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Detecting genes that affect specific traits (such as human diseases and crop yields) is important for treating complex diseases and improving crop quality. A genome-wide association study (GWAS) provides new insights and directions for understanding complex traits by identifying important single nucleotide polymorphisms. Many GWAS summary statistics data related to various complex traits have been gathered recently. Studies have shown that GWAS risk loci and expression quantitative trait loci (eQTLs) often have a lot of overlaps, which makes gene expression gradually become an important intermediary to reveal the regulatory role of GWAS. In this review, we review three types of gene-trait association detection methods of integrating GWAS summary statistics and eQTLs data, namely colocalization methods, transcriptome-wide association study-oriented approaches, and Mendelian randomization-related methods. At the theoretical level, we discussed the differences, relationships, advantages, and disadvantages of various algorithms in the three kinds of gene-trait association detection methods. To further discuss the performance of various methods, we summarize the significant gene sets that influence high-density lipoprotein, low-density lipoprotein, total cholesterol, and triglyceride reported in 16 studies. We discuss the performance of various algorithms using the datasets of the four lipid traits. The advantages and limitations of various algorithms are analyzed based on experimental results, and we suggest directions for follow-up studies on detecting gene-trait associations. [ABSTRACT FROM AUTHOR]

Key message: A total of 389 and 344 QTLs were identified by GWAS and QTL mapping explaining accumulatively 32.2–65.0% and 23.7–63.4% of phenotypic variation for 14 shoot-borne root traits using more than 1300 individuals across multiple field trails. Efficient nutrient and water acquisition from soils depends on the root system architecture (RSA). However, the genetic determinants underlying RSA in maize remain largely unexplored. In this study, we conducted a comprehensive genetic analysis for 14 shoot-borne root traits using 513 inbred lines and 800 individuals from four recombinant inbred line (RIL) populations at the mature stage across multiple field trails. Our analysis revealed substantial phenotypic variation for these 14 root traits, with a total of 389 and 344 QTLs identified through genome-wide association analysis (GWAS) and linkage analysis, respectively. These QTLs collectively explained 32.2–65.0% and 23.7–63.4% of the trait variation within each population. Several a priori candidate genes involved in auxin and cytokinin signaling pathways, such as IAA26, ARF2, LBD37 and CKX3, were found to co-localize with these loci. In addition, a total of 69 transcription factors (TFs) from 27 TF families (MYB, NAC, bZIP, bHLH and WRKY) were found for shoot-borne root traits. A total of 19 genes including PIN3, LBD15, IAA32, IAA38 and ARR12 and 19 GWAS signals were overlapped with selective sweeps. Further, significant additive effects were found for root traits, and pyramiding the favorable alleles could enhance maize root development. These findings could contribute to understand the genetic basis of root development and evolution, and provided an important genetic resource for the genetic improvement of root traits in maize. [ABSTRACT FROM AUTHOR]

Tocopherol is an important lipid-soluble antioxidant beneficial for both human health and plant growth. Here, we fine mapped a major QTL-qVE1 affecting γ-tocopherol content in maize kernel, positionally cloned and confirmed the underlying gene ZmPORB1 (por1), as a protochlorophyllide oxidoreductase. A 13.7 kb insertion reduced the tocopherol and chlorophyll content, and the photosynthetic activity by repressing ZmPORB1 expression in embryos of NIL-K22, but did not affect the levels of the tocopherol precursors HGA (homogentisic acid) and PMP (phytyl monophosphate). Furthermore, ZmPORB1 is inducible by low oxygen and light, thereby involved in the hypoxia response in developing embryos. Concurrent with natural hypoxia in embryos, the redox state has been changed with NO increasing and H2O2 decreasing, which lowered γ-tocopherol content via scavenging reactive nitrogen species. In conclusion, we proposed that the lower light-harvesting chlorophyll content weakened embryo photosynthesis, leading to fewer oxygen supplies and consequently diverse hypoxic responses including an elevated γ-tocopherol consumption. Our findings shed light on the mechanism for fine-tuning endogenous oxygen concentration in the maize embryo through a novel feedback pathway involving the light and low oxygen regulation of ZmPORB1 expression and chlorophyll content. [ABSTRACT FROM AUTHOR]

Southern corn leaf blight (SCLB) seriously threatens corn production. The timely and accurate monitoring of SCLB conditions (e.g., detection during the asymptomatic stage and severity classification during the symptomatic stage) is valuable for precision agriculture, because the application of pesticides depends on disease conditions. Compared with time-consuming and laborious field surveys, spectroscopy is a promising tool for plant disease monitoring. The unique advantages of combining multiple spectral enhancement features for monitoring rice and wheat diseases have been recognized. However, physiological and biochemical differences between maize leaves and rice and wheat leaves, along with the specific spectral response of SCLB, are likely to affect the performance of combining multiple spectral enhancement features. In addition, similar previous studies have not combined spectral slope features, i.e., first-order spectral derivatives (FSDs), with spectral bands (SBs) and spectral indices (SIs) and wavelet features (WFs) to improve plant disease detection. Thus, the performance of a method that combines FSDs, WFs, SBs, and SIs for SCLB asymptomatic detection, symptomatic detection, and symptomatic severity classification should be evaluated further. Here, the utility of combining SBs, SIs, WFs, and FSDs was quantified and evaluated in the asymptomatic detection, symptomatic detection, and symptomatic severity classification of SCLB. Various forms of spectral enhancement features that were sensitive to SCLB infection from the asymptomatic stage to the severe stage were first identified and combined using the RELIEF-F and sequential floating forward selection algorithms on the basis of two independent inoculation experiments. Finally, SCLB asymptomatic detection, symptomatic detection, and symptomatic severity classification models were developed and evaluated using the support vector machine algorithm. Results showed that combining FSDs with SBs, SIs, and WFs achieved the best performance in SCLB spectroscopic monitoring. (1) SCLB asymptomatic detection and symptomatic detection were moderately improved, i.e., overall accuracy (OA) and macro F1 (MF1) improved by ~ 1% to 2%. The OA of SCLB asymptomatic detection was 87.1% with an MF1 of 0.87, and that of symptomatic detection was 93.1% with an MF1 of 0.93. (2) SCLB symptomatic severity classification was significantly improved, i.e., OA and MF1 improved by ~ 7%. The OA of severity classification was 81.8% with am MF1 of 0.82. This study demonstrated that the complementary relationships among SBs, SIs, WFs, and FSDs could effectively improve SCLB spectroscopic monitoring. The proposed method provides a novel tool for large-scale SCLB spectroscopic monitoring. It has broad implications for assisting management decisions (i.e., when and where to apply pesticides and how much to apply) in precision agriculture. [ABSTRACT FROM AUTHOR]

