scholarly journals Genetic Relatedness Among Co-Foundresses of Two Desert Ants, Veromessor Pergandei and Acromyrmex Versicolor (Hymenoptera: Formicidae)

1988 ◽  
Vol 95 (3-4) ◽  
pp. 191-201 ◽  
Author(s):  
Robert H. Hagen ◽  
Deborah R. Smith ◽  
Steven W. Rissing
Keyword(s):  
Genetic Relatedness ◽  
Desert Ants ◽  
Veromessor Pergandei ◽  
Acromyrmex Versicolor

scholarly journals Colony Founding Behavior of Some Desert Ants: Geographic Variation in Metrosis

2000 ◽  
Vol 103 (1-2) ◽  
pp. 95-101 ◽  
Author(s):  
Steven W. Rissing ◽  
Robert A. Johnson ◽  
John W. Martin
Keyword(s):  
Geographic Variation ◽  
Comparative Studies ◽  
Colony Founding ◽  
Colony Foundation ◽  
Desert Ants ◽  
Adaptive Value ◽  
Acromyrmex Versicolor

The antsPogonomyrmex catifornicusandPheidole tucsonicadisplay cooperative colony foundation with co-foundresses forming associations without respect to relatedness. Geographic variation in method of colony foundation [cooperative (pleometrosis) versus non-cooperative (haplometrosis)] occurs inP. californicus, Acromyrmex versicolor, Myrmecocystus mimicus and Messor pergandei.Such variation in colony founding behavior strongly suggests that comparative studies of the adaptive value of cooperative colony founding will be extremely rewarding.

An Outbreak of ESBL-producing Klebsiella pneumoniae in an Iranian Referral Hospital: Epidemiology and Molecular Typing

2019 ◽  
Vol 19 (1) ◽  
pp. 46-54 ◽  
Author(s):  
Shima Mahmoudi ◽  
Babak Pourakbari ◽  
Aliakbar Rahbarimanesh ◽  
Mohammad Reza Abdosalehi ◽  
Keyghobad Ghadiri ◽  
...  
Keyword(s):  
Klebsiella Pneumoniae ◽  
Nosocomial Infections ◽  
Molecular Typing ◽  
Genetic Relatedness ◽  
Referral Hospital ◽  
Limited Information ◽  
Hospital Epidemiology ◽  
Rapd Pcr ◽  
Published Report ◽  
Random Amplification

Introduction: Klebsiella pneumoniae is a common cause of nosocomial infections; however, there is limited information in Iran regarding nosocomial outbreaks due to extended-spectrum β–lactamase (ESBL) producing K pneumoniae strains, particularly using molecular methods. The present study focused on the molecular mechanism of ESBL resistance and genetic relatedness in K. pneumoniae isolates causing nosocomial infections in an Iranian referral hospital. Material and Methods: This study evaluated the antimicrobial resistance and molecular epidemiology of K. pneumoniae causing nosocomial infections in children between October 2013 and March 2014. The ESBL detection was carried out for all the isolates by the CLSI method and PCR was carried out for the detection of the blaSHV, blaTEM, and blaCTX-M genes among ESBL-producing K. pneumonia. Molecular typing of the K. pneumoniae was performed using random amplification of polymorphic DNA-polymerase chain reaction (RAPD-PCR). Results: A total of 30 isolates of K. pneumoniae were used for epidemiological analysis. High rates of resistance to cefotaxime (n=29, 97%), cefazolin (n=29, 97%), cefepime (n=25, 83%) and gentamicin (n=23, 77%) were observed. A total of 29 strains (97%) produced ESBLs. The frequency of blaSHV, blaCTX-M and blaTEM genes among these isolates was 83% (n=25), 70% (n=21) and 57% (n=17), respectively. Surprisingly 11 isolated (37%) carried blaSHV, blaCTX-M and blaTEM genes simultaneously. Moreover, the concurrent presence of “blaSHV and blaCTX-M” and “blaSHV and blaTEM” was seen in 8 (27%) and 4 (13%) isolates, respectively. RAPDPCR analyses revealed that K. pneumoniae isolates belonged to 2 RAPD-PCR types among which one cluster counted for 28 isolates. Conclusion: To our knowledge, this is the first published report of a nosocomial outbreak of ESBL-producing K. pneumoniae in children in Iran. Although the epidemiology of nosocomial infections with ESBL-producing organisms has not yet been explored in depth in Iran, our findings suggest that ESBL-producing organisms are already an established public health threat in our country.

scholarly journals Early prediction of biomass in hybrid rye based on hyperspectral data surpasses genomic predictability in less-related breeding material

2021 ◽  
Vol 134 (5) ◽  
pp. 1409-1422
Author(s):  
Rodrigo José Galán ◽  
Angela-Maria Bernal-Vasquez ◽  
Christian Jebsen ◽  
Hans-Peter Piepho ◽  
Patrick Thorwarth ◽  
...  
Keyword(s):  
Dry Matter ◽  
Genetic Relatedness ◽  
Snp Array ◽  
Matter Content ◽  
Hyperspectral Data ◽  
Winter Rye ◽  
Dry Matter Content ◽  
Early Prediction ◽  
Bivariate Model ◽  
Fresh Matter

Abstract Key message Hyperspectral data is a promising complement to genomic data to predict biomass under scenarios of low genetic relatedness. Sufficient environmental connectivity between data used for model training and validation is required. Abstract The demand for sustainable sources of biomass is increasing worldwide. The early prediction of biomass via indirect selection of dry matter yield (DMY) based on hyperspectral and/or genomic prediction is crucial to affordably untap the potential of winter rye (Secale cereale L.) as a dual-purpose crop. However, this estimation involves multiple genetic backgrounds and genetic relatedness is a crucial factor in genomic selection (GS). To assess the prospect of prediction using reflectance data as a suitable complement to GS for biomass breeding, the influence of trait heritability ($$H^{2}$$ H 2 ) and genetic relatedness were compared. Models were based on genomic (GBLUP) and hyperspectral reflectance-derived (HBLUP) relationship matrices to predict DMY and other biomass-related traits such as dry matter content (DMC) and fresh matter yield (FMY). For this, 270 elite rye lines from nine interconnected bi-parental families were genotyped using a 10 k-SNP array and phenotyped as testcrosses at four locations in two years (eight environments). From 400 discrete narrow bands (410 nm–993 nm) collected by an uncrewed aerial vehicle (UAV) on two dates in each environment, 32 hyperspectral bands previously selected by Lasso were incorporated into a prediction model. HBLUP showed higher prediction abilities (0.41 – 0.61) than GBLUP (0.14 – 0.28) under a decreased genetic relationship, especially for mid-heritable traits (FMY and DMY), suggesting that HBLUP is much less affected by relatedness and $$H^{2}$$ H 2 . However, the predictive power of both models was largely affected by environmental variances. Prediction abilities for DMY were further enhanced (up to 20%) by integrating both matrices and plant height into a bivariate model. Thus, data derived from high-throughput phenotyping emerges as a suitable strategy to efficiently leverage selection gains in biomass rye breeding; however, sufficient environmental connectivity is needed.

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