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Citation: Sichalwe, K.L.; Kayondo,
S.I.; Edema, R.; Omari, M.A.;
Kulembeka, H.; Rubaihayo, P.; Kanju,
E. Unlocking Cassava Brown Streak
Disease Resistance in Cassava:
Insights from Genetic Variability and
Combining Ability. Agronomy 2024,14,
2122. https://doi.org/10.3390/
agronomy14092122
Academic Editor: Jadwiga ´
Sliwka
Received: 25 July 2024
Revised: 28 August 2024
Accepted: 10 September 2024
Published: 18 September 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
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4.0/).
agronomy
Article
Unlocking Cassava Brown Streak Disease Resistance in Cassava:
Insights from Genetic Variability and Combining Ability
Karoline Leonard Sichalwe 1, 2, *, Siraj Ismail Kayondo 3, Richard Edema 1, Mikidadi Abubakar Omari 1,
Heneriko Kulembeka 4, Patrick Rubaihayo 1and Edward Kanju 3
1Department of Agricultural Production, Makerere University, Kampala P.O. Box 7062, Uganda;
redema@marcci.org (R.E.); mikisb2340@yahoo.com (M.A.O.); prubaihayo@gmail.com (P.R.)
2Tanzania Agricultural Research Institute Kibaha, Coast P.O. Box 30031, Tanzania
3International Institute for Tropical Agriculture, Plot 25 Mikocheni, Dar es Salaam P.O Box 34441, Tanzania;
s.kayondo@cgiar.org (S.I.K.); edkanju@gmail.com (E.K.)
4Tanzania Agricultural Research Institute Ukiriguru, Shinyanga Road, Mwanza P.O. Box 1433, Tanzania;
kulembeka@yahoo.com
*Correspondence: carosicha@gmail.com; Tel.: +255-766-871-425
Abstract: Cassava brown streak disease (CBSD) threatens cassava production in sub-Saharan Africa
despite the availability of resistant varieties. Extreme environmental factors weaken plant defenses,
reducing CBSD resistance. This study examined CBSD inheritance in cassava populations, assessed
genetic variability, and identified superior sources of resistance using F1, S1, and half-sib offspring
populations derived from resistant sources. The offspring underwent field evaluation at two distinct
sites from 2019 to 2021, and the symptom-free genotypes were analyzed using reverse transcription-
quantitative polymerase chain reaction (RT-qPCR). Resistance to CBSD was categorized as most
resistant, resistant, most tolerant, or tolerant based on symptoms and virus titers. The findings indi-
cated that the resistance to CBSD is highly influenced by genotypes, F1/S1 types, and environmental
conditions. An analysis of combining abilities revealed significant general combining abilities (GCAs)
for CBSD, cassava mosaic disease (CMD), and traits associated with yield. The heritability estimates
for resistance to CBSD varied between 43.4% and 63.2% for foliar symptoms and 14.6% and 57.9%
for root necrosis across locations. The inheritance pattern involved a combination of additive and
recessive genes with selfed (S1) populations displaying stronger and more effective resistance to the
disease. The cassava brown streak virus (CBSV) was highly prevalent, and the Ugandan cassava
brown streak virus (UCBSV) was not prevalent. Four genotypes were highly resistant to CBSD and
could be key sources of resistance to this disease.
Keywords: resistance sources; CBSV; UCBSV; root necrosis; virus sources; heritability estimates
1. Introduction
Cassava (Manihot esculenta Crantz) is a tropical root crop and an important source
of carbohydrates for millions of people around the world [
1
]. This crop can be grown
in marginal soils with limited rainfall, making it a food security crop for sub-Saharan
African countries [
2
]. Cassava production is seriously threatened by several viral diseases,
with cassava brown streak disease (CBSD) being a major concern [
3
]. CBSD has been a
prevalent production constraint in East Africa for over seven decades [
4
]; its impact is
steadily increasing in Central and Southern Africa [
5
,
6
] and emerging as a threat to West
Africa, the continent’s largest cassava producer [7].
CBSD is caused by two Ipomoviruses: the Ugandan cassava brown streak virus
(UCBSV) and the cassava brown streak virus (CBSV) [
8
]. Their effects lead to significant
crop yield reduction and economic losses of up to USD 1 billion [
9
]. CBSD profoundly
impacts the economic stability of the affected regions, disrupting important economic
activities and undermining the livelihoods of local communities. It poses a serious threat to
Agronomy 2024,14, 2122. https://doi.org/10.3390/agronomy14092122 https://www.mdpi.com/journal/agronomy
Agronomy 2024,14, 2122 2 of 18
food security by affecting the availability and accessibility of this essential staple food and,
thereby, the nutritional well-being of the population in the affected areas [
10
]. This disease
manifests with various symptoms, including yellow chlorosis in the leaves, leading to a loss
of green pigmentation and impaired photosynthesis. In the stems, brown stripes appear,
and in severe cases, the disease can lead to dieback, where stems and branches progressively
wither and die [
11
]. In the tuberous roots, cork-like necrosis appears, resulting in dry and
decayed tissue [
11
]. The variability of CBSD symptoms has led to different classifications
depending on the specific screening method used, including resistance mechanisms such as
insect vector avoidance, virus spread, virus replication, and immune response. Identifying
and quantifying resistance to viral infection in selected cassava varieties has been made
possible by reliable techniques such as molecular virus detection [12].
Using CBSD-resistant varieties is considered a sustainable and effective control strat-
egy. However, challenges remain due to whitefly vectors, variations in virus strain, and
environmental conditions that can impact the consistent and durable expression of resis-
tance across generations [
13
]. Previous studies have indicated that CBSD resistance is
influenced by additive and non-additive gene actions. Additive gene actions have been
reported in several studies where the cumulative effects of individual alleles contribute to
a trait’s expression [
14
,
15
]. In addition, non-additive gene action also plays a significant
role in controlling CBSD resistance, as highlighted in Nduwumuremyi et al. [
16
], and
Zacarias and Labuschagne, [
17
]. These findings reveal the complex genetic architecture
underlying CBSD resistance, indicating that it involves a combination of multiple genetic
effects that contribute to the overall resistance observed in cassava populations. Other
important, related cassava diseases and pests, such as cassava mosaic disease (CMD) have
been reported to be influenced by additive [
18
] and non-additive [
19
] gene action; resistance
to cassava green mites has been reported to be influenced by additive gene action [
20
]
and seventeen candidate genes associated with its resistance [
21
]. The importance of both
additive and non-additive gene effects in controlling the expression of agronomic traits has
also been reported [
16
,
20
]. Conflicting reports on gene effects can be attributed to factors
such as population type, mating design, analytical methods, study locations, and genotype
by environment interactions [22,23].
This study was conducted to address a critical gap in understanding disease resistance
in cassava, specifically focusing on CBSD. Despite ongoing research aimed at developing
resistant varieties, limited information is available on the use of mixed populations to deter-
mine inheritance patterns and gene actions controlling CBSD resistance. The objectives of
this study were to (i) investigate the inheritance of CBSD resistance in cassava populations
biparental (F) and selfed (S1) lines derived from known resistant parents; (ii) explore the
variability in resistance to CBSD levels within the populations; and (iii) identify superior
sources of resistance.
2. Materials and Methods
2.1. Plant Materials
The breeding materials were obtained from the International Institute of Tropical Agri-
culture (IITA) in Uganda. Three resistant CBSD genotypes, MM06/0123, CBSD MM06/0130,
and MM06/0128, along with one susceptible parent (TME14), were selected to develop
biparental (F1) and selfed (S1) populations. The criteria for selecting these parents included
their resistance to diseases, high fresh root yield, and high dry matter content (Table 1). A
total of 703 cassava genotypes were developed, and the NASE13 and NAROCASS1 checks
were included in the experiments. The NASE13 and NAROCASS1 checks are improved
varieties with high yield, high dry matter content, drought tolerance, and resistance to both
CMD and CBSD. Before planting the clonal evaluation trial in April 2019, the generated
populations underwent screening for CBSD and CMD in a germplasm maintenance trial
for two years at the IITA.
Agronomy 2024,14, 2122 3 of 18
Table 1. Characteristics of parental materials.
Parents CBSD Status Other Traits
MM060123 Resistant CMD resistant, High yield, High DMC
MM060128 Resistant CMD resistant, High yield, High DMC
MM060130 Resistant CMD resistant, High yield, High DMC
TME14 Susceptible CMD resistant, High yield, High DMC
CMD, cassava mosaic disease; CBSD, cassava brown streak disease: DMC, dry matter content.
2.2. Experimental Sites and Design
The experimental trials were conducted at the National Semi-Arid Resources Research
Institute (NaSARRI) and an IITA research station. In eastern Uganda, where the NaSARRI
is situated, the weather is characterized by a tall savannah ecology with rainfall between
1000 mm and 1300 mm per annum, temperatures between 18
◦
C and 31
◦
C (Supplementary
Figure S1A), and sandy loam soil with a PH of between 5.8 and 6.0 [
24
]. This place is
at latitude 01
◦
32
′
00
′′
N and longitude 32
◦
25
′
00
′′
E and is one of the country’s medium
spot areas for CBSD screening. The IITA is in Namulonge in Central Uganda, which is
characterized by a tropical rainforest ecology, rainfall of about 1500 mm per annum, a
temperature average of 22.20
◦
C (Supplementary Figure S1B), and sandy clay soil with
a PH of between 4.9 and 5.0 [
24
]. This place is at latitude 00
◦
32
′
00
′′
N and longitude
32◦36′36′′ E. The place is known as a hotspot for CBSD screening.
The clonal evaluation trial used an augmented design comprising test genotypes and
checks planted with parental genotypes in eight to ten blocks depending on the available
genotypes in the specific year and location. The field experiments were planted for two
cropping seasons from 2019 to 2022. The plot size was 5 m
2
, and the spacing was 1 m
×
1 m.
No fertilizer or irrigation was applied in the experiments, and weeds were controlled using
a hand hoe.
2.3. Phenotypic Data Collection
2.3.1. Disease Assessment
Disease assessment was conducted by collecting data on CBSD and CMD, as presented
below (Table 2).
Table 2. Virus disease data collection parameters, description, and collection period.
Parameter. Description Period
CBSDLI Cassava brown streak disease leaf incidence measured as a proportion of
plants within a plot showing symptoms to the total plant population
3, 6, and 9 months after planting
CBSDLS Cassava brown streak disease scored for severity of leaf symptoms on a scale
of 1 (clean/no infection) to 5 (severely diseased)
3, 6, and 9 months after planting
CBSDRI Cassava brown streak disease root incidence as a proportion of roots within a
plot showing symptoms to the total plant population
At harvest
(12 months after planting)
CBSDRS Cassava brown streak disease scored for severity of root symptoms on a scale
of 1 (clean/no necrosis) to 5 (severe lesions)
At harvest
(12 months after planting
CMDI
Cassava mosaic disease incidence measured as a proportion of plants within a
plot showing symptoms to the total plant population 3 and 6 months after planting
CMDS Cassava mosaic disease severity scored for severity of leaf symptoms on a
scale of 1 (clean) to 5 (severely diseased) 3 and 6 months after planting
2.3.2. Assessment of Yield and Yield Components
The following yield component data for each genotype were collected at harvest,
twelve months after planting (12MAP): number of fresh storage roots per plot; the fresh
storage root weight (kg/plot) converted to fresh root yield (t/ha); and the shoot weight (kg
per plot). Other variables, such as harvest index (HI), were calculated using the formula in
Agronomy 2024,14, 2122 4 of 18
Equation (1), and dry matter content (DMC in %) was determined using specific gravity,
calculated using the formula in Equation (2) [25].
HI =Weight of fresh storage root
Weight of fresh storage root +Weight of the above ground biomass, (1)
Dry matter content (%)=158.3 Wa
Wa −Ww −142, (2)
where Wa = mass of roots in air (kg), and Ww = mass of roots in water (kg).
Samples were chosen for virus detection and quantification based on observable
foliar CBSD symptoms with scores of 1, 2, or 3 for leaf severity and a score of 1 only
(asymptomatic) for root necrosis. Root slices of 2 cm were cut and covered in aluminum
foil, immediately stored on ice, refrigerated at
−
20
◦
C for short storage in the field, and
transferred to a
−
80
◦
C freezer for long-term storage at the TARI Kibaha laboratory. Before
extraction, samples were removed from the
−
80
◦
C refrigerator and returned to the
−
20
◦
C
refrigerator. Total RNA was extracted using a cetyl trimetyl ammonium bromide (CTAB)
protocol [
26
]. The RNA quality and purity were determined using a NanoDrop2000
spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The RNA samples were
used to test for the presence or absence of the CBSD virus using a Taqman assay. The tests
for CBSV and UCBSV were independently performed [
27
]. Specific primers that anneal
CBSV and UCBSV coat proteins were used (Table 3) for virus detection.
Table 3. Primers and probes targeting CBSV and UCBSV for real-time RT-qPCR.
Primer Name Sequence (5′to 3′) Annealing Site Source
CBSV-CP-Fer2 GAAGGGATTGGAYTRGAAGGA 7390–7410 Shirima et al. 2017 [27]
CBSV-CP-R1-1 GAACGCGGTATCCACACATA 8197–8216 Shirima et al. 2017 [27]
UCBSV-CP-F1−1 AGAGATCTGGAAAGGAAGT 7981–7999 Shirima et al. 2017 [27]
UCBSV-CP-R1-1 CTCGCCAYGACTTCTCATT 8403–8421 Shirima et al. 2017 [27]
COX-R CAACTACGGATATATAAGRRCCRRAACTG Adams et al. 2013 [28]
COX-F CGTCGCATTCCAGATTATCCA Adams et al. 2013 [28]
COX probe [HEX]-AGGGCATTCCATCCAGCGTAAGCA-[BHQ1] Adams et al. 2013 [28]
R represents A or G; Y represents C or T. Designations with -F denote forward, and those with -R denote reverse
primers. Those with -probe represent TaqMan probes.
Complementary DNA (cDNA) was prepared from 1
µ
g of template RNA using first-
strand cDNA synthesis (quick protocol). The complete reverse transcriptase reaction (2
µ
L)
contained 50
µ
M of Oligo dT18 (New England Biolabs, Ipswich, MA, USA), 10
×
M-MuLV
buffer, 200 U/
µ
L of MuMLV reverse transcriptase (RT), 10 mM of dNTP Mix, 40 U/
µ
L of
RNase inhibitor, and nuclease-free water. Samples detected with the virus were analyzed
with an absolute quantification qPCR reaction using a Taqman assay specific to CBSV and
UCBSV. Quantification was performed by measuring 6PK01-Fer2 plasmid concentration
using a Qubit 3.0 fluorometer followed by ten-fold serial dilution starting with an original
concentration of 21.5 ng/
µ
L. A quantification reaction was prepared using 25
µ
L of Mg,
10
×
PCR buffer, 25 Mm of MgCl
2
, 10 mM of dNTP, 7.5
µ
M primers, a 5
µ
M probe,
1
×
reference dye, 5 U/
µ
L of Taq DNA polymerase, and plasmids. The PCR program was
set to 95
◦
C for 10 min, 95
◦
C for 15 s, and 60
◦
C for 1 min for 40 PCR cycles. The reaction
was performed using the Stratagene Mx3000P qPCR system (Agilent Technologies, Santa
Clara, CA, USA), and data were acquired using the Mx3000P qPCR software (Agilent
Aria Software v1.71). RNA amplification during the PCR process ranged from 15 to
35 cycles with amplification efficiency between 100% and 104.8%, a standard coefficient
of correlation (R2) curve of 0.99 and a slope of 3.21 (Supplementary Figure S2). The data
were assembled in Microsoft Excel and analyzed for detected genotypes with their specific
viruses and concentrations.
Agronomy 2024,14, 2122 5 of 18
2.4. Data Analysis
Data analysis was performed at different phases. Phase one comprised analysis of
variance using the lmer package in R (R.4.1.2) (R Core Team. 2021): all individual F1
and S1 genotypes were combined, and Best Linear Unbiased Prediction (BLUP) estimated
the mixed model’s random effects. In phase two, the crossed F1 and S1 genotypes were
analyzed to determine variabilities using the lmer package in R.4.1.2. Finally, genotypes
were averaged to assess family performance. Analysis of variance was performed using
the model in Equation (3):
Yijk =µ+Gi +Ej +GEk+∈ij, (3)
where Yijk is the observed phenotypic value,
µ
is the overall mean, Gi is the genotype
effect, Ej is the environmental effect, GEk is the interaction effect between genotype and
environment, and ∈is the residual error term assuming a normal distribution.