The genomic basis underlying the selection for environmental adaptation and yield-related traits in maize remains poorly understood. Here we carried out genome-wide profiling of the small RNA (sRNA) transcriptome (sRNAome) and transcriptome landscapes of a global maize diversity panel under dry and wet conditions and uncover dozens of environment-specific regulatory hotspots. Transgenic and molecular studies of Drought-Related Environment-specific Super eQTL Hotspot on chromosome 8 (DRESH8) and ZmMYBR38, a target of DRESH8-derived small interfering RNAs, revealed a transposable element-mediated inverted repeats (TE-IR)-derived sRNA- and gene-regulatory network that balances plant drought tolerance with yield-related traits. A genome-wide scan revealed that TE-IRs associate with drought response and yield-related traits that were positively selected and expanded during maize domestication. These results indicate that TE-IR-mediated posttranscriptional regulation is a key molecular mechanism underlying the tradeoff between crop environmental adaptation and yield-related traits, providing potential genomic targets for the breeding of crops with greater stress tolerance but uncompromised yield. Transposon-associated inverted repeats play a role in drought resistance and yield-related traits in maize. [ABSTRACT FROM AUTHOR]

Unilateral cross incompatibility (UCI) occurs between popcorn and dent corn, and represents a critical step towards speciation. It has been reported that ZmGa1P, encoding a pectin methylesterase (PME), is a male determinant of the Ga1 locus. However, the female determinant and the genetic relationship between male and female determinants at this locus are unclear. Here, we report three different types, a total of seven linked genes underlying the Ga1 locus, which control UCI phenotype by independently affecting pollen tube growth in both antagonistic and synergistic manners. These include five pollen-expressed PME genes (ZmGa1Ps-m), a silk-expressed PME gene (ZmPME3), and another silk-expressed gene (ZmPRP3), encoding a pathogenesis-related (PR) proteins. ZmGa1Ps-m confer pollen compatibility. Presence of ZmPME3 causes silk to reject incompatible pollen. ZmPRP3 promotes incompatibility pollen tube growth and thereby breaks the blocking effect of ZmPME3. In addition, evolutionary genomics analyses suggest that the divergence of the Ga1 locus existed before maize domestication and continued during breeding improvement. The knowledge gained here deepen our understanding of the complex regulation of cross incompatibility. Unilateral cross incompatibility (UCI) is a type of prezygotic reproductive isolation, which is associated with multiple loci in maize. Here, the authors use genetic analysis to separate the Ga1 locus into two functional components and identify seven linked genes encoding three types of proteins. [ABSTRACT FROM AUTHOR]

In this study, based on automatic control and image processing, a high-throughput and low-cost maize ear traits scorer (METS) was developed for the automatic measurement of 34 maize ear traits. In total, 813 maize ears were measured using METS, and the results showed that the square of the correlation coefficient (R2) of the manual measurements versus the automatic measurements for ear length, ear diameter, and kernel thickness were 0.96, 0.79, and 0.85, respectively. These maize ear traits could be used to classify the type, and the results showed that the classification accuracy of the support vector machine (SVM) model for the test set was better than that of the random forest (RF) model. In addition, the general applicability of the image analysis pipeline was also demonstrated on other independent maize ear phenotyping platforms. In conclusion, equipped with image processing and automatic control technologies, we have developed a high-throughput method for maize ear scoring, which could be popularized in maize functional genetics, genomics, and breeding applications. [ABSTRACT FROM AUTHOR]

In recent years, deep learning has been widely used in diverse fields of research, such as speech recognition, image classification, autonomous driving and natural language processing. Deep learning has showcased dramatically improved performance in complex classification and regression problems, where the intricate structure in the high-dimensional data is difficult to discover using conventional machine learning algorithms. In biology, applications of deep learning are gaining increasing popularity in predicting the structure and function of genomic elements, such as promoters, enhancers, or gene expression levels. In this review paper, we described the basic concepts in machine learning and artificial neural network, followed by elaboration on the workflow of using convolutional neural network in genomics. Then we provided a concise introduction of deep learning applications in genomics and synthetic biology at the levels of DNA, RNA and protein. Finally, we discussed the current challenges and future perspectives of deep learning in genomics. [ABSTRACT FROM AUTHOR]

Key message: Genetic relationships among Chinese maize germplasms reveal historical trends in heterotic patterns from Chinese breeding programs and identify line Dan340 as a potential genome donor for elite inbred line Zheng58.Abstract: The characterization of the genetic relationships, heterotic patterns and breeding history of lines in maize breeding programs allows breeders to efficiently use maize germplasm for line improvement over time. In this study, 269 temperate inbred lines, most of which have been widely used in Chinese maize breeding programs since the 1970s, were genotyped using the Illumina MaizeSNP50 BeadChip, which contains 56,110 single-nucleotide polymorphisms. The STRUCTURE analysis, cluster analysis and principal coordinate analysis results consistently revealed seven groups, of which five were consistent with known heterotic groups within the Chinese maize germplasm—Domestic Reid, Lancaster, Zi330, Tang SPT and Tem-tropic I (also known as “P”). These genetic relationships also allowed us to determine the historical trends in heterotic patterns during the three decades from 1970 to 2000, represented by Mo17 from Lancaster, HuangZaoSi (HZS) from Tang SPT, Ye478 from Domestic Reid and P178 from Tem-tropic I heterotic groups. Mo17-related commercial hybrids were widely used in the 1970s and 1980s, followed by the release of HZS- and Ye478-related commercial hybrids in the 1980s and 1990s, and the introduction of Tem-tropic I group in the 1990s and 2000s. Additionally, we identified inbred line Dan340 as a potential genome donor for Zheng58, which is the female parent of the most widely grown commercial hybrid ZhengDan958 in China. We also reconstructed the recombination events of elite line HZS and its 14 derived lines. These findings provide useful information to direct future maize breeding efforts. [ABSTRACT FROM AUTHOR]

Key message: Sixteen major QTLs regulating maize kernel traits were mapped in multiple environments and one of them, qKW - 9.2 , was restricted to 630 Kb, harboring 28 putative gene models. Abstract: To elucidate the genetic basis of kernel traits, a quantitative trait locus (QTL) analysis was conducted in a maize recombinant inbred line population derived from a cross between two diverse parents Zheng58 and SK, evaluated across eight environments. Construction of a high-density linkage map was based on 13,703 single-nucleotide polymorphism markers, covering 1860.9 cM of the whole genome. In total, 18, 26, 23, and 19 QTLs for kernel length, width, thickness, and 100-kernel weight, respectively, were detected on the basis of a single-environment analysis, and each QTL explained 3.2-23.7 % of the phenotypic variance. Sixteen major QTLs, which could explain greater than 10 % of the phenotypic variation, were mapped in multiple environments, implying that kernel traits might be controlled by many minor and multiple major QTLs. The major QTL qKW- 9.2 with physical confidence interval of 1.68 Mbp, affecting kernel width, was then selected for fine mapping using heterogeneous inbred families. At final, the location of the underlying gene was narrowed down to 630 Kb, harboring 28 putative candidate-gene models. This information will enhance molecular breeding for kernel traits and simultaneously assist the gene cloning underlying this QTL, helping to reveal the genetic basis of kernel development in maize. [ABSTRACT FROM AUTHOR]

Key message: Genetic determinants of metabolites related to drought tolerance in maize. Abstract: Water deficit or drought is one of the most serious abiotic stresses of plant development and greatly reduces crop production, and the plant's response to this deficit leads to many metabolic changes. To dissect the genetic basis of these metabolic traits in maize, we performed a genome-wide association analysis of drought-related traits using 156,599 SNPs in 318 maize inbred lines. In total, 123 significant SNP/trait associations ( P ≤ 6.39E−6) involving 63 loci were identified for related metabolic and physiological traits in multiple tissues and different environments under two irrigation conditions. Of the 63, 23 loci demonstrated a significant interaction effect between QTL and water status, indicating that these metabolite-associated loci were probably related to drought stress tolerance. To evaluate the potential utility of metabolite-associated loci applied in hybrid maize breeding, we assembled two groups of hybrid entries with high or low drought tolerance and measured the metabolic and physiological traits. In the hybrid pools, a set of 10 metabolite-associated loci identified in leaf and ear were validated as responsive to drought stress. The favorable alleles of these ten loci were significantly enriched in hybrids with high drought tolerance, which jointly explained almost 18.4 % of the variation in drought tolerance using a multivariate logistic regression model. These results provide clues to understanding the genetic basis of metabolic and physiological changes related to drought tolerance, potentially facilitating the genetic improvement of varieties with high drought tolerance in maize breeding programs. [ABSTRACT FROM AUTHOR]

Sugarcane mosaic virus (SCMV) is one of the most damaging virus diseases in maize. Two major loci, Scmv1 and Scmv2, have been identified in many studies across a broad spectrum of germplasm by linkage mapping. In this study, we undertook a genome-wide association study (GWAS) in a maize association panel comprising 504 diverse inbred lines with over 556,000 SNP markers in three environments. Extensive phenotypic variation of resistance to SCMV was observed in the association panel. GWAS identified five genes significantly associated with resistance to SCMV. A cluster of four genes was detected near or within the Scmv2 region on chromosome 3 (bin 3.05). GRMZM2G116204, which encoded auxin binding protein and resided within the fine-mapped Scmv2 region, was predicted as the most likely candidate gene for Scmv2. In conclusion, we found that GWAS along with linkage analyses are effective approaches to the mapping of resistance to SCMV and to the subsequent identification of causal genes. [ABSTRACT FROM AUTHOR]

Northern corn leaf blight (NCLB) is a prevalent foliar disease in maize. Deployment of resistant cultivars is an effective way to control NCLB. In this study, 207 recombinant inbred lines derived from a K22 × By815 cross were planted in Yangling, China, in 2012 and 2013. NCLB score and lesion size were investigated after artificial inoculation. Significant phenotypic variation in NCLB resistance was observed in both years. Using a genetic map containing high-density single-nucleotide polymorphisms with average genetic distance of 0.74 cM, quantitative trait loci (QTL) for NCLB score and lesion size were analyzed. For NCLB score, four and three QTL were identified in 2012 and 2013, respectively. Two stable QTL were identified in both years. Of these, qNCLB5.04, located on chromosome 5 (bin 5.04), had the largest resistance effect, accounting for 19 and 20 % of the phenotypic variation in 2012 and 2013, respectively. For lesion size, six QTL were identified. Of these, one consensus QTL was associated with both lesion length and width, and the other five were associated only with lesion width. Among all QTL identified, only qNCLB5.04 was associated with both NCLB score and lesion size. Thus, our mapping results suggest that qNCLB5.04 could be a desirable target for marker-assisted selection for NCLB resistance in maize breeding programs. [ABSTRACT FROM AUTHOR]

