Molecular Plant Breeding 2015, Vol.6, No.17, 1
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The contents of each jar were sieved with mesh
(Endecotts Ltd, UK
1
) 90 days after infestation to
separate grains, insects and flour. The flour produced
by the insects was weighed, while the number of
damaged kernels and adult insect progeny were
counted. The grain weight loss was computed by
subtracting the final from the initial weight of the
grain sample and expressed as a percentage (Tefera et
al. 2011). Damaged kernels were separated from the
undamaged based on grain tunnelling and holes. The
percentage of damaged grain was computed. Finally,
the weight of the damaged and undamaged grains was
measured.
3.3 DNA extraction and genotyping
Leaf samples were harvested from 10 healthy plants
per genotype about 3 weeks after sowing at the
Kiboko station. They were sampled in perforated
Ziploc bags, immediately transferred into a Styrofoam
box containing dry ice and transported to the
Biosciences for eastern and central Africa (BecA) hub
in Nairobi. Approximately equal amount of leaf tissue
from each of the 10 plants per genotype was bulked,
cut into pieces, and transferred into 1.2 ml strip tubes
that contained two 4-mm stainless steel grinding balls
(Spex CetriPrep, USA). The leaf samples were
freeze-dried for 4 days using a Labconco freeze dryer
(
) as described in the user’s
manual. The lyophilized leaf samples were ground
into fine powder at 1500 strokes per minute for 2
minutes using GenoGrinder-2000 and genomic DNA
was extracted using a modified version of the
CIMMYT high throughput mini-prep Cetyl Trimethyl
Ammonium Bromide (CTAB) method as described
elsewhere (Semagn 2014). The quality of the isolated
DNA was checked after running aliquots of DNA
samples on a 0.8% agarose gel that contained 0.3
µg/mL Gel-Red-(Biotium). DNA concentration was
measured using NanoDrop-ND-1000 Spectrophotometer,
(Thermo Scientific, Wilmington, DE 19810, USA).
The samples were genotyped with 56 fluorescently-
labelled SSRs (Appendix 1), selected from the list of
markers used for the genetic characterization of
CIMMYT maize inbred lines and OPVs (Warburton et
al., 2002). Polymerase Chain Reaction (PCR), genotyping
and data scoring were done as described in another
paper (Semagn et al., 2014). Both DNA extraction and
genotyping were done at the Biosciences Eastern and
Central Africa (BecA) hub.
3.4 Analysis of phenotypic data
The percentage weight loss, flour weight and grain
damage data were transformed using arcsine
transformation to normalize its frequency distribution.
A univariate analysis of variance using the general
linear model (GLM) procedure of SAS version 9.3
(SAS Institute 2003) was performed on grain
biophysical and insect bioassay traits as well as the
stem borer damage traits. A susceptibility index based
on leaf damage score, number of borer exit holes and
cumulative tunnel length was computed by summing
up the ratios between values and overall mean and
dividing by the number of parameters evaluated.
Germplasm with susceptibility-index values less than
0.8 were regarded as resistant, and those with greater
than 0.8 as susceptible (Tefera et al. 2011).
3.5 Analysis of molecular data
SSR data analyses were conducted as described by
Semagn et al., (2014). Briefly, AlleloBin
(
.
icrisat.org/bt-software-downloads.htm
) was used for
adjusting inconsistencies in allele calls obtained from
GeneMapper software. The number of adjusted alleles
per locus for each bulked genotype varied from 2 to
11. Thus, the adjusted allele sizes were converted into
binary format (present =1 and absent = 0) using
ALS-Binary
(
oads.htm
). Rogers distance matrix was calculated
between each pair of genotypes using NTSYS-pc for
Windows, version 2.0. The distance matrix was used
to generate phenograms using the unweighted
pair-group method based on arithmetic average
(UPGMA) as implemented in MEGA5.1. Principal
component analysis (PCA) was performed to project
the genotypes into different groups using JMP version
7.0 (SAS institute Inc., Cary, NC, USA). The first two
principal components were plotted to visualize
patterns of relationships among genotypes. An admixture
model-based clustering method implemented in the
software package STRUCTURE version 2.3.3 (Pritchard
et al., 2000) was used to infer population structure
among genotypes. STRUCTURE was run by varying
the number of clusters (k) from 1 to 6, with each K
repeated thrice at a burn-in period of 100,000 and
100,000 MCMC (Markov Chain Monte Carlo)
replications after burn-in. Genotypes with membership
probabilities > 60% were assigned to the same group,
