QTL mapping in three rice populations uncovers major genomic regions associated with African rice gall midge resistance

African rice gall midge (AfRGM) is one of the most destructive pests of irrigated and lowland African ecologies. This study aimed to identify the quantitative trait loci (QTL) associated with AfRGM pest incidence and resistance in three independent bi-parental rice populations (ITA306xBW348-1, ITA306xTOG7106 and ITA306xTOS14519), and to conduct meta QTL (mQTL) analysis to explore whether any genomic regions are conserved across different genetic backgrounds. Composite interval mapping (CIM) conducted on the three populations independently uncovered a total of 28 QTLs associated with pest incidence (12) and pest severity (16). The number of QTLs per population associated with AfRGM resistance varied from three in the ITA306xBW348-1 population to eight in the ITA306xTOG7106 population. Each QTL individually explained 1.3 to 34.1% of the phenotypic variance. The major genomic region for AfRGM resistance had a LOD score and R2 of 60.0 and 34.1% respectively, and mapped at 111 cM on chromosome 4 (qAfrGM4) in the ITA306xTOS14519 population. The meta-analysis reduced the number of QTLs from 28 to 17 mQTLs, each explaining 1.3 to 24.5% of phenotypic variance, and narrowed the confidence intervals by 2.2 cM. There was only one minor effect mQTL on chromosome 1 that was common in the TOS14519 and TOG7106 genetic backgrounds; all other mQTLs were background specific. We are currently fine-mapping and validating the major effect genomic region on chromosome 4 (qAfRGM4). This is the first report in mapping the genomic regions associated with the AfRGM resistance, and will be highly useful for rice breeders

Ecological factors influence balancing selection on leaf chemical profiles of a wildflower

Balancing selection is frequently invoked as a mechanism that maintains variation within and across populations. However, there are few examples of balancing selection operating on loci underpinning complex traits, which frequently display high levels of variation. We investigated mechanisms that may maintain variation in a focal polymorphism - leaf chemical profiles of a perennial wildflower (Boechera stricta, Brassicaceae) - explicitly interrogating multiple ecological and genetic processes including spatial variation in selection, antagonistic pleiotropy and frequency-dependent selection. A suite of common garden and greenhouse experiments showed that the alleles underlying variation in chemical profile have contrasting fitness effects across environments, implicating two ecological drivers of selection on chemical profile: herbivory and drought. Phenotype-environment associations and molecular genetic analyses revealed additional evidence of past selection by these drivers. Together, these data are consistent with balancing selection on chemical profile, probably caused by pleiotropic effects of secondary chemical biosynthesis genes on herbivore defence and drought response

Análise de equações preditivas da gordura corporal em jovens atletas de "taekwondo"

Devido à falta de métodos acessíveis válidos para mensurar o percentual de gordura corporal (%G) de taekwondistas adolescentes (TKDA), objetivou-se analisar seis equações antropométricas de predição do %G, em cinco TKDA (12,23 anos ± 1,60), utilizando como método de referência a Densitometria Radiológica de Dupla Energia (DEXA). Os %G estimados pelas equações foram comparados pelo teste t-student, regressão linear e Bland e Altman (B&A) com os obtidos por DEXA. Apenas a equação de Slaughter et al. (1988) foi adequada pelo cálculo amostral, e embora tenha subestimado o %G (em 4,85% ± 0,98), esta apresentou alta correlação (R = 0,935; R² = 0,874 EPE = 1,01) e baixa amplitude nos limites de concordância a 95% (3,84%) pelo B&A em comparação com a DEXA. Portanto, esta equação mostrou-se adequada para a predição do %G em TKDA, desde que seja corrigida pela equação de ajuste [%G (DEXA) = 1,64 + 1,24 • %G (Eq 4)] gerada pela regressão linear.Debido a la falta de métodos accesibles válidos para medir el porcentaje de grasa del cuerpo (%G) de atletas de taekwondo adolescentes (TKDA), destinada a analizar seis ecuaciones antropométricas de predicción de %G, en cinco TKDA (12,23 años ± 1,60 ), utilizando como método de referencia la Densitometría Radiológica de Energía Dual (DEXA). El %G estimado por las ecuaciones fue comparado mediante la prueba t-student, regresión lineal y Bland & Altman (B&A) con los que se obtienen mediante DEXA. Sólo la ecuación del SLAUGHTER et al. (1988) fue adecuada para el cálculo del tamaño de la muestra y, a pesar de que había subestimado la %G (4,85 % ± 0,98 ), este mostró una alta correlación (R = 0,935 ; R2 = 0,874 EPE = 1,01 ) y baja amplitud dentro de los límites de concordancia con el 95% (3,84 %) por B&A en comparación con la DEXA. Por lo tanto, esta ecuación demostró ser adecuada para la predicción de %G en TKDA, desde que corrigida mediante la siguiente ecuación de ajuste [ %G (DEXA) = 1,64 + 1,24 • %G (eq 4)] generada mediante regresión lineal.Due to the lack of valid and accessible tests to measure the body fat percentage (BF%) of adolescent taekwondo athletes (TKDA), this study aimed to analyze six anthropometric equations in the prediction of BF% with the Dual-Energy-x-Ray (DEXA) as referential method for five TKDA (12.23 years ± 1.60). The BF% estimated by the equations were compared with DEXA values using the t-student , linear regression and Bland & Altman (B&A) tests. Only the equation of Slaughter et al. (1988) was adequated by the sample size calculation, and although it subestimated the BF% (in 4.85% ± 0.98), it showed a high correlation (R = 0.935; R² = 0.874 EPE = 1.01) and low amplitude in the limits of agreement at 95% (3.84%) by B&A in comparison to DEXA. However, this equation is adequated to predict the BF% in TKDA, if it's corrected by the adjustement equation [%G (DEXA) = 1,64 + 1,24•%G (Eq 4)] generated by linear regression