Genetic analysis and molecular mapping of two dominant complementary genes determining resistance to sugarcane mosaic virus in maize

Wu, Jianyu; Ding, Junqiang; Du, Yanxiu; Xu, Y B; Zhang, Xue-cai

doi:10.1007/s10681-007-9384-8

Cited by 31 publications

(23 citation statements)

References 26 publications

(22 reference statements)

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“…Moreover, the QTL on chromosome 9 in our study (named Qgr-hn-2) were quite near to marker Umc1893 (bin9.02), with only 0 cM of mapping distance between them. This suggested that Umc1893 could probably be co-segregated with the gene controlling GR within the QTL; thus, the marker could be considered in markerassisted selection breeding, similar to previous reports (Wu et al, 2007;Guo et al, 2008). The other two QTLs (Qgr-hn-1 and Qgr-ln-1) were far away from their linked markers, up to 8.5 and 10 cM, respectively.…”

Section: Discussionsupporting

confidence: 84%

Identification of the quantitative trait loci for grain rate in maize

Liu¹,

He²,

Zheng³

et al. 2010

Afr. J. Biotechnol.

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Grain rate (GR) is a very important trait in maize (Zea mays L.) breeding program related to yield. To realize its genetic basis, a recombinant inbred line (RIL) population and different nitrogen (N) regimes were used to map the quantitative trait loci (QTLs) for GR in maize. As a result, two QTLs were identified under high N regime and could explain a total of 14.84% of phenotypic variance. Due to additive effect, the QTL on chromosome 6 could decrease 0.029 of GR, while the QTL on chromosome 9 could increase 0.0203 of GR. Under low N regime, one QTL was mapped on chromosome 6 and could account for 9.52% of phenotypic variance, and owning to additive effect, the QTL could make GR decrease by 0.0234. The result in comparison with previous studies showed that the three QTLs in this present study were new quantitative loci associated with GR in maize. These results were beneficial for understanding the genetic basis of GR in maize.

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Section: Discussionsupporting

confidence: 84%

Identification of the quantitative trait loci for grain rate in maize

Liu¹,

He²,

Zheng³

et al. 2010

Afr. J. Biotechnol.

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“…Mosaic virus is particularly prominent on maize fields and causes great loss in grain and forage yields (Fuchs & Gruntzig ; Wu et al . ). Two major resistance QTLs for this disease are known, scmv1 on chromosome 6 and scmv2 on chromosome 3 (Xia et al .…”

Section: Discussionmentioning

confidence: 97%

Signatures of local adaptation in lowland and highland teosintes from whole‐genome sequencing of pooled samples

et al. 2017

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Spatially varying selection triggers differential adaptation of local populations. Here, we mined the determinants of local adaptation at the genomewide scale in the two closest maize wild relatives, the teosintes Zea mays ssp parviglumis and ssp. mexicana. We sequenced 120 individuals from six populations: two lowland, two intermediate and two highland populations sampled along two altitudinal gradients. We detected 8 479 581 single nucleotide polymorphisms (SNPs) covered in the six populations with an average sequencing depth per site per population ranging from 17.0× to 32.2×. Population diversity varied from 0.10 to 0.15, and linkage disequilibrium decayed very rapidly. We combined two differentiation-based methods, and correlation of allele frequencies with environmental variables to detect outlier SNPs. Outlier SNPs displayed significant clustering. From clusters, we identified 47 candidate regions. We further modified a haplotype-based method to incorporate genotype uncertainties in haplotype calling, and applied it to candidate regions. We retrieved evidence for selection at the haplotype level in 53% of our candidate regions, and in 70% of the cases the same haplotype was selected in the two lowland or the two highland populations. We recovered a candidate region located within a previously characterized inversion on chromosome 1. We found evidence of a soft sweep at a locus involved in leaf macrohair variation. Finally, our results revealed frequent colocalization between our candidate regions and loci involved in the variation of traits associated with plant-soil interactions such as root morphology, aluminium and low phosphorus tolerance. Soil therefore appears to be a major driver of local adaptation in teosintes.

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“…In this work, an immortal F 9 RIL population consisting of 239 RILs was constructed, and 100 SSR markers were selected for QTL mapping, which could improve the reliability of the experiments. By comparison of Qscmv6 with other QTLs or genes identified in other resistant maize inbred lines against SCMV or MDMV (Ignjatović et al 1995;Xu et al 1999;Duble et al 2003;Chen et al 2005;Wu et al 2007) (Table 3), it was found that the previous mapping populations were focused on F 2 or BC. The number and location of identified QTLs or genes were different in different reports, but, the common in these reports was at least one QTL or gene located between bin6.00 and bin6.01 on chromosome 6, which could confirm the facticity and reliability of our experimental results.…”

Section: Discussionmentioning

confidence: 99%