Key message: Maize kernel row number might be dominated by a set of large additive or partially dominant loci and several small dominant loci and can be accurately predicted by fewer than 300 top KRN-associated SNPs. Abstract: Kernel row number (KRN) is an important yield component in maize and directly affects grain yield. In this study, we combined linkage and association mapping to uncover the genetic architecture of maize KRN and to evaluate the phenotypic predictability using these detected loci. A genome-wide association study revealed 31 associated single nucleotide polymorphisms (SNPs) representing 17 genomic loci with an effect in at least one of five individual environments and the best linear unbiased prediction (BLUP) over all environments. Linkage mapping in three F populations identified 33 KRN quantitative trait loci (QTLs) representing 21 QTLs common to several population/environments. The majority of these common QTLs that displayed a large effect were additive or partially dominant. We found 70 % KRN-associated genomic loci were mapped in KRN QTLs identified in this study, KRN-associated SNP hotspots detected in NAM population and/or previous identified KRN QTL hotspots. Furthermore, the KRN of inbred lines and hybrids could be predicted by the additive effect of the SNPs, which was estimated using inbred lines as a training set. The prediction accuracy using the top KRN-associated tag SNPs was obviously higher than that of the randomly selected SNPs, and approximately 300 top KRN-associated tag SNPs were sufficient for predicting the KRN of the inbred lines and hybrids. The results suggest that the KRN-associated loci and QTLs that were detected in this study show great potential for improving the KRN with genomic selection in maize breeding. [ABSTRACT FROM AUTHOR]

Key message: Thirty loci for fertility restoration of pollen fertility, anther exsertion and pollen shedding to maize CMS-S were identified by GWAS. Abstract: S type cytoplasmic male sterile (CMS-S) is the main type of CMS in maize; poor understanding of the genetic architecture of fertility restoration to CMS-S is one of the reasons to impede its utility in hybrid breeding. In this study, genome-wide identification of genetic loci for fertility restoration ability to CMS-S was firstly conducted with a set of testcrossing association mapping panel in three environments. A total of 19, 3 and 8 significant loci ( P < 1.8 × 10, α = 1) for pollen fertility, anther exsertion and pollen shedding were identified, respectively, and individual locus explained up to 28.26 % of phenotypic variation. Of them, only Rf3, the main restorer-fertility gene of CMS-S, was identified for the three traits simultaneously. In addition, 83 candidate genes within the 100 kb extension regions of these loci were predicted. These results revealed that besides Rf3 multiple genetic loci and mechanisms are involved in the fertility restoration ability to CMS-S. Results in this study would provide important information for understanding the genetic architecture of fertility restoration to CMS-S in maize. [ABSTRACT FROM AUTHOR]

Head smut is a systemic disease in maize caused by the soil-borne fungus Sporisorium reilianum that poses a grave threat to maize production worldwide. A major head smut quantitative resistance locus, qHSR1, has been detected on maize chromosome bin2.09. Here we report the map-based cloning of qHSR1 and the molecular mechanism of qHSR1-mediated resistance. Sequential fine mapping and transgenic complementation demonstrated that ZmWAK is the gene within qHSR1 conferring quantitative resistance to maize head smut. ZmWAK spans the plasma membrane, potentially serving as a receptor-like kinase to perceive and transduce extracellular signals. ZmWAK was highly expressed in the mesocotyl of seedlings where it arrested biotrophic growth of the endophytic S. reilianum. Impaired expression in the mesocotyl compromised ZmWAK-mediated resistance. Deletion of the ZmWAK locus appears to have occurred after domestication and spread among maize germplasm, and the ZmWAK kinase domain underwent functional constraints during maize evolution. [ABSTRACT FROM AUTHOR]

Key message: Genetic basis of grain yield heterosis relies on the cumulative effects of dominance, overdominance, and epistasis in maize hybrid Yuyu22. Abstract: Heterosis, i.e., when F hybrid phenotypes are superior to those of the parents, continues to play a critical role in boosting global grain yield. Notwithstanding our limited insight into the genetic and molecular basis of heterosis, it has been exploited extensively using different breeding approaches. In this study, we investigated the genetic underpinnings of grain yield and its components using 'immortalized F' and recombinant inbred line populations derived from the elite hybrid Yuyu22. A high-density linkage map consisting of 3,184 bins was used to assess (1) the additive and additive-by-additive effects determined using recombinant inbred lines; (2) the dominance and dominance-by-dominance effects from a mid-parent heterosis dataset; and (3) the various genetic effects in the 'immortalized F' population. Compared with a low-density simple sequence repeat map, the bin map identified more quantitative trait loci, with higher LOD scores and better accuracy of detecting quantitative trait loci. The bin map showed that, among all traits, dominance was more important to heterosis than other genetic effects. The importance of overdominance/pseudo-overdominance was proportional to the amount of heterosis. In addition, epistasis contributed to heterosis as well. Phenotypic variances explained by the QTLs detected were close to the broad-sense heritabilities of the observed traits. Comparison of the analyzed results obtained for the 'immortalized F' population with those for the mid-parent heterosis dataset indicated identical genetic modes of action for mid-parent heterosis and grain yield performance of the hybrid. [ABSTRACT FROM AUTHOR]