2.4.1. Analysis of Variance for Parents and Families
The combined data were analyzed using the ASReml package in R (R.4.1.1.) Genotypes
were fitted as fixed factors; environments were treated as random factors; and the mean
squares for SCA, GCA1, GCA2 and the interactions between environments and seasons
were fitted in the model in Equation (4):
Yijk =µ+G+Fi+Mj+FM +Ek+GE+∈, (4)
where Y is the observed phenotypic value of the progeny of the ith female crossed with jth
male in the kth environment,
µ
is the overall mean, G is the genotype effect, F is the GCA of
the ith female, M is the GCA of the jth male, SCA is the cross between the ith female and the
jth male, Ek is the environmental effect, GE is the interaction effect between the genotype
and environment, and ∈is the residual error term assuming a normal distribution.
2.4.2. Estimation of Variance Components and Heritability
Phenotypic and genotypic variances were computed from the expected mean squares
of the analysis of variance; the phenotypic coefficient of variation (PCV) and the geno-
typic coefficient of variation (GCV) were estimated using the formula below, expressed in
percentage [29].
σ2
g=MSG −MSE
r(5)
σ2
p=σ2
g+MSE (6)
Here,
σ2
g
is the genotypic variance,
σ2
p
is the phenotypic variance, MSG is the genotypic
mean square, MSE is the error mean square, and r is the replication number.
PCV =qσ2
p/x×100 (7)
GVC =qσ2
g/X×100 (8)
Here, PCV is the phenotypic coefficient of variation, GCV is the genotypic coefficient
of variation,
X
is the grand average of the traits,
σp
is the phenotypic variance, and
σg
is
the genotypic variance.
Population heritability was estimated at two levels: level one was heritability across en-
vironments, and level two was for specific years in the location. Heritability was computed
according to Falconer and Mackay, [30] using the following formula:
H2=σ2
g
σ2
p
×100, (9)
Agronomy 2024,14, 2122 6 of 18
where σ2
gis the genotypic variance, and σ2
pis the phenotypic variance.
2.4.3. Selection of Resistant Genotypes and Level of Resistance in Populations
Absolute CBSV and UCBSV quantification was determined by running the default
settings of the MxPro qPCR software (Agilent Aria Software v1.71) on the Stratagene
Mx3000P qPCR system (Agilent Technologies). The data were assembled in Microsoft
Excel, and correlation analysis was performed. The resistance levels were categorized
as most resistant (MR), resistant (R), most tolerant (MT), and tolerant (T) based on the
foliar symptoms, root necrosis, and the virus detection test. The proportion of resistant and
tolerant genotypes per family was computed by expressing the absolute number of resistant
genotypes as a percentage of the total number of genotypes established in that family.
3. Results
3.1. Performance and Genetic Variation in Genotypes and Population Types
The descriptive statistics for genotypes across seasons and locations are presented
in Table 4. The CBSD incidences had a minimum of 0% and a maximum of 100%, while
CBSD severities had a minimum score of 1 and a maximum of 5 in CBSDL3S and CBSDRS,
respectively. The lowest mean CBSDLI (55.79%) was observed at 3MAP (CBSDL3I) and
the highest (65.14%) at 9MAP (CBSDL91). The same trend was observed for CBSD leaf
severities (CBSDLS), where the lowest mean (1.95) was observed at 3MAP and the highest
(2.28) at 9MAP. For CBSD root necrosis incidence (CBSDRI) and severity (CBSDRS), the
mean CBSDRI was 37.84%, whereas the mean CBSDRS was 2.76. The cassava mosaic
disease severity (CMDLS) trend followed a similar pattern, where the genotypes had the
lowest (1) and the highest (5) at 3MAP and 9MAP, respectively. The CMD incidences
exhibited fluctuations across different months after planting, with CMDL6I having the
highest mean incidence at 19.31
±
0.65 standard error. The CMD severities also varied but
generally remained lower than the CBSD severities.
Table 4. Descriptive statistics for CBSD incidences and severities (3, 6, and 9 MAP), CMD incidences
and severities (3 and 6 MAP), and yield traits across two seasons and locations.
Variable Min Max Mean ±SE STDEV CV (%)
CBSDL3I 0 100 55.79 ±0.8 42.75 76.64
CBSDL6I 0 100 63.35 ±0.78 41.75 65.9
CBSDL9I 0 100 65.14 ±0.78 41.45 63.63
CBSDL3S 1 5 1.95 ±0.01 0.75 38.63
CBSDL6S 1 4 2.23 ±0.02 0.89 39.88
CBSDL9S 1 4 2.28 ±0.02 0.88 38.51
CBSDR12S 1 5 2.76 ±0.02 1.32 47.8
CBSDR12I 0 100 37.84 ±0.66 35.27 93.2
CMDL3I 0 100 18.33 ±0.64 34.01 185.51
CMDL6I 0 100 19.31 ±0.65 34.61 179.3
CMDL9I 0 100 13.11 ±0.56 29.75 226.96
CMDL3S 1 5 1.5 ±0.02 0.87 58.3
CMDL6S 1 4 1.52 ±0.02 0.86 56.56
CMDL9S 1 5 1.36 ±0.01 0.75 55.18
DMC 16.3 68.16 35.5 ±0.11 5.03 77.63
FYLD 0 175 15.46 ±0.34 17.98 116.27
HI 0 1 0.34 ±0 0.17 48.51
TRTN 0 73 14.45 ±0.21 11.22 14.16
CBSDLS, cassava brown streak disease leaf severity; CBSDRS, cassava brown streak disease root severity; CBSDLI,
cassava brown streak disease leaf incidence; CBSDRI, cassava brown streak disease root incidence; CMDS, cassava
mosaic disease severity; CMDI, cassava mosaic disease incidence; 3,6 and 9, months after planting; FRYLD, fresh
root yield; HI, harvest index; DMC, dry matter content; TRTN, total root number; Min, minimum; Max, maximum;
SE, standard error; STDEV, standard deviation; CV, coefficient of variation.
Other yield traits, such as DMC, Fresh Yield (FYLD), HI, and the total root tuber
number (TRTN), showed considerable variation. The DMC ranged from 16.3% to 68.16%
Agronomy 2024,14, 2122 7 of 18
with an average of 35.5%, while the FYLD had an average of 15.46 t/ha; few genotypes
outperformed at 175 t/ha. HI ranged between 0 and 1, indicating different biomass
proportions allocated to harvestable parts. The TRTN showed variability with a maximum
value of 73.
The analysis of variance detected highly significant differences (p< 0.001) between
genotype, environment, and genotype by environment interaction effects for CBSD in-
cidences and severities at different infection stages (3, 6, and 9 months after planting).
Significant differences were also observed for CBSDRS, CBSDRI, and CMD severities and
incidences at different infection stages (Table 5). Similarly, the significance levels for MSG,
MSE, and MSGxE indicated significant genetic, environmental, and genotype-environment
interaction effects on FRYLD, HI, and DMC. A significant genotype and environment
interaction (MSGxE) was observed in the TRTN (p< 0.05) (Table 5).
Table 5. Mean squares for genotype (G), environment (E), and GxE interactions for CBSD, CMD, and
yield traits over two seasons in Namulonge and Serere, Uganda.
Sources of Variation
Trait MSG (672) MSE (3) MSGxE (1351) MSR (127)
CBSDL3S 0.82 *** 41.973 *** 0.382 *** 0.144
CBSDL6S 1.52 *** 64.66 *** 0.39 *** 0.227
CBSDL9S 1.46 *** 28.12 *** 0.47 *** 0.225
CBSDRS 2.3519 *** 23.52 *** 1.39 *** 1.09 ***
CBSDL3I 2677 *** 166236 *** 1171 *** 578
CBSDL6I 3513 *** 111414 *** 843 *** 414
CBSDL9I 3224 *** 124710 *** 934 *** 429
CBSDRI 1938.7 *** 10980.7 *** 784.4 *** 604.7 ***
CMD3S 1.40 *** 36.29 *** 0.49 *** 0.173
CMDS6S 1.58 *** 33.97 *** 0.36 *** 0.097
CMDS3I 2022 *** 99169 *** 734 *** 112
CMD6I 2350 *** 100955 *** 614 *** 47
FRYL (ta/ha) 530.3 *** 18006.4 *** 258.7 *** 258.7 ***
HI 0.029 *** 3.76 *** 0.01 *** 0.011
DMC 46.49 *** 535.59 *** 15.08 *** 9.27
TRN 204.9 *** 7480.0 *** 79.4 * 65.4
* and ***, significance levels at 0.05, and 0.001, respectively; MSG, mean square of genotype; MSE, mean square of
the environment; MSGxE, mean square of GXE interaction; MSR, mean square of residual; number in parenthesis,
degree of freedom; CBSDLS, cassava brown streak disease leaf severity; CBSDRS, cassava brown streak disease
root severity; CBSDLI, cassava brown streak disease leaf incidence; CBSDRI, cassava brown streak disease root
incidence; CMDS, cassava mosaic disease severity; CMDI, cassava mosaic disease incidence; 3,6, and 9, months
after planting; FRYL, fresh root yield; HI, harvest index; DMC, dry matter content; TRTN, total root number.
The analysis of variance for all traits evaluated among the population types (PTs), en-
vironments (Es), and their interactions (PTxEs) are presented in Table 6. Highly significant
differences (p< 0.001) were detected between the PT for all the traits except for CBSDRI,
HI, and DMC. The differences between PT were significant (p< 0.005) for CBSDL3I and
CMD3S. Highly significant differences (p< 0.001) were detected between environments for
all the traits recorded. Furthermore, highly significant differences (p< 0.001) were detected
for the interactions between PT and E for all the traits except CMD3I, CMD6I, HI (p< 0.01),
and CMD6S (p< 0.05).
Agronomy 2024,14, 2122 8 of 18
Table 6. Mean squares for PT, environment Es, and PT
×
Es for disease resistance and yield traits
evaluated across two seasons at Namulonge and Serere, Uganda.
Trait Sources of Variation
MSPT (3) MSE (3) MSPTxE (9) MSR (2138)
CBSDL3S 1.76 * 46.99 *** 2.06 *** 0.49
CBSDL6S 3.55 *** 67.71 *** 3.41 *** 0.71
CBSDL9S 3.87 *** 31.07 *** 2.32 *** 0.75
CBSDRS 10.02 *** 25.53 *** 4.62 *** 1.65
CBSDL3I 4332 * 19.933 *** 5629 *** 1551
CBSDL6I 9521 *** 11161 *** 7460 *** 1603
CBSDL9I 11298 *** 135177 *** 6052 *** 1573
CBSDRI 2157.3 18811.6 *** 2763 *** 1115.3
CMD3S 1.76 * 46.99 *** 2.06 *** 0.49
CMD6S 12.44 *** 30.71 *** 1.47 * 0.711
CMD3I 46803 *** 92391 *** 2795 ** 1080
CMD6I 20097 *** 94448 *** 2934 ** 1098
FRYLD (ta/ha) 1033 *** 530.25 *** 145.6 *** 33.15
HI 0.03 3.77 *** 0.045 ** 0.02
DMC 35.73 768.78 *** 116.32 *** 23.83
TRTN 2421.1 *** 7863.7 *** 407.3 *** 112.8
*, **, and *** indicate significance levels at 0.05, 0.01, and 0.001, respectively; MSPT, mean square of population
types; MSE, mean square of environment; MSPTxE, mean square of PT x E interaction; MSR, mean square of
residual; number in parenthesis, degree of freedom; CBSDLS, cassava brown streak disease leaf severity; CBSDRS,
cassava brown streak disease root severity; CBSDLI, cassava brown streak disease leaf incidence; CBSDRI, cassava
brown streak disease root incidence; CMDS, cassava mosaic disease severity; CMDI, cassava mosaic disease
incidence; 3, 6, and 9 months after planting; FRYL, fresh root yield; HI, harvest index; DMC, dry matter content;
TRTN, total root number.
3.1.1. Frequency of CBSD Root Necrosis Categories within Crosses
The proportion of CBSD root necrosis in fresh roots within mapping population crosses
was also compared (Figure 1). The classifications were as follows: resistant for a score of 1,
tolerant for a score of 2, and susceptible for scores of 3–5 of CBSD root severity (Figure 2).
Less than 10% of the resistant genotypes were observed among the F1 and S1 crosses. In a
susceptible by susceptible cross (TME14XTME14), only 2% of resistant genotypes were ob-
served. The resistant x resistant cross (MM060123) had slightly more susceptible genotypes
at 71.7% compared with resistant
×
resistant F1 parents, including MM060123XMM060128
(58.6%), MM060123XMM060130 (59.5), and MM060128XMM060130 (66.3%).
Agronomy 2024, 14, x FOR PEER REVIEW 9 of 19
Figure 1. Proportion of CBSD root necrosis in biparental F1 and selfing crosses (S1). Score
classification: score 1, resistant; score 2, tolerant; score 3–5, susceptible; (A), S1; (B), F1.
Figure 2. Score severity of cassava brown streak disease on root symptoms ranging from scale 1 (no
visible symptoms, leftmost) to scale 5 (severely brown necrosis, rightmost).
3.1.2. Differential Performance of Controls, Parents, and Populations in
Multiple Environments
The control lines had higher CBSD scores class than the parents and populations in
the 2019sendusu environment, and the lowest score (1) was observed in the 2021serere
environment (Figure 3a). In the F1 and S1 populations, the highest scores (2.5 and 2.6,
respectively) were observed in the 2020serere environment. On the other hand, the S1 and
F1 populations had the highest CMDS_6MAP scores (class 2) in 2019sendusu, while the
controls and parents were class 1 (Figure 3b).
The CBSDRS for the controls varied across all four environments, with the highest
score at 3.5 and the lowest score at 2 in 2021serere (Figure 4a). The parent fresh yield was
lower than that of the control and populations in 2019sendusu and was lowest in
environments with less than 10 t/ha in 2020serere (Figure 4b). The highest fresh root yield
was observed in the controls across all four environments.
DMC showed a substantial difference between populations and environments. The
highest DMC in 2019sendusu was in the parents, while the lowest was in the controls
(Figure 5a). There was only a small variation between F1 and S1 populations. The harvest
index showed significant differences between the controls, parents, and the F1 and S1
Figure 1. Proportion of CBSD root necrosis in biparental F1 and selfing crosses (S1). Score classifica-
tion: score 1, resistant; score 2, tolerant; score 3–5, susceptible; (A), S1; (B), F1.
Agronomy 2024,14, 2122 9 of 18
Agronomy 2024, 14, x FOR PEER REVIEW 9 of 19
Figure 1. Proportion of CBSD root necrosis in biparental F1 and selfing crosses (S1). Score
classification: score 1, resistant; score 2, tolerant; score 3–5, susceptible; (A), S1; (B), F1.
Figure 2. Score severity of cassava brown streak disease on root symptoms ranging from scale 1 (no
visible symptoms, leftmost) to scale 5 (severely brown necrosis, rightmost).
3.1.2. Differential Performance of Controls, Parents, and Populations in
Multiple Environments
The control lines had higher CBSD scores class than the parents and populations in
the 2019sendusu environment, and the lowest score (1) was observed in the 2021serere
environment (Figure 3a). In the F1 and S1 populations, the highest scores (2.5 and 2.6,
respectively) were observed in the 2020serere environment. On the other hand, the S1 and
F1 populations had the highest CMDS_6MAP scores (class 2) in 2019sendusu, while the
controls and parents were class 1 (Figure 3b).
The CBSDRS for the controls varied across all four environments, with the highest
score at 3.5 and the lowest score at 2 in 2021serere (Figure 4a). The parent fresh yield was
lower than that of the control and populations in 2019sendusu and was lowest in
environments with less than 10 t/ha in 2020serere (Figure 4b). The highest fresh root yield
was observed in the controls across all four environments.
DMC showed a substantial difference between populations and environments. The
highest DMC in 2019sendusu was in the parents, while the lowest was in the controls
(Figure 5a). There was only a small variation between F1 and S1 populations. The harvest
index showed significant differences between the controls, parents, and the F1 and S1
Figure 2. Score severity of cassava brown streak disease on root symptoms ranging from scale 1 (no
visible symptoms, leftmost) to scale 5 (severely brown necrosis, rightmost).
3.1.2. Differential Performance of Controls, Parents, and Populations in
Multiple Environments
The control lines had higher CBSD scores class than the parents and populations in
the 2019 sendusu environment, and the lowest score (1) was observed in the 2021 serere
environment (Figure 3a). In the F1 and S1 populations, the highest scores (2.5 and 2.6,
respectively) were observed in the 2020serere environment. On the other hand, the S1 and
F1 populations had the highest CMDS_6MAP scores (class 2) in 2019sendusu, while the
controls and parents were class 1 (Figure 3b).
Agronomy 2024, 14, x FOR PEER REVIEW 10 of 19
populations, as well as across the 2019sendusu, 2020serere, 2021sendusu, and 2021serere
environments. The highest harvest index (0.6) was observed in controls in 2020serere
(Figure 5b). Plant establishment was higher than 95% for all population types in
2019sendusu, with the lowest observed in controls (82%) in 2021sendusu (Figure 5c).
Figure 3. Estimated marginal means of population types by the environment for CBSD_6MAP (a) and CMD_6MAP (b).
3.1.3. Combining Abilities and Mode of Gene Action for Resistance to Cassava Brown
Streak Disease
The analysis of variance for combining abilities showed that the environment was
significant (p < 0.05) for all the traits measured (Table 7). The mean squares for GCA1,
GCA2, and SCA represent genetic variability within the parents and families for each trait.
The GCA1 (female) effects were significant (p < 0.05) for all CBSD incidence and severities
on foliar, roots, and root yield traits. The GCA2 (male) effects were significantly different
only in CBSDRI and CBSDRS; for the other traits, non-significant effects were observed.
SCA (specific combining ability) represents the non-additive genetic effects resulting from
interactions between parental genotypes. The SCA effects were not significant for all traits
measured. The GCA/SCA ratio provides insights into the relative importance of additive
(GCA) and non-additive (SCA) genetic effects in trait inheritance. The GCA/SCA ratio was
high and positive. The percentage contribution to the Sum of Square showed that GCA1
had a higher contribution than its corresponding GCA2 or SCA for all traits under
investigation.
Figure 3. Estimated marginal means of population types by the environment for CBSD_6MAP (a)
and CMD_6MAP (b).
The CBSDRS for the controls varied across all four environments, with the highest
score at 3.5 and the lowest score at 2 in 2021serere (Figure 4a). The parent fresh yield
was lower than that of the control and populations in 2019sendusu and was lowest in
environments with less than 10 t/ha in 2020serere (Figure 4b). The highest fresh root yield
was observed in the controls across all four environments.
Agronomy 2024,14, 2122 10 of 18
Agronomy 2024, 14, x FOR PEER REVIEW 11 of 19
Figure 4. Estimated marginal means of population types by environments for CBSDRS (a) and fresh
yield (fyld) (b).
Figure 5. Estimated marginal means of population types by environments for dry maer content
(DMC) (a), harvest index (HI) (b), and plant establishment (c).
The genetic parameters related to disease and yield traits in cassava populations are
summarized in Table 8. The results showed that the phenotypic variances (PVs) for traits
associated with CBSD, CMD, FYLD, and DMC were higher than the corresponding
genotypic variances (GVs) and environmental variances (EVs). A high PCV (>20%) was
recorded for all traits except DMC, whose PVC was moderate (12.39%). The highest GCV
(67.05%) was observed for CMDI6 and the lowest for DMC (5.49%).
The genetic advance (GA) ranged from 0.02 for HI to 17.54 for CBSDL6I, and the
genetic advance as a percent of the mean (GAM) ranged from 3.21% for CBSDRI to 62.23%
for CMD6I. The GAM was classified as low (below 10%), medium (10–20%), or high
Figure 4. Estimated marginal means of population types by environments for CBSDRS (a) and fresh
yield (fyld) (b).
DMC showed a substantial difference between populations and environments. The
highest DMC in 2019sendusu was in the parents, while the lowest was in the controls
(Figure 5a).
There was only a small variation between F1 and S1 populations. The harvest
index showed significant differences between the controls, parents, and the F1 and S1 popu-
lations, as well as across the 2019sendusu, 2020serere, 2021sendusu, and 2021serere environ-
ments. The highest harvest index (0.6) was observed in controls in 2020serere
(Figure 5b).
Plant establishment was higher than 95% for all population types in 2019sendusu, with the
lowest observed in controls (82%) in 2021sendusu (Figure 5c).
Agronomy 2024, 14, x FOR PEER REVIEW 11 of 19
Figure 4. Estimated marginal means of population types by environments for CBSDRS (a) and fresh
yield (fyld) (b).
Figure 5. Estimated marginal means of population types by environments for dry maer content
(DMC) (a), harvest index (HI) (b), and plant establishment (c).
The genetic parameters related to disease and yield traits in cassava populations are
summarized in Table 8. The results showed that the phenotypic variances (PVs) for traits
associated with CBSD, CMD, FYLD, and DMC were higher than the corresponding
genotypic variances (GVs) and environmental variances (EVs). A high PCV (>20%) was
recorded for all traits except DMC, whose PVC was moderate (12.39%). The highest GCV
(67.05%) was observed for CMDI6 and the lowest for DMC (5.49%).
The genetic advance (GA) ranged from 0.02 for HI to 17.54 for CBSDL6I, and the
genetic advance as a percent of the mean (GAM) ranged from 3.21% for CBSDRI to 62.23%
for CMD6I. The GAM was classified as low (below 10%), medium (10–20%), or high
Figure 5. Estimated marginal means of population types by environments for dry matter content
(DMC) (a), harvest index (HI) (b), and plant establishment (c).
Agronomy 2024,14, 2122 11 of 18
3.1.3. Combining Abilities and Mode of Gene Action for Resistance to Cassava Brown
Streak Disease
The analysis of variance for combining abilities showed that the environment was
significant (p< 0.05) for all the traits measured (Table 7). The mean squares for GCA1,
GCA2, and SCA represent genetic variability within the parents and families for each trait.
The GCA1 (female) effects were significant (p< 0.05) for all CBSD incidence and severities
on foliar, roots, and root yield traits. The GCA2 (male) effects were significantly different
only in CBSDRI and CBSDRS; for the other traits, non-significant effects were observed.
SCA (specific combining ability) represents the non-additive genetic effects resulting from
interactions between parental genotypes. The SCA effects were not significant for all
traits measured. The GCA/SCA ratio provides insights into the relative importance of
additive (GCA) and non-additive (SCA) genetic effects in trait inheritance. The GCA/SCA
ratio was high and positive. The percentage contribution to the Sum of Square showed
that GCA1 had a higher contribution than its corresponding GCA2 or SCA for all traits
under investigation.
Table 7. Mean square of parents and families for CBSD, CMD, and root yield traits.
SOV CBSDLS CBSDLI CBSDRS CBSDRI CMDS CMDI FYLD HI DMC TRTN
Environment
81.333 ***
141,870 *** 25.9728 *** 23,519 ***
50.116 ***
130,085 *** 23,491.5 *** 5.9935 ***
749.31 ***
11,551.2 ***
GCA1 7.061 *** 23,094 *** 14.7296 *** 13,209.4 *** 5.205 *** 7535 *** 5999.9 *** 0.2998 ***
178.08 ***
1988.7 ***
GCA2 8.159 *** 31,911 *** 8.398 *** 8952.5 *** 1.161 * 1903 * 2520 *** 0.1514 *** 34.77 1866.6 ***
SCA 1.385 * 3715 ** 3.7492 * 1919.2. 0.403 349 1292.5 *** 0.029 9.62 784.1 ***
Environment:GCA1
2.06 *** 4237 *** 2.4087 * 2670.9 *** 0.693 * 1441 ** 592.9 *** 0.0369 ** 86.64 *** 277.4 ***
Environment:GCA2
0.422 2185 3.0499 * 2535.4 ** 0.616 981 308.5 0.0095 5.8 89.3
Environment: SCA 0.481 998 1.0776 549.7 0.358 645 387.7 0.0045 8.47 135
Residuals 0.659 1438 1.6394 1145.1 0.471 754 268.3 0.0199 22.94 100.7
GCA/SCA ratio 9.3 12.1 6.03 10.9 17.6 29.7 6.8 15.5 24.9 4.3
% SS GCA1 61.76 59.47 69.84 72.08 86.87 87.87 74.61 78.17 89.18 59.14
% SS GCA2 28.55 32.87 15.93 19.54 7.74 8.88 12.53 15.78 6.96 22.2
% SS SCA 9.69 7.65 14.22 8.38 5.39 3.26 12.86 6.05 3.86 18.66
*,**, and *** indicate significance levels at 0.5,0.01 and 0.001 respectively; CBSDLS, cassava brown streak disease
leaf severity; CBSDLI, cassava brown streak disease leaf incidence; CBSDRS, cassava brown streak disease root
severity; CBSDRI, cassava brown streak disease root incidence; CMDS, cassava mosaic disease severity; CMDI,
cassava mosaic disease incidence; FYLD, fresh root yield; HI, harvest index; DMC, dry matter content; DF, degree
of freedom; GCA1, general combining ability for females; GCA2, general combining ability for males; SCA,
specific combining ability.
The genetic parameters related to disease and yield traits in cassava populations
are summarized in Table 8. The results showed that the phenotypic variances (PVs) for
traits associated with CBSD, CMD, FYLD, and DMC were higher than the corresponding
genotypic variances (GVs) and environmental variances (EVs). A high PCV (>20%) was
recorded for all traits except DMC, whose PVC was moderate (12.39%). The highest GCV
(67.05%) was observed for CMDI6 and the lowest for DMC (5.49%).
Table 8. Genetic parameters for diseases and yield-related traits in cassava populations.
Traits Mean SE EV GV PV ECV GCV PCV H GA GAM
CBSDL6I 61.49 11.28 1018.6 310.47 1329.07 51.91 28.66 59.29 0.23 17.54 28.53
CBSDL6S 2.2 0.25 0.5 0.13 0.62 32.09 16.17 35.94 0.2 0.33 14.99
CMD6I 20.88 9.81 769.72 196.06 965.78 132.85 67.05 148.81 0.2 13 62.23
CMD6S 1.56 0.23 0.41 0.15 0.55 40.69 24.51 47.5 0.27 0.41 26.04
FYLD 19.24 5.92 280.26 30.96 311.22 87.01 28.92 91.69 0.1 3.61 18.79
HI 0.38 0.05 0.02 0 0.02 35.39 10.2 36.87 0.08 0.02 5.82
DMC 35.5 1.39 15.56 3.8 19.36 11.11 5.49 12.39 0.2 1.78 5.01
CBSDRI 20.72 10.48 878.08 9.62 887.7 143.04 14.97 143.82 0.01 0.67 3.21
CBSDRS 1.48 0.19 0.29 0.05 0.33 36.07 14.65 38.93 0.14 0.17 11.37
SE, standard error; EV, environment variance; GV, genotypic variance; PV, phenotypic variance; ECV, environmen-
tal coefficient of variation; GCV, genotypic coefficient of variation, PCV, phenotypic coefficient of variation; H,
broad sense heritabilities; GA, genetic advance; GAM, genetic advance of mean.
Agronomy 2024,14, 2122 12 of 18
The genetic advance (GA) ranged from 0.02 for HI to 17.54 for CBSDL6I, and the
genetic advance as a percent of the mean (GAM) ranged from 3.21% for CBSDRI to 62.23%
for CMD6I. The GAM was classified as low (below 10%), medium (10–20%), or high (above
20%). Low GAM (<10%) was observed for DMC, HI, and CBSDRI; medium for CBSDL6S,
CBSDS9, FRYLD, and CBSDRS; and high for CBSDL6I, CMD6I, and CMD6S (Table 8). Low
heritability estimates (
≤
30) were observed across seasons and locations for all the traits
presented, ranging from 0.01 (CBSDRI) to 0.27 (CMDS6).
The heritability estimates for CBSD traits were expanded to locations in specific
growing seasons, and the results are presented in Table 9. Almost all broad sense heritability
for CBSD severities and incidences at the IITA were higher than those at the NaSARRI.
The highest (69.2%) was observed for CBSDL6I, and the lowest (27.3%) was observed for
CBSDL3I in 2019/2022 (across all locations). The heritability estimates at the IITA were
higher than those at NaSARRI. The broad sense heritability estimates ranged from 14.6
(CBSDRS at the NaSARRI) to 69.2 (CBSDI6 at the IITA).
Table 9. Broad-sense heritability of CBSD across years and locations.
Trait Year Location H (%)
CBSDL3I 2019 to 2022 IITA 65.0
CBSDL3I 2020 to 2022 NaSARRI 32.7
CBSDL3I 2019 to 2022 Multilocation 27.3
CBSDL3S 2019 to 2022 IITA 54.0
CBSDL3S 2020 to 2022 NaSARRI 32.5
CBSDL3S 2019 to 2022 Multilocation 29.2
CBSDL6I 2019 to 2022 IITA 69.2
CBSDL6I 2020 to 2022 NaSARRI 49.4
CBSDL6I 2019 to 2022 Multilocation 39.3
CBSDL6I 2019 to 2022 IITA 63.2
CBSDL6I 2020 to 2022 NaSARRI 43.4
CBSDL6I 2019 to 2022 Multilocation 36.4
CBSDL9I 2019 to 2022 IITA 53.3
CBSDL9I 2020 to 2022 NaSARRI 44.6
CBSDL9I 2019 to 2022 Multilocation 39.4
CBSDL9S 2019 to 2022 IITA 46.8
CBSDL9S 2020 to 2022 NaSARRI 58.4
CBSDL9S 2019 to 2022 Multilocation 42.4
CBSDRI 2019 to 2022 IITA 62.1
CBSDRI 2020 to 2022 NaSARRI 31.9
CBSDRI 2019 to 2022 Multilocation 48.2
CBSDRS 2019 to 2022 IITA 57.9
CBSDRS 2020 to 2022 NaSARRI 14.6
CBSDRS 2019 to 2022 Multilocation 36.1
CBSDLI, cassava brown streak disease leaf incidence; CBSDLS, cassava brown streak disease leaf severity; CBSDRI,
cassava brown streak disease root incidence; CBSDRS, cassava brown steak disease root severity; 3, 6, and 9,
months after planting.
3.1.4. Virus Detection and Quantification
Cassava genotypes that showed leaf symptoms and root necrosis (Figure 6) were
excluded, while those with clean leaves and roots showing no observable CBSD symptoms
(Figure 7) were selected for virus detection. Virus detection and quantification revealed
the prevalence of CBSV and fewer UCBSV occurrences in both sites (Table 10). The roots
chosen for virus detection were selected during the root assessment, and the sample with a
score of 1 was selected.
Agronomy 2024,14, 2122 13 of 18
Agronomy 2024, 14, x FOR PEER REVIEW 13 of 19
observed for CBSDL3I in 2019/2022 (across all locations). The heritability estimates at the
IITA were higher than those at NaSARRI. The broad sense heritability estimates ranged
from 14.6 (CBSDRS at the NaSARRI) to 69.2 (CBSDI6 at the IITA).
Table 9. Broad-sense heritability of CBSD across years and locations.
Trait
Year
Location
H (%)
CBSDL3I
2019 to 2022
IITA
65.0
CBSDL3I
2020 to 2022
NaSARRI
32.7
CBSDL3I
2019 to 2022
Multilocation
27.3
CBSDL3S
2019 to 2022
IITA
54.0
CBSDL3S
2020 to 2022
NaSARRI
32.5
CBSDL3S
2019 to 2022
Multilocation
29.2
CBSDL6I
2019 to 2022
IITA
69.2
CBSDL6I
2020 to 2022
NaSARRI
49.4
CBSDL6I
2019 to 2022
Multilocation
39.3
CBSDL6I
2019 to 2022
IITA
63.2
CBSDL6I
2020 to 2022
NaSARRI
43.4
CBSDL6I
2019 to 2022
Multilocation
36.4
CBSDL9I
2019 to 2022
IITA
53.3
CBSDL9I
2020 to 2022
NaSARRI
44.6
CBSDL9I
2019 to 2022
Multilocation
39.4
CBSDL9S
2019 to 2022
IITA
46.8
CBSDL9S
2020 to 2022
NaSARRI
58.4
CBSDL9S
2019 to 2022
Multilocation
42.4
CBSDRI
2019 to 2022
IITA
62.1
CBSDRI
2020 to 2022
NaSARRI
31.9
CBSDRI
2019 to 2022
Multilocation
48.2
CBSDRS
2019 to 2022
IITA
57.9
CBSDRS
2020 to 2022
NaSARRI
14.6
CBSDRS
2019 to 2022
Multilocation
36.1
CBSDLI, cassava brown streak disease leaf incidence; CBSDLS, cassava brown streak disease leaf
severity; CBSDRI, cassava brown streak disease root incidence; CBSDRS, cassava brown steak
disease root severity; 3, 6, and 9, months after planting.
3.1.4. Virus Detection and Quantification
Cassava genotypes that showed leaf symptoms and root necrosis (Figure 6) were
excluded, while those with clean leaves and roots showing no observable CBSD
symptoms (Figure 7) were selected for virus detection. Virus detection and quantification
revealed the prevalence of CBSV and fewer UCBSV occurrences in both sites (Table 10).
The roots chosen for virus detection were selected during the root assessment, and the
sample with a score of 1 was selected.
Figure 6. CBSD-infected cassava leaves showing yellow chlorosis (A) and roots with brown lesions
(B).
Figure 6. CBSD-infected cassava leaves showing yellow chlorosis (A) and roots with brown le-
sions (B).
Agronomy 2024, 14, x FOR PEER REVIEW 14 of 19
Figure 7. Uninfected cassava leaves (A) and roots (B).
Table 10. CBSV and UCBSV detection at the NaSARRI and IITA.
Sample Type Location Sampled CBSV
UCBSV
CBSV &
UCBSV
Negative
Roots
NaSARRI_1
175
59
0
0
116
NaSARRI_2
61
37
1
0
24
IITA
85
73
1
0
8
Leaves
NaSARRI_2
63
11
2
1
52
IITA
74
36
0
0
38
NaSARRI_1, 2020/2021 harvest; NaSARRI_2, 2021/2022 harvest; IITA = 2021/2022 harvest.
UCBSV was observed on leaves at the NaSARRI and roots at the IITA. At the
NaSARRI site, one sample had co-infection with both CBSV and UCBSV on its leaves.
Root samples collected at the NaSARRI during season one had 66.3% uninfected
genotypes, whereas, during season two, 82.54% of leaves and 39.3% of roots were not
detected with the viruses. At the IITA, 51.35% of leaves and only 9.41% of root samples
collected were virus-free.
Based on the observed leaf symptoms, root necrosis, and virus detection, nine
genotypes were either most resistant (MR), resistant (R), most tolerant (MT), or tolerant
(T) to CBSD. Their phenotypes (apart from a root necrosis class score of 1–2) had negative
virus detection, low leaf incidence (less than 20%), and a maximum leaf severity score of
class 2 (Table 11). The genotypes MM160145, MM160582B, and MM160089A tested
negative (no cq) for leaf and root virus detection; however, they showed root symptoms
(necrosis), implying that they were infected by a new strain that current primers cannot
detect.
Sixteen asymptomatic genotypes, including the checks, were identified, with
MM160031 exhibiting asymptomatic positivity for both foliar and root necrosis (Table 12).
These observations were made at the IITA. The rest of the remaining genotypes displayed
asymptomatic positivity for either foliar symptoms or root necrosis at both sites (Table
12). The NAROCASS1 (IITA) and NAROCASS 2 (NaSARRI) check varieties were also
asymptomatically positive for root necrosis.
Table 11. Performance of nine of the most promising genotypes with ≤20% CBSD incidence and ≤2
CBSD severity, CBSDRS ≤ 2, CMD severity, and negative virus detection at the IITA and NaSARRI.
Genotype Pedigrees CBSDS3 CMDS3
CBSDS
6
CMDS6 CBSDS9
CMDS9 CBSDRS Status Location
MM160145
S1_MM060130
1
1
1
1
2
1
2
MT
both
MM161487
S1_MM060123
1
1
1
1
1
1
1
MR
both
MM160227
S1_MM060130
2
3
1
1
1
1
1
R
both
MM160582B
S1_MM060128
1
1
1
1
1
1
2
MT
both
MM161113 F1_MM060123XMM0601
30
1 1 1 1 1 1 1 MR NAS
Figure 7. Uninfected cassava leaves (A) and roots (B).
Table 10. CBSV and UCBSV detection at the NaSARRI and IITA.
Sample Type Location Sampled CBSV UCBSV CBSV &
UCBSV Negative
Roots
NaSARRI_1
175 59 0 0 116
NaSARRI_2
61 37 1 0 24
IITA 85 73 1 0 8
Leaves
NaSARRI_2
63 11 2 1 52
IITA 74 36 0 0 38
NaSARRI_1, 2020/2021 harvest; NaSARRI_2, 2021/2022 harvest; IITA = 2021/2022 harvest.
UCBSV was observed on leaves at the NaSARRI and roots at the IITA. At the NaSARRI
site, one sample had co-infection with both CBSV and UCBSV on its leaves. Root samples
collected at the NaSARRI during season one had 66.3% uninfected genotypes, whereas,
during season two, 82.54% of leaves and 39.3% of roots were not detected with the viruses.
At the IITA, 51.35% of leaves and only 9.41% of root samples collected were virus-free.
Based on the observed leaf symptoms, root necrosis, and virus detection, nine geno-
types were either most resistant (MR), resistant (R), most tolerant (MT), or tolerant (T) to
CBSD. Their phenotypes (apart from a root necrosis class score of 1–2) had negative virus
detection, low leaf incidence (less than 20%), and a maximum leaf severity score of class
2 (Table 11). The genotypes MM160145, MM160582B, and MM160089A tested negative
(no cq) for leaf and root virus detection; however, they showed root symptoms (necrosis),
implying that they were infected by a new strain that current primers cannot detect.
Table 11. Performance of nine of the most promising genotypes with
≤
20% CBSD incidence and
≤
2
CBSD severity, CBSDRS ≤2, CMD severity, and negative virus detection at the IITA and NaSARRI.
Genotype Pedigrees
CBSDS3 CMDS3 CBSDS6 CMDS6 CBSDS9 CMDS9 CBSDRS
Status
Location
MM160145 S1_MM060130 1 1 1 1 2 1 2 MT both
MM161487 S1_MM060123 1 1 1 1 1 1 1 MR both
MM160227 S1_MM060130 2 3 1 1 1 1 1 R both
MM160582B S1_MM060128 1 1 1 1 1 1 2 MT both
MM161113
F1_MM060123XMM060130
1 1 1 1 1 1 1 MR NAS
MM161247
F1_MM060123XMM060130
2 1 1 1 1 1 1 MR NAS
MM160089A S1_MM060130 1 1 1 1 1 1 2 MT IITA
Agronomy 2024,14, 2122 14 of 18
Table 11. Cont.
Genotype Pedigrees
CBSDS3 CMDS3 CBSDS6 CMDS6 CBSDS9 CMDS9 CBSDRS
Status
Location
MM160406
F1_MM060128XMM060130
1 3 1 3 1 1 1 T IITA
MM160530 S1_MM060128 1 1 1 1 2 1 1 MT IITA
CBSDS, cassava brown streak disease severity; CMDS, cassava mosaic disease severity; CBSDRS, cassava brown
streak disease root severity; 3, 6, and 9, months after planting; MR, most resistant; R, resistant; MT, most tolerant;
T, tolerant.
Sixteen asymptomatic genotypes, including the checks, were identified, with MM160031
exhibiting asymptomatic positivity for both foliar and root necrosis (Table 12). These observa-
tions were made at the IITA. The rest of the remaining genotypes displayed asymptomatic
positivity for either foliar symptoms or root necrosis at both sites (Table 12). The NAROCASS1
(IITA) and NAROCASS 2 (NaSARRI) check varieties were also asymptomatically positive for
root necrosis.
Table 12. Sixteen asymptomatic cassava genotypes (including two checks) at the IITA and NaSSARI.
Genotype Pedigrees CBSDL3S CBSDL6S
CBSDL6S CBSDRS
CBSV_L CBSV_R Location
MM160031 MM060130XMM060130 1 1 1 1 24.03 26.25 IITA
MM160371 MM060128XMM060130 1 1 1 1 No Cq 36.82 NaSARRI
MM160234 MM060130XMM060130 1 1 1 1 No Cq 31.92 IITA
MM161627 MM060128 HS 1 1 1 1 No Cq 29.52 IITA
MM160760 MM060123XMM060128 1 1 1 1 No Cq 34.27 NaSARRI
MM161145 MM060123XMM060130 1 1 1 1 No Cq 37.61 NaSARRI
MM160969 MM060123XMM060128 1 1 1 1 28.45 IITA
MM161030 MM060123XMM060128 1 1 1 1 29.26 IITA
MM160909 MM060123XMM060128 1 1 1 1 30.8 IITA
LTG 5 UNKNOWN 1 1 1 1 32.11 IITA
MM160668A MM060128XMM060128 1 1 1 1 28.68 IITA
NAROCASS1
NDL9036 1 1 1 1 36.66 IITA
MM160069 MM060130XMM060130 1 1 1 1 34.96 NaSARRI
MM160877 MM060123XMM060128 1 1 1 1 35.76 NaSARRI
NAROCASS2
Kitumbua 1 1 1 1 36.68 NaSARRI
MM160602 MM060128XMM060128 1 1 1 1 25.37 NaSARRI
CBSDLS, cassava brown streak disease leaf severity; CMDS, cassava mosaic disease severity; CBSDRS, cassava
brown streak disease root severity; 3 and 6, months after planting; CBSV_L, leaf samples quantified for CBSV;
CBSV_R, root samples quantified for CBSV.
4. Discussion
The genetic observed variation within and between populations in this study em-
phasized the role of the selfed populations in enhancing selection breeding. The results
indicated that resistance to CBSD was primarily controlled by an additive mode of gene
action, consistent with the previous studies by Chipeta et al. [
16
] and Nduwumuremyi
et al. [
14
]. Furthermore, identifying the genotypes most resistant to CBSD across vari-
ous locations highlighted the importance of utilizing different locations in the selection
process [31].
The performance of cassava genotypes under varying environmental conditions re-
vealed an essential dimension of their adaptability [
32
], enabling an assessment of the
performance of the genotypes for a range of traits. The significant differences (p< 0.05)
detected among the genotypes in response to both CBSD and CMD indicated a diverse
array of resistance levels among the genotypes. These variations hold significant implica-
tions for programs seeking to breed resistance against these two economically undesirable
diseases [
33
]. Consistent results were also observed for traits such as CBSDLS, CBSDRS,
and FRYLD, further strengthening the validity and robustness of the results. The repetition
of similar patterns across multiple traits underscored the stability of the findings and
enhanced the validity of the observed trend. Identifying the quantitative loci associated
with the resistance to CBSD will elucidate the genetic architecture of the resistance, paving
the way for further investigation.
The interaction between genotypes and the environment, particularly in the context of
CBSD, revealed the influence of quantitative traits [
34
], underscoring the multifaceted na-
ture of genotype-environment relationships, emphasizing the need for a nuanced approach
Agronomy 2024,14, 2122 15 of 18
in assessing and selecting genotypes for desired traits, and underscoring the complex inter-
play between genetics and the environment. This is crucial for informed decision-making
in cassava genotype selection for superior resistance to disease and overall performance.
The performance of the resistant parents at the IITA in 2019 showed similar mean
scores to the susceptible parents for CBSDLS, suggesting that prolonged drought might
directly contribute to weakening plant defenses in some resistant varieties within the
population [
35
]. This highlights the complexity of the interaction between drought stress
and plant susceptibility to CBSD. Deeper insights into how environmental factors such
as drought and soil conditions influence the expression of resistance traits are needed.
This will enable the development of cassava varieties that are resilient to biotic and abiotic
stresses. Additionally, developing environment-specific breeding strategies that account for
genotypes with specific adaptations to some local environmental conditions will enhance
resistance optimization and improve cassava yields.
The S1 and F1 results indicate that higher resistant gene accumulation might be
attainable from crosses between lines. However, resistance rather than through biparental
crosses of resistant and susceptible lines but resistant lines was also generated from a selfing
susceptible line (TME14XTME14), suggesting that CBSD resistance is likely recessive, as
reported by Sheat and Winter [
36
]. In addition, multiple genes conferring resistance
to CBSD were indicated by segregation patterns in F1 and S1 populations through the
distribution of the scores exhibiting similarities between crosses and S1s and indicating the
complex genetic basis of CBSD resistance. Identifying more resistant progeny from the S1
generation of MM160123 suggested the strong expression of the recessive alleles for the
resistance trait transferred from the parent MM160123.
The PV analysis demonstrated the allocation of total variation into GVs and EVs,
providing valuable insights into the underlying sources of variability that contributed to
the observed phenotypic variation. The high proportion of PVs indicated a strong environ-
mental influence on the traits under study, and a relatively low proportion of Genotypic
Variance Components (GVCs) was observed in some traits, particularly DMC, suggesting a
comparatively weak genetic influence on their expression [
37
]. This observation highlights
the potential for genetic improvement through hybridization, followed by rigorous selec-
tion, rather than relying solely on the phenotypic performance of individual genotypes.
Similar conclusions were reported by Nduwumuremyi et al. [
16
]. The substantial differ-
ences observed between the PCV and its corresponding GCV highlighted the significant
impact of environmental factors on the expression of these traits, indicating the sensitivity
of genotypes to environmental variations. This suggests that selecting genotypes based
solely on phenotypic performance may yield limited genetic improvements in traits due to
the confounding influence of environmental factors [38].
The general combining ability (GCA) and specific combining ability (SCA) analysis
provided valuable insights into the underlying gene effects and their interactions in the
expression of the studied traits. The GCA results indicated additive gene effects and
additive x additive interactions. On the other hand, SCA results suggested the dominance
and epistatic effects. The significance of GCA across all traits underscored the predominance
of additive genes in the expression of CBSDLS, CBSDRS, and FRYLD [
16
], CBSDLI [
17
],
and HI trait [
39
]. The non-significance of SCA for CBSDRI, CMDS, CMDI, HI, and DMC
indicated that parental interactions do not significantly influence the performance of their
hybrids, suggesting that additive gene effects are more influential than non-additive effects.
The high positive GCA/SCA ratio indicated that additive gene effects contributed to
shaping the expression of the studied traits, underscoring the substantial role of additive
genetic components in the variability of these traits.
The predominance of additive gene effects suggested that recurrent selection is an
effective breeding strategy for increasing the frequency of favorable alleles for CBSD in
cassava populations.
Across different seasons and locations, most heritability estimates were low, suggesting
the pronounced influence of environmental factors [
40
]. However, at a specific location,
Agronomy 2024,14, 2122 16 of 18
moderate to high broad sense heritability estimates were recorded for the CBSD trait,
indicating a stronger genetic influence on the expression of this trait in that environment
and implying that improvement through simple selection could be a viable approach for
enhancing CBSD resistance, as suggested by Kayondo et al. [41].
We underscored the resistance level of several CBSD-resistant genotypes, including
MM160145, MM161487, MM160227, and MM160582B, which exhibited minimal foliar
symptoms and root necrosis (
≤
2). These genotypes came from the full-sib population of
CBSD-resistant, MM060123, MM060128, and MM060130 parents. The resistance observed
in these genotypes was derived from S1 populations, surpassing the performance of their S0
parents. Similar results were reported by Pariyo et al. [
42
] and Kaweesi et al. [
43
], indicating
the effectiveness of utilizing S1 populations for breeding resistance to CBSD. The stability
of the four genotypes across contrasting environments indicates the potential for making
genetic progress in CBSD resistance through inbreeding.
The root necrosis in genotypes that tested negative for the CBSD virus on roots and
leaves indicated that root necrosis might be caused by a distinct virus biotype that could
not be detected by the primers used. This study was limited by the inability to develop
primers that matched the observed results. Additionally, the coexistence of genotypes that
tested positive for CBSD on leaves but negative on roots indicated the virus concentration
in the leaves, possibly because the virus had not yet reached the roots or the roots had
developed resistance mechanisms. Conversely, genotypes testing positive for CBSD on
roots but negative on leaves suggested differential resistance mechanisms between the two
plant parts. Shirima et al. [
27
] reported similar observations. Understanding the molecular
and physiological basis of these differential resistance mechanisms is important, as this
knowledge can lead to more targeted breeding efforts and the development of cassava
varieties with comprehensive resistance profiles.
5. Conclusions
This study finds that selfed populations exhibit strong recessive allele expression
and greater resistance than their parental lines, making them valuable for enhancing
resistance breeding. Additionally, the use of cassava genotypes MM161487, MM160227,
MM170098, MM160582B, and MM160145 have demonstrated significant potential for high
yield and resistance to CBSD and CMD, positioning them as key candidates for future
breeding programs.
Supplementary Materