Mapping QTL for Grain Yield and Plant Traits in a Tropical Maize Population

Lima, Milena; Souza, Cláudio Lopes de; Bento, Dyeme Antonio Vieira; Souza, Anete Pereira de; Carlini-Garcia, L. A.

doi:10.1007/s11032-005-5679-4

Cited by 92 publications

(74 citation statements)

References 39 publications

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“…Flowering-related traits of maize have been extensively studied in China, and in other countries, using different populations and methods (Wang et al, 2010;Yang, 2012;Zheng et al, 2011Zheng et al, , 2012Wei et al, 2014). F 2:3 populations and recombinant inbred lines (RILs) are useful in the study of flowering traits, plant types, yield, and resistance (Lima et al, 2006;Salgado et al, 2008;Ku et al, 2012;Yang et al, 2014a). Genetic mapping studies on flowering traits of maize are influenced by the genetic background, environment, population, marker numbers, and mapping methods used (Austin and Lee, 1996;Li et al, 2007Li et al, , 2011.…”

Section: Introductionmentioning

confidence: 99%

Comparative quantitative trait locus mapping of maize flowering-related traits in an F2:3 and recombinant inbred line population

et al. 2016

Genet. Mol. Res.

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ABSTRACT. Flowering-related traits in maize are affected by complex factors and are important for the improvement of cropping systems in the maize zone. Quantitative trait loci (QTLs) detected using different materials and methods usually vary. In the present study, 266 maize (Zea mays) F 2:3 families and 301 recombinant inbred lines (RIL) derived from a cross between 08-641 (founding parent from southeast China) and Ye478 (founding parent from China) were evaluated for four flowering-related traits, including days to tasseling (DTT), days to pollen shedding (DPS), days to silking (DTS), and anthesis-silking interval. Sixty-six QTLs controlling the target traits were detected in the F 2:3 and RIL populations via single environment analysis and joint analysis across all environments (JAAE). The QTLs explained 0.8-13.47% of the phenotypic variation, with 12 QTLs explaining more than 10%. The results of meta-QTL (MQTL) analysis indicated that 41 QTLs could be integrated into 14 MQTLs. One MQTL included 2.9 QTLs, ranging from two to ten QTLs for one to three traits. QTLs, including MQTL1-1 and MQTL9-1, were detected across the F 2:3 and RIL populations via SAE and JAAE. Among the MQTLs, nine QTLs were integrated into MQTL9-1 and affected DTT, DPS, and DTS, with the favored allele being derived from 08-641. MQTL3-2 showed high phenotypic variation and was suitable for fine mapping to determine the genetic mechanisms of flowering. MQTL3-2 could be applied to improve inbred lines using marker-assisted selection.

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Section: Introductionmentioning

confidence: 99%

Comparative quantitative trait locus mapping of maize flowering-related traits in an F2:3 and recombinant inbred line population

et al. 2016

Genet. Mol. Res.

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“…In addition, the power of association analysis to identify significant marker-trait associations for grain yield decreased in drought conditions as different gene networks in different genotypes were involved in physiological processes that lead to adaptation to drought stress (Maccaferri et al, 2011). Lima et al (2006) found a small number of QTLs mapped in the same genomic regions for grain yield and correlated traits, suggesting that this could be because the majority of the segregating QTLs in the population remained unmapped.…”

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confidence: 99%

“…Marković et al (2008) identified a chromosome region involved in ASI expression close to bnlg1525. The marker umc1025 was used to identify a QTL with an additive effect on grain yield explaining 3% of its total phenotypic variation in the study of Lima et al (2006) and a QTL with a dominant gene action explaining 10.4% of grain yield variation as reported by Li et al (2010). Liu et al (2008) mapped a QTL near the marker bnlg238 with a partial dominant effect and 10% of the explained phenotypic variation of grain yield under low nitrogen stress.…”

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confidence: 99%

“…Marković et al (2008) observed that some of maize families had short ASI in one location, while in the other ASI was considerable longer. Similarly, the expression of the QTL mapped for grain yield, plant and ear height and number of ears per plant changed across environments, resulting the differential performance of the maize families (Lima et al, 2006). Furthermore, several studies suggested that different loci and combinations of their alleles were expressed under different intensity of drought (Messmer et al, 2009;.…”

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confidence: 99%

“…Undoubtedly, the large number of QTLs that control complex traits, such as yield, under drought conditions, the high proportion of QTLs that interact with environments and their epistatic effects could make the routine use of molecular markers in identifying and developing drought tolerant genotypes a rather challenging task. The high environmental variability could be addressed by identifying sets of environments with ideally low or non-crossover GEI and QTLs that are specific for and stable in those environments (Lima et al, 2006). This ideal scenario is not always achievable as the lack of repeatability of the GEI patterns over years and unpredictable crossover interaction are common in maize growing regions (Stojaković et al, 2015).…”

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Agronomic and molecular evaluation of maize inbred lines for drought tolerance

Mikić

Zorić

Stanisavljević

et al. 2017

Span. j. agric. res.

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Drought is a severe threat to maize yield stability in Serbia and other temperate Southeast European countries occurring occasionally but with significant yield losses. The development of resilient genotypes that perform well under drought is one of the main focuses of maize breeding programmes. To test the tolerance of newly developed elite maize inbred lines to drought stress, field trials for grain yield performance and anthesis silk interval (ASI) were set in drought stressed environments in 2011 and 2012. Inbred lines performing well under drought, clustered into a group with short ASI and a smaller group with long ASI, were considered as a potential source for tolerance. The former contained inbreds from different heterotic groups and with a proportion of local germplasm. The latter consisted of genotypes with mixed exotic and Lancaster germplasm, which performed better in more drought-affected environments. Three inbreds were selected for their potential drought tolerance, showing an above-average yield and small ASI in all environments. Association analysis indicated significant correlations between ASI and grain yield and three microsatellites (bnlg1525, bnlg238 and umc1025). Eight alleles were selected for their favourable concurrent effect on yield increase and ASI decrease. The proportion of phenotypic variation explained by the markers varied across environments from 5.7% to 22.4% and from 4.6% to 8.1% for ASI and yield, respectively. The alleles with strongest effect on performance of particular genotypes and their interactions in specific environments were identified by the mean of partial least square interactions analysis indicating potential suitability of the makers for tolerant genotype selection.

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Genomics of Tropical Maize, a Staple Food and Feed across the World

Crouch

Genomics of Tropical Crop Plants

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Mapping QTL for Grain Yield and Plant Traits in a Tropical Maize Population

Cited by 92 publications

References 39 publications

Comparative quantitative trait locus mapping of maize flowering-related traits in an F2:3 and recombinant inbred line population

Comparative quantitative trait locus mapping of maize flowering-related traits in an F2:3 and recombinant inbred line population

Agronomic and molecular evaluation of maize inbred lines for drought tolerance

Genomics of Tropical Maize, a Staple Food and Feed across the World

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