Drought can cause severe reduction in maize production, and strongly threatens crop yields. To dissect this complex trait and identify superior alleles, 350 tropical and subtropical maize inbred lines were genotyped using a 1536-SNP array developed from drought-related genes and an array of 56,110 random SNPs. The inbred lines were crossed with a common tester, CML312, and the testcrosses were phenotyped for nine traits under well-watered and water-stressed conditions in seven environments. Using genome-wide association mapping with correction for population structure, 42 associated SNPs ( P ≤ 2.25 × 10 0.1/ N) were identified, located in 33 genes for 126 trait × environment × treatment combinations. Of these genes, three were co-localized to drought-related QTL regions. Gene GRMZM2G125777 was strongly associated with ear relative position, hundred kernel weight and timing of male and female flowering, and encodes NAC domain-containing protein 2, a transcription factor expressed in different tissues. These results provide some good information for understanding the genetic basis for drought tolerance and further studies on identified candidate genes should illuminate mechanisms of drought tolerance and provide tools for designing drought-tolerant maize cultivars tailored to different environmental scenarios. [ABSTRACT FROM AUTHOR]

To investigate the genetic basis of maize seedling response to waterlogging, we performed a genome-wide association study in 144 maize inbred lines, measuring length, fresh and dry weight of roots and shoots under normal and waterlogged conditions using 45,868 SNPs. This panel was divided into three subgroups based on the population structure results and the LD decay distance was 180 kb. A biparental advanced backcross (AB) population was also used to detect quantitative trait loci (QTL). In a comparison of 16 different models, principal components analysis (PCA/top PC3) + K was found to be best for reduction of false-positive associations for further analysis. A whole-genome scan detected four strong peak signals ( P < 2.18 × 10) significantly associated with the waterlogging response on chromosomes 5, 6 and 9. SNP4784, SNP200, SNP298, and SNP6314 showed significant association with corresponding traits under waterlogging and explained 14.99-19.36 %, 15.75-17.64 %, 16.08 % and 15.44 % of the phenotypic variation, respectively. The identified SNPs were located in GRMZM2G012046, GRMZM2G009808, GRMZM2G137108 and GRMZM2G369629 (AGPV1). SNP4784 (GRMZM2G012046) was colocalized with the major QTL that was identified with the same traits in the AB population. Forty-seven SNPs significantly associated ( P < 2.18 × 10) with six traits in association mapping were identified and, among these, 33 SNPs were already reported in literature as waterlogging-related traits. These results will help elucidate the genetic basis of differential responses and tolerance to waterlogging stress among maize inbred lines, and provide novel loci for improvement of waterlogging tolerance of maize inbred lines using marker-assisted selection. [ABSTRACT FROM AUTHOR]

Provitamin A (Pro-VA) is necessary for human vision and immune system health, especially in growing children. The first committed step in the maize carotenoid biosynthesis pathway is catalyzed by phytoene synthase 1 (encoded by PSY1) which controls the flux of substrates into the pathway. The flow of these substrates could be directed into production of the β-branch carotenoids (the step controlled largely by the lycopene epsilon cyclase gene), but terminated after the production of β-carotene, rather than allowing it to be converted into the next metabolite (the step controlled largely by the β- carotenoid hydroxylase gene). In this study, PSY1 was subjected to association mapping in two diverse maize populations, quantitative trait loci (QTL) mapping in one segregating population, and expression analysis of lines polymorphic for sites within PSY1. The results indicated that a 378-bp InDel upstream of the transcription start site and a SNP in the fifth exon resulting in a Thr to Asn substitution, explaining 7 and 8 % of the total carotenoid variation, respectively, may be functional sites associated with total carotenoid levels in maize grain. Analysis of the evolution of PSY1 strongly suggests that there was positive selection for these polymorphic sites after the divergence of yellow maize from white maize. [ABSTRACT FROM AUTHOR]

Vitamin A deficiency (VAD) compromises immune function and is the leading cause of preventable blindness in children in many developing countries. Biofortification, or breeding staple food crops that are rich in micronutrients, provides a sustainable way to fight VAD and other micronutrient malnutrition problems. Polymorphisms, with associated molecular markers, have recently been identified for two loci, LcyE (lycopene epsilon cyclase) and CrtRB1 (β-carotene hydroxylase 1) that govern critical steps in the carotenoid biosynthetic pathway in maize endosperm, thereby enabling the opportunity to integrate marker-assisted selection (MAS) into carotenoid breeding programs. We validated the effects of 3 polymorphisms (LcyE5′TE, LcyE3′Indel and CrtRB1-3′TE) in 26 diverse tropical genetic backgrounds. CrtRB1-3′TE had a two-ten fold effect on enhancing beta-carotene (BC) and total provitamin A (proA) content. Reduced-function, favorable polymorphisms within LcyE resulted in 0-30 % reduction in the ratio of alpha- to beta-branch carotenoids, and increase in proA content (sometimes statistically significant). CrtRB1-3′TE had large, significant effect on enhancing BC and total ProA content, irrespective of genetic constitution for LcyE5′TE. Genotypes with homozygous favorable CrtRB1-3′TE alleles had much less zeaxanthin and an average of 25 % less total carotenoid than other genotypes, suggesting that feedback inhibition may be reducing the total flux into the carotenoid pathway. Because this feedback inhibition was most pronounced in the homozygous favorable LcyE (reduced-function) genotypes, and because maximum total proA concentrations were achieved in genotypes with homozygous unfavorable or heterozygous LcyE, we recommend not selecting for both reduced-function genes in breeding programs. LcyE exhibited significant segregation distortion (SD) in all the eight, while CrtRB1 in five of eight digenic populations studied, with favorable alleles of both the genes frequently under-represented. MAS using markers reported herein can efficiently increase proA carotenoid concentration in maize. [ABSTRACT FROM AUTHOR]

Maize kernel oil is a valuable source of nutrition. Here we extensively examine the genetic architecture of maize oil biosynthesis in a genome-wide association study using 1.03 million SNPs characterized in 368 maize inbred lines, including 'high-oil' lines. We identified 74 loci significantly associated with kernel oil concentration and fatty acid composition (P < 1.8 × 10?6), which we subsequently examined using expression quantitative trait loci (QTL) mapping, linkage mapping and coexpression analysis. More than half of the identified loci localized in mapped QTL intervals, and one-third of the candidate genes were annotated as enzymes in the oil metabolic pathway. The 26 loci associated with oil concentration could explain up to 83% of the phenotypic variation using a simple additive model. Our results provide insights into the genetic basis of oil biosynthesis in maize kernels and may facilitate marker-based breeding for oil quantity and quality. [ABSTRACT FROM AUTHOR]

Selection of recombinant inbred lines (RILs) from elite hybrids is a key method in maize breeding especially in developing countries. The RILs are normally derived by repeated self-pollination and selection. In this study, we first investigated the accuracy of different models in predicting the performance of F hybrids between RILs derived from two elite maize inbred lines Zong3 and 87-1, and then compared these models through simulation using a wider range of genetic models. Results indicated that appropriate prediction models depended on genetic architecture, e.g., combined model using breeding value and genome-wide prediction (BV+GWP) has the highest prediction accuracy for high V/ V ratio (>0.5) traits. Theoretical studies demonstrated that different components of genetic variance were captured by different prediction models, which in turn explained the accuracy of these models in predicting the F hybrid performance. Based on genome-wide prediction model (GWP), 114 untested F hybrids possibly having higher grain yield than the original F hybrid Yuyu22 (the single cross between Zong3 and 87-1) have been identified and recommended for further field test. [ABSTRACT FROM AUTHOR]

Most of the maize kernel oil is located in the embryo while the majority of starch is located in the endosperm. Maize kernel composition and value are affected significantly by the ratio of the embryo size to the endosperm size; however, the genetic regulation of embryo to endosperm ratio (EER) in maize is unknown. Here we identified ZmGE2 gene, which encodes a cytochrome p450 protein, as a gene associated with EER variation in maize. We first expressed rice Giant Embryo ( GE) gene driven by oleosin promoter in maize and detected a 23.2 % reduction in EER in transgenic seeds, demonstrating the existence of evolutionarily conserved mechanisms for EER determination in rice and maize. We next identified maize GE2, a homolog of rice GE sharing 70 % identity in amino sequence, as a candidate based on the similar expression pattern and co-localization with a previously detected QTL for EER. Followed by linkage and association mapping, a 247-bp transposable element (TE) insertion in 3′-untranslated region of ZmGE2 gene was identified to be associated with increase in EER and kernel oil content. Expression level of the favorable ZmGE2 allele containing the 247-bp TE insertion was strongly reduced. In addition, the 247-bp TE insertion site was a selection target during the artificial long-term selection for the high EER trait in a high oil population. This is the first report that demonstrates an association of ZmGE2 with EER variation in maize and identifies ZmGE2 gene as a promising target for manipulation of EER and grain composition by either transgenic approach or molecular breeding in maize. [ABSTRACT FROM AUTHOR]

Kernel oil content in maize is a complex quantitative trait. Phenotypic variation in kernel oil content can be dissected into its component traits such as oil metabolism and physical characteristics of the kernel, including embryo size and embryo-to-endosperm weight ratio (EEWR). To characterize quantitative trait loci (QTL) for kernel oil content, a recombinant inbred population derived from a cross between normal line B73 and high-oil line By804 was genotyped using 228 molecular markers and phenotyped for kernel oil content and its component traits [embryo oil content, embryo oil concentration, EEWR, embryo volume, embryo width, embryo length, and embryo width-to-length ratio (EWLR)]. A total of 58 QTL were identified for kernel oil content and its component traits in 26 genomic regions across all chromosomes. Eight main-effect QTL were identified for kernel oil content, embryo oil content, embryo oil concentration, EEWR, embryo weight, and EWLR, each accounting for over 10 % of the phenotypic variation in six genomic regions. Over 90 % of QTL identified for kernel oil content co-localized with QTL for component traits, validating their molecular contribution to kernel oil content. On chromosome 1, the QTL that had the largest effect on kernel oil content ( qKO1- 1) was associated with embryo width; on chromosome 9, the QTL for kernel oil content ( qKO9) was related to EEWR ( qEEWR9). Embryo oil concentration and embryo width were identified as the most important component traits controlling the second largest QTL for kernel oil content on chromosome 6 ( qKO6) and a minor QTL for kernel oil content on chromosome 5 ( qKO5- 2), respectively. The dissection of kernel oil QTL will facilitate future cloning and/or functional validation of kernel oil content, and help to elucidate the genetic basis of kernel oil content in maize. [ABSTRACT FROM AUTHOR]

The organization of maize ( Zea mays L.) germplasm into genetically divergent heterotic groups is the foundation of a successful hybrid maize breeding program. In this study, 94 CIMMYT maize lines (CMLs) and 54 United States germplasm enhancement of maize (GEM) lines were assembled and characterized using 1,266 single nucleotide polymorphisms (SNPs) with high quality. Based on principal component analysis (PCA), the GEM lines and CMLs were clearly separated. In the GEM lines, there were two groups classified by PCA corresponding to the heterotic groups 'stiff stalk' and 'non-stiff stalk'. CMLs did not form obvious subgroups by PCA. The allelic frequency of each SNP differed in GEM lines and CMLs. In total, 3.6% alleles (46/1,266) of CMLs are absent in GEM lines and 4.4% alleles (56/1,266) of GEM lines are absent in CMLs. The performance of F1 plants ( n = 654) produced by crossing between different groups based on pedigree information was evaluated at the breeding nurseries of two CIMMYT stations. Genomic estimated phenotypic values of plant height and days to anthesis for a testing set of 45 F1 crosses were predicted based on the training data of 600 F1 crosses using a best linear unbiased prediction method. The prediction accuracy benefitted from the adoption of the markers associated with quantitative trait loci for both traits; however, it does not necessarily increase with an increase in marker density. It is suggested that genomic selection combined with association analysis could improve prediction efficiency and reduce cost. For hybrid maize breeding in the tropics, incorporating GEM lines which have unique alleles and clear heterotic patterns into tropically adapted lines could be beneficial for enhancing heterosis in grain yields. [ABSTRACT FROM AUTHOR]

The gene encoding acyl-CoA:diacylglycerol acyltransferase ( DGAT1- 2) is a key quantitative trait locus that controls oil content and oleic acid composition in maize kernels. Here we re-sequenced the DGAT1- 2 region responsible for oil variation in a maize landrace set and in 155 inbred lines (35 high-oil and 120 normal lines). The high-oil DGAT1- 2 allele was present in most Northern Flint and Southern Dent populations but was absent in five of eight Corn Belt Dent open-pollinated populations and in most of the earlier inbred lines. Loss of the high-oil DGAT1- 2 allele possibly resulted from genetic drift in the early twentieth century when a few Corn Belt Dent populations were selected for the development of high-grain-yield inbred lines. Association analysis detected significant effects of two PCR-based functional markers (HO06 and DGAT04; developed based on DGAT1- 2 polymorphisms) on kernel oil content and oleic acid composition using the 155 inbred lines. Zheng58 and Chang7-2, the parent inbred lines of elite hybrid Zhengdan958, were used to transfer the favorable allele from the high-oil line By804 using marker-assisted backcrossing with the two functional markers. In BC5F2:3 populations, oil content of the three genotypes (−/−, +/−, and +/+) was, respectively, 3.37, 4.20, and 4.61% (Zheng58 recipient line) and 4.14, 4.67, and 5.25% (Chang7-2 recipient line). Oil content of homozygous kernels containing the high-oil DGAT1- 2 allele increased by 27-37% compared with recurrent parents. Hence, these functional markers can be used to re-introduce the high-oil DGAT1- 2 allele into modern inbred lines for increased oil content through marker-assisted backcrossing. [ABSTRACT FROM AUTHOR]

Association mapping is a powerful approach for exploring the molecular basis of phenotypic variations in plants. A maize ( Zea mays L.) association mapping panel including 527 inbred lines with tropical, subtropical and temperate backgrounds, representing the global maize diversity, was genotyped using 1,536 single nucleotide polymorphisms (SNPs). In total, 926 SNPs with minor allele frequencies of ≥0.1 were used to estimate the pattern of genetic diversity and relatedness among individuals. The analysis revealed broad phenotypic diversity and complex genetic relatedness in the maize panel. Two different Bayesian approaches identified three specific subpopulations, which were then reconfirmed by principal component analysis (PCA) and tree-based analyses. Marker-trait associations were performed to assess the suitability of different models for false-positive correction by population structure (Q matrix/PCA) and familial kinship (K matrix) alone or in combination in this panel. The K, Q + K and PCA + K models could reduce the false positives, and the Q + K model performed slightly better for flowering time, ear height and ear diameter. Our findings suggest that this maize panel is suitable for association mapping in order to understand the relationship between genotypic and phenotypic variations for agriculturally complex quantitative traits using optimal statistical methods. [ABSTRACT FROM AUTHOR]

Advances in high-throughput SNP genotyping and genome sequencing technologies have enabled genome-wide association mapping in dissecting the genetic basis of complex quantitative traits. In this study, 82 SSRs and 884 SNPs with minor allele frequencies (MAF) over 0.20 were used to compare their ability to assess population structure, principal component analysis (PCA) and relative kinship in a maize association panel consisting of 154 inbred lines. Compared to SNPs, SSRs provided more information on genetic diversity. The expected heterozygosity (He) of SSRs and SNPs averaged 0.65 and 0.44, and the polymorphic information content of these two markers was 0.61 and 0.34 in this panel, respectively. Additionally, SSRs performed better at clustering all lines into groups using STRUCTURE and PCA approaches, and estimating relative kinship. For both marker systems, the same clusters were observed based on PCA and the first two eigenvectors accounted for similar percentage of genetic variations in this panel. The correlation coefficients of each eigenvector from SSRs and SNPs decreased sharply when the eigenvector varied from 1 to 3, but kept around 0 when the eigenvector were over 3. The kinship estimates based on SSRs and SNPs were moderately correlated ( r = 0.69). All these results suggest that SSR markers with moderate density are more informative than SNPs for assessing genetic relatedness in maize association mapping panels. [ABSTRACT FROM AUTHOR]

Lipids play an important role in plants due to their abundance and their extensive participation in many metabolic processes. Genes involved in lipid metabolism have been extensively studied in Arabidopsis and other plant species. In this study, a total of 1003 maize lipid-related genes were cloned and annotated, including 42 genes with experimental validation, 732 genes with full-length cDNA and protein sequences in public databases and 229 newly cloned genes. Ninety-seven maize lipid-related genes with tissue-preferential expression were discovered by in silico gene expression profiling based on 1984483 maize Expressed Sequence Tags collected from 182 cDNA libraries. Meanwhile, 70 QTL clusters for maize kernel oil were identified, covering 34.5% of the maize genome. Fifty-nine (84%) QTL clusters co-located with at least one lipid-related gene, and the total number of these genes amounted to 147. Interestingly, thirteen genes with kernel-preferential expression profiles fell within QTL clusters for maize kernel oil content. All the maize lipid-related genes identified here may provide good targets for maize kernel oil QTL cloning and thus help us to better understand the molecular mechanism of maize kernel oil accumulation. [ABSTRACT FROM AUTHOR]

Transposable elements (TEs)-mediated gene sequence movement is thought to play an important role in genome expansion and origin of genes with novel functions. In this study, a gene, HGGT, involved in vitamin E synthesis was used in a case study to discover and characterize transposons carrying gene fragments in maize. A total of 69 transposons that are distributed across the 10 chromosomes and have an average length of 3689 bp were identified from the maize sequence database by using the BLAST search algorithm. Three of these carry gene fragments from the progenitor HGGT gene, while the rest (66) contain gene fragments from other cellular genes. Nine of the 69 transposons conthin fragments derived from two locations in the genome. By querying the maize Expressed Sequence Tag (EST) database, we found that at least thirteen out of the 69 TEs had corresponding transcripts. More interestingly, two transposons that carry gene fragments from two different chromosomal loci, could be expressed as chimeric transcripts. [ABSTRACT FROM AUTHOR]

A set of recombinant inbred lines (RIL) derived from Yuyu22, an elite hybrid widespread in China, was used to construct an immortalized F2 (IF2) population comprising 441 different crosses. Genetic linkage maps were constructed containing 10 linkages groups with 263 simple sequence repeat (SSR) molecular markers. Twelve and ten quantitative trait loci (QTL) were detected for plant height in the IF2 and RIL populations respectively, using the composite interval mapping method, and six same QTL were identified in the two populations. In addition, ten unique heterotic loci (HL) located on seven different chromosomes were revealed for plant height using the mid-parent heterosis as the input data. These HL explained 1.26%–8.41% of the genotypic variance in plant height heterosis and most expressed overdominant effects. Only three QTL and HL were located in the same chromosomal region, it implied that plant height and its heterosis might be controlled by two types of genetic mechanisms. [ABSTRACT FROM AUTHOR]

By adding thirty-one markers in the previous linkage map, a new genetic linkage map containing 205 markers was constructed, spanning a total of 2305.4 cM with an average interval of 11.2 cM. The genotypic errors in the whole genome were detected by the statistical method and removed manually. The precision of the linkage map was improved significantly. Main and epistatic QTL were detected by R/qtl, and main QTL were confirmed and refined by multiple interval mapping (MIM). Finally, MIM detected seven QTL for rows number, and five QTL for each grain yield, kernels per row and 100-kernel weight. The contribution to genetic variations of QTL varied from 35.3% for grain yield to 61.5% for rows number. Only kernels per row exhibited significant epistatic interactions between QTL. Twenty-four epistatic QTL were detected which distributed on almost all the ten chromosomes. About two-third epistatic QTL were observed between main QTL and another locus, which had no significant effects. These results indicate rather clearly that there are a number of QTL affecting trait expressions, not directly but indirectly through interactions with other loci. Thus, epistatic QTL effects may play a crucial role, if not more important than main QTL effects, in the genetic variation for the measured traits in present study. [ABSTRACT FROM AUTHOR]

Studies plant height in maize, an important agronomic and model trait that is suitable for studying developmental biology. Use of data from locations in Wuhan and Xiangfan and a molecular linkage map covering 10 chromosomes; Analysis of QTLs affecting plant height at five different developmental stages by the combination of composite interval mapping and the conditional analysis method; Number of QTLs located at different regions of five chromosomes; Finding that there were different QTL effect values on plant height at various developmental stages; Indication that three QTLs were detected at all five stages; Suggestion that QTL expression varied at different stages; Detection of seven conditional QTLs for plant height; Indication that QTLs for plant height are expressed in different time-space; Implication for marker assistant selection when conducted for quantitative traits.

Chromatin loops connect regulatory elements to their target genes. They serve as bridges between transcriptional regulation and phenotypic variation in mammals. However, spatial organization of regulatory elements and its impact on gene expression in plants remain unclear. Here, we characterize epigenetic features of active promoter proximal regions and candidate distal regulatory elements to construct high-resolution chromatin interaction maps for maize via long-read chromatin interaction analysis by paired-end tag sequencing (ChIA-PET). The maps indicate that chromatin loops are formed between regulatory elements, and that gene pairs between promoter proximal regions tend to be co-expressed. The maps also demonstrated the topological basis of quantitative trait loci which influence gene expression and phenotype. Many promoter proximal regions are involved in chromatin loops with distal regulatory elements, which regulate important agronomic traits. Collectively, these maps provide a high-resolution view of 3D maize genome architecture, and its role in gene expression and phenotypic variation. Spatial organization of regulatory elements and its impact on gene expression in plants remain unclear. Here, the authors construct maize chromatin interaction maps using chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) and show their associations with gene expression and agronomic traits. [ABSTRACT FROM AUTHOR]

Meiotic crossover (CO) plays a key role in producing gametophytes and generating genetic variation. The patterns of CO production differ inter- and intra-species, as well as between sexes. However, sex-specific patterns of CO production have not been accurately profiled independently of genetic backgrounds in maize. Here, we develop a method to isolate single female gametophyte for genomes sequencing in maize. We show that more COs are observed in male (19.3 per microspore) than in female (12.4 per embryo sac). Based on Beam-Film model, the more designated class I and II COs are identified in male than in female. In addition, CO maturation inefficiency (CMI) is detected in some genetic backgrounds, suggesting that maize may be an ideal model for dissecting CMI. This research provides insights toward understanding the molecular mechanism of CO production between sexes and may help to improve maize breeding efficiency through paternal selection. Meiotic crossover (CO) landscape differs inter- and intra-species, as well as between sexes. Here, the authors show that male meiosis produces more COs than female in maize and detect CO maturation inefficiency in some genetic backgrounds, which may help to improve breeding efficiency. [ABSTRACT FROM AUTHOR]