Comparison between abdominal fat measured by CT and anthropometric indices as prediction factors for mortality and morbidity after colorectal surgery.

AIM: This study aims to determine which anthropometric (body mass index (BMI), waist-hip-ratio (WHR) and waist-to-height ratio (WHtR)) and radiological (visceral fat area (VFA) measured by CT scan) measurements of adiposity correlated better with postoperative outcome of colorectal cancer (CRC) surgery. We also assessed which of these measurements best predicted overall survival (OS) and disease-free survival (DFS). METHODS: Data from 90 consecutive Caucasian CRC patients who underwent surgery for colorectal cancer between 2010 and 2011 with a median follow-up of 53.25 months were analysed. The correlations of different adiposity measurements and postoperative outcomes were determined using logistic regression models and multivariate analyses. RESULTS: Higher WHtR (p = 0.007) and VFA (p = 0.01) significantly increased the risk of overall morbidity, especially of Clavien-Dindo III or IV. The WHtR correlated best with VFA (p <0.0001), which is considered the gold standard for measuring visceral fat, whereas BMI (p = 0.15) was not a good predictor of postoperative morbidity. Multivariate analyses showed consistently significant results for postoperative complications for VFA in combination with all of the other variables analysed and for WHtR, confirming that VFA and WHtR were reliable independent prognostic factors of morbidity. VFA had a significant effect on OS (p = 0.012) but did not correlate with DFS (p = 0.51). CONCLUSIONS: Both VFA and WHtR independently provided predictive data for potential postoperative complications after CRC surgery. In case CT scan was used for diagnostic purposes, VFA should be used in routine clinical practice.

Genomic approaches for designing durum wheat ready for climate change with a focus on drought.

Climate change is projected to have a significant impact on temperature and precipitation profiles in the Mediterranean basin. The incidence and severity of drought will become commonplace and this will reduce the productivity of rain-fed crops such as durum wheat. Genetic diversity is the material basis for crop improvement and plant breeding has exploited naturally occurring variation to deliver cultivars with improved resistance to abiotic stresses. The coupling of new genomic tools, technologies, and resources with genetic approaches is essential to underpin wheat breeding through marker-assisted selection and hence mitigate climate change. Improvements in crop performance under abiotic stresses have primarily targeted yield-related traits and it is anticipated that the application of genomic technologies will introduce new target traits for consideration in wheat breeding for resistance to drought. Many traits relating to the plant's response and adaptation to drought are complex and multigenic, and quantitative genetics coupled with genomic technologies have the potential to dissect complex genetic traits and to identify regulatory loci, genes and networks. Full realization of our abilities to manipulate metabolism, transduction pathways, and transcription factors for crop improvement ultimately relies on our basic understanding of the regulation of plant networks at all levels of function.

A genetic linkage map of the Durum x Triticum dicoccoides backcross population based on SSRs and AFLP markers, and QTL analysis for milling traits.

Durum wheat ( Triticum turgidum L. var durum) is mainly produced and consumed in the Mediterranean region; it is used to produce several specific end-products; such as local pasta, couscous and burghul. To study the genetics of grain-milling quality traits, chromosomal locations, and interaction with the environment, a genetic linkage map of durum was constructed and the quantitative trait loci QTLs for the milling-related traits, test weight (TW) and thousand-kernel weight (TKW), were identified. The population constituted 114 recombinant inbred lines derived from the cross: Omrabi 5 /Triticum dicoccoides 600545// Omrabi 5. TW and TKW were analyzed over 18 environments (sites x years). Single-sequence-repeat markers (SSRs), Amplified-fragment-length-polymorphism markers (AFLPs), and seed storage proteins (SSPs) showed a high level of polymorphism (>60%). The map was constructed with 124 SSRs, 149 AFLPs and 6 SSPs; its length covered 2,288.8 cM (8.2 cM/marker). The map showed high synteny with previous wheat maps, and both SSRs and AFLPs mapped evenly across the genome, with more markers in the B genome. However, some rearrangements were observed. For TW, a high genotypic effect was detected and two QTLs with epistasic effect were identified on 7AS and 6BS, explaining 30% of the total variation. The TKW showed a significant transgressive inheritance and five QTLs were identified, explaining 32% of the total variation, out of which 25% was of a genetic nature, and showing QTLxE interaction. The major TKW-QTLs were around the centromere region of 6B. For both traits, Omrabi 5 alleles had a significant positive effect. This population will be used to determine other QTLs of interest, as its parents are likely to harbor different genes for diseases and drought tolerance.

