QTLs Associated with Resistance to Soybean Cyst Nematode in Soybean: Meta‐Analysis of QTL Locations

Abstract

Soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) is the most important pest of soybean [Glycine max (L.) Merr.] in the world. A total of 17 quantitative trait locus (QTL) mapping papers and 62 marker–QTL associations have been reported for resistance to soybean cyst nematode in soybean. Conflicting results often occurred. The objectives of this study were to: (i) evaluate evidence for reported marker–QTL associations for resistance to SCN in soybean and (ii) extract relatively reliable and useful information from the reported marker–QTL associations in soybean. A meta‐analysis was conducted for QTL locations by comparing the 95% confidence intervals of the reported QTLs. QTLs for different races or different studies were classified into one cluster if their confidence intervals had a region in common. The QTLs of the same cluster may have a shared locus. QTLs for different races or different studies were classified into different clusters if their confidence regions had no region in common and were ≥ 20 cM away from each other. Different clusters may represent different loci. Reported SCN resistant QTLs were classified into three categories: suggestive, significant, and confirmed. Confirmed QTLs are credible and can be candidates for fine mapping and gene cloning. QTLs on linkage groups (LGs) G, A2, B1, E, and J were classified as confirmed. Two clusters of QTLs were identified on LG G. One of them is rhg1 One cluster of QTLs was identified near the end of LG B1, but one QTL may exist around the middle of LG B1. One cluster of QTLs was identified on LGs A2, E, and J, respectively. QTLs on LGs B2, C1, C2, D1a, D2, L, M, and N were classified into suggestive or significant. Confirmation studies are needed to lend credibility for these QTLs. A relationship between soybean QTLs and SCN races is discussed.

Rice Root Genetic Architecture: Meta-analysis from a Drought QTL Database

“…In some papers, the confidence interval was computed using a support interval that was either LODmax-1 or LODmax-2, but in most papers, the confidence interval was not given. To homogenize the data and estimate missing confidence intervals, a simpler solution was to use the empirical formula proposed by Darvasi and Soller (1997) for F 2 and BC and extended by Guo et al (2006) to other population types. For a BC, an F 2 or a DH population, the QTL confidence interval at the 95% level is 530/Nr 2 , where N is the population size and r 2 is the proportion of the total variance explained by the QTL.…”

“…Software packages based on this methodology are available such as BioMercator (Arcade et al 2004) and Meta-QTL (Veyrieras et al 2007), a new software that removes some of the limitations of BioMercator in the number of QTLs it can handle at once. Meta-QTL analyses for flowering time in maize ), resistance to a nematode in soybean (Guo et al 2006), earliness in bread wheat (Hanocq et al 2007), and N uptake in maize (Coque et al 2008) have already shown the usefulness of this approach in determining the number of "true" QTLs underlying the observed QTLs and in positioning consensus QTLs with more precision. In rice, Norton et al (2008) conducted a study on root QTLs, but it was limited to the Azucena × Bala population and only three QTL clusters.…”

Meta-analysis of QTLs Involved in Pre-harvest Sprouting Tolerance and Dormancy in Bread Wheat

“…Meta-QTL analysis has also been successfully conducted in several other crops like maize Truntzler et al, 2010;Hao et al, 2010;Li et al, 2011;Wang et al, 2006;Coque et al, 2008), cotton (Rong et al, 2007), rice (Ballini et al, 2008;Norton et al, 2008;Khowaja et al, 2009), rapeseed (Shi et al, 2009), potato (Danan et al, 2011), cocoa (Lanaud et al, 2009), soybean (Guo et al, 2006;Sun et al, 2012) and apricot (Marandel et al, 2009). …”

Mapeamento de QTLs para caracteres relacionados com a fixação biológica de nitrogênio (FBN) em soja

“…Para avaliar a confiabilidade dos dados sobre mapeamento de QTLs disponíveis, Guo et al (2006) utilizaram as informações descritas acima em um estudo de metaanálise, baseado no intervalo de confiança. QTLs mapeados por diferentes trabalhos e QTLs significativos para diferentes raças de NCS foram agrupados quando seus intervalos de confiança foram sobrepostos e considerados como um mesmo lócus.…”

“…Os QTLs mapeados para diferentes raças (1, 2, 3, 4, 5 e 14) foram agrupados nas mesmas regiões nos grupos A2, G, E, B1 e J. Por exemplo, o QTL do grupo de ligação G (rhg1) foi frequentemente, associado com resistência às raças 1, 2, 3 e 5 e o QTL no grupo A2 (Rhg4) é associado à resistência à raça 3 e, em alguns casos, com a resistência às raças 2, 5 e 14. Wu et al (2009), utilizando uma população grande de RILs (275 F 7:9 Essex x PI 437654), com boa cobertura do genoma (2.406 cM), intervalo médio de 8,7 cM e empregando o método de mapeamento por intervalo composto, identificaram os QTLs de efeito maior e já bem descritos GL A2, B1 e G e o QTL de pequeno efeito para resistência às raças 5 e 14, no grupo de ligação I (Sat_299-Sct_189) classificado como QTL sugestivo por Guo et al (2006). Além de confirmar essas regiões, quatro novos QTLs de pequeno efeito foram mapeados nos grupos H e K para a raça 1, no grupo C1 para a raça 3 e no grupo D1a para as raças 2 e 3.…”