions. Among them, major QTLs qHd7.1, qHd7.2 and qHd8 for heading date, and qPh1 and qPh7.1 for plant height were commonly detected. qHd7.1 and qHd7.2 were mapped to small regions of less than 1 cM. Genome position comparison of previously cloned genes with QTLs detected in this study revealed that qHd5 and qPh3.1 were two novel QTLs. The alleles of these QTLs increasing trait values were dispersed in both parents, which well explained the transgressive segregation observed in this population. In addition, the interaction between qHd7.1 and qHd8 was detected under all LD conditions. Multiple-QTL model analysis revealed that all QTLs and their interactions explained over 80% of heading date variation and 50% of plant height variation. Two heading date QTLs were detected under SD condition. Of them, qHd10 were commonly identified under LD condition. The difference in QTL detection between LD and SD conditions indicated most heading date QTLs are sensitive to photoperiod. These findings will benefit breeding design for heading date and plant height in rice.     

Genetic dissection of starch paste viscosity characteristics in waxy maize revealed by high-density SNPs in a recombinant inbred line population

Starch paste viscosity properties are widely used as important indicators for quality estimation in waxy maize. To elucidate the genetic basis of paste viscosity characteristics of waxy maize, seven parameters from the rapid visco analyzer (RVA) profile were analyzed for quantitative trait loci (QTLs) in this study, using a recombinant inbred line population derived from a cross between the inbred lines Tongxi5 and Hengbai522. A high-density linkage map was constructed using 2703 bin markers, covering 1876.20 cM of the whole genome with an average genetic distance of 0.73 cM between adjacent bin markers. Seventy-two QTLs were detected for RVA parameters across 3 years, of which 17 could be identified in 2 years, and 6 identified in all 3 years. Eight QTL clusters were observed to be co-associated with two or more RVA parameters. Three major QTLs, qPV4-1, qTV4-1, and qFV5-2, which explained over 10% of the phenotypic variation, were stably mapped to the chromosomes 4 or 5 in all years. Based on functional annotations, two genes were considered as potential candidate genes for the identified major QTLs. The QTLs and candidate genes identified in this study will be useful for further understanding of the genetic architecture of starch paste viscosity characteristics in waxy maize, and may facilitate molecular breeding for grain quality improvement in breeding programs, and simultaneously provide a basis for cloning of the genes underlying these QTLs.     

Unconditional and conditional QTL analysis of kernel weight related traits in wheat (Triticum aestivum L.) in multiple genetic backgrounds

Wheat thousand kernel weight (TKW) is a complex trait, and is largely controlled by several kernel traits, including kernel length (KL) and kernel width (KW). In order to reveal the genetic relationship between TKW and these kernel traits (KW and KL) as accurate as possible, we applied both unconditional and conditional mapping analyses to three distinct genetic populations, one DH population and two RIL populations. This report describes the identifications of 36 unconditional and conditional additive QTLs and 30 pairs of unconditional and conditional epistatic QTLs, all of which are closely associated with TKW. While the conditional additive locus Qtkw1B, detected in the RIL2 population, exhibited the largest contribution, explaining 14.12 % of TKW variance, the unconditional epistatic QTLs Qtkw3A-2/Qtkw5B.1, detected in the DH population, accounted for 11.95 % of phenotypic variance. This study also showed that, compared with unconditional mapping, conditional mapping resulted in very different numbers and different extent of effects of additive and epistatic QTLs that were associated with TKW when TKW was conditioned on kernel traits (KW and KL). These data strongly suggest that KW and KL indeed play a significant role in determining TKW. Furthermore, we demonstrated that the effects of the 25 additive QTLs for TKW were either entirely or largely determined by KW, while the effects of the other 25 additive QTLs for TKW were either entirely or largely affected by KL. We conclude that the conditional mapping can be useful for a better understanding of the interrelationship between the yield contributing traits at the QTL level.     

Expression quantitative trait loci analysis of the Rubisco activase gene in maize

Expression quantitative trait loci (eQTL) analyses were applied in order to identify genetic factors that are relevant to the expression of a β-isoform Rubisco activase gene in maize, namely ZmRCAβ, in this study. During two years, a maize recombinant inbred line population was measured for ZmRCAβ expression levels at the grain filling stage. Based on a genetic map containing 916 molecular markers, we detected five eQTLs, namely qRCA2.1 on chromosome 2, and qRCA4.1, qRCA4.2, qRCA4.3, and qRCA4.4 on chromosome 4. These eQTLs explained the phenotypic variation ranging from 6.14% to 7.50% with the logarithm of the odd values ranging from 3.11 to 4.96. Based on the position of the eQTLs and ZmRCAβ on the chromosome, qRCA4.2 was inferred as a cis-eQTL and the remaining as a trans-eQTL, suggesting that a combination of both cis- and trans-acting elements might control ZmRCAβ expression. qRCA4.2, qRCA4.3, and qRCA4.4 were repeatedly detected during two years.     

Genetic analysis of shoot fresh weight in a cross of wild (<Emphasis Type="Italic">G. soja</Emphasis>) and cultivated (<Emphasis Type="Italic">G. max</Emphasis>) soybean

Shoot fresh weight (SFW) is one of the parameters, used to estimate the total plant biomass yield in soybean. In the present study, a total of 188 F_5:8 recombinant inbred lines (RIL) derived from an interspecific cross of PI 483463 (Glycine soja) and Hutcheson (Glycine max) were investigated for SFW variation in the field for three consecutive years. The parental lines and RILs were phenotyped in the field at the R6 stage by measuring total biomass in kg/plot to identify the QTLs for SFW. Three QTLs qSFW6_1, qSFW15_1, and qSFW19_1 influencing SFW were identified on chromosome 6, 15, and 19, respectively. The QTL qSFW19_1 flanked between the markers BARC-044913-08839 and BARC-029975-06765 was the stable QTL expressed in all the three environments. The phenotypic variation explained by the QTLs across all environments ranged from 6.56 to 21.32 %. The additive effects indicated contribution of alleles from both the parents and additive × environment interaction effects affected the expression of SFW QTL. Screening of the RIL population with additional SSRs from the qSFW19_1 region delimited the QTL between the markers SSR19-1329 and BARC-29975-06765. QTL mapping using bin map detected two QTLs, qSFW19_1A and qSFW19_1B. The QTL qSFW19_1A mapped close to the Dt1 gene locus, which affects stem termination, plant height, and floral initiation in soybean. Potential candidate genes for SFW were pinpointed, and sequence variations within their sequences were detected using high-quality whole-genome resequencing data. The findings in this study could be useful for understanding genetic basis of SFW in soybean.     

Rational design and analysis of an <Emphasis Type="Italic">Escherichia coli</Emphasis> strain for high-efficiency tryptophan production

l-tryptophan (l-trp) is a precursor of various bioactive components and has great pharmaceutical interest. However, due to the requirement of several precursors and complex regulation of the pathways involved, the development of an efficient l-trp production strain is challenging. In this study, Escherichia coli (E. coli) strain KW001 was designed to overexpress the l-trp operator sequences (trpEDCBA) and 3-deoxy-D-arabinoheptulosonate-7-phosphate synthase (aroG ^fbr ). To further improve the production of l-trp, pyruvate kinase (pykF) and the phosphotransferase system HPr (ptsH) were deleted after inactivation of repression (trpR) and attenuation (attenuator) to produce strain KW006. To overcome the relatively slow growth and to increase the transport rate of glucose, strain KW018 was generated by combinatorial regulation of glucokinase (galP) and galactose permease (glk) expression. To reduce the production of acetic acid, strain KW023 was created by repressive regulation of phosphate acetyltransferase (pta) expression. In conclusion, strain KW023 efficiently produced 39.7 g/L of l-trp with a conversion rate of 16.7% and a productivity of 1.6 g/L/h in a 5 L fed-batch fermentation system.