Identification of a microsatellite on chromosome 7B showing a strong linkage with yellow pigment in durum wheat (Triticum turgidum L. var. durum).

The objective of this study is to identify QTLs linked to yellow pigment content in durum wheat. A durum-dicoccoides genetic linkage map was constructed using 124 microsatellites, 149 amplified fragment length polymorphism (AFLPs), and six seed storage proteins (SSP) in a population of 114 recombinant inbred lines (F8). The population has been obtained from a cross between a durum cultivar Omrabi5 and Triticum dicoccoides600545 and backcrossed to Omrabi5. The map consists of 14-durum chromosomes plus an unknown group; and shows a good synteny to the previously published wheat maps. Yellow pigment was measured in the population in three different locations during 3 seasons. Analysis of QTLs was based on simple and simplified composite interval mapping (SIM and sCIM). Three QTLs for yellow pigment were detected on the chromosomal group 7 (7AL and 7BL telomeres) explaining 62% of the total variation. On 7BL, a major microsatellite (Xgwm344) explained by itself 53%, whereas on 7AL, the other two QTLs have contributed 13 and 6%. All determined QTLs showed a strong genetic effect and a weak QTL x E effect. The QTLs effect was consistent across all environments and showed a large effect. Consequently, promising QTLs will be used in the marker assisted breeding program to enhance the selection efficiency for yellow pigment.

Genetic variation among populations of the Hessian fly Mayetiola destructor (Diptera: Cecidomyiidae) in Morocco and Syria.

The RAPD-PCR technique was used to study genetic variation within and among geographical populations of the Hessian fly, Mayetiola destructor (Say), from Morocco and Syria, associated with the fly's ability to overcome resistance in three wheat cultivars containing H5, H13 and H22 resistance genes. Variation was detected both for the level of susceptibility of the cultivars and RAPD profiles of M. destructor populations. By the use of RAPD-PCR, high genetic variability was detected among individuals and populations of M. destructor within and between areas separated geographically. The DNA fingerprints of populations of M. destructor were area-specific with Nei's measures of genetic distance ranging from 0.156 (between Abda and Beni Mellal, Morocco) to 1.977 (between Marchouch, Morocco and Lattakia, Syria). Cluster analysis of the genetic distances among the populations, identified the Syrian population as an outlier. A highly significant correlation (r = 0.81) observed between the genetic and geographic distances among the populations, provided genetic support for dispersal of the fly from its presumed origin in West Asia to Morocco.

Use of AMMI and linear regression models to analyze genotype-environment interaction in durum wheat.

The joint durum wheat (Triticum turgidum L var 'durum') breeding program of the International Maize and Wheat Improvement Center (CIMMYT) and the International Center for Agricultural Research in the Dry Areas (ICARDA) for the Mediterranean region employs extensive multilocation testing. Multilocation testing produces significant genotype-environment (GE) interaction that reduces the accuracy for estimating yield and selecting appropriate germ plasm. The sum of squares (SS) of GE interaction was partitioned by linear regression techniques into joint, genotypic, and environmental regressions, and by Additive Main effects and the Multiplicative Interactions (AMMI) model into five significant Interaction Principal Component Axes (IPCA). The AMMI model was more effective in partitioning the interaction SS than the linear regression technique. The SS contained in the AMMI model was 6 times higher than the SS for all three regressions. Postdictive assessment recommended the use of the first five IPCA axes, while predictive assessment AMMI1 (main effects plus IPCA1). After elimination of random variation, AMMI1 estimates for genotypic yields within sites were more precise than unadjusted means. This increased precision was equivalent to increasing the number of replications by a factor of 3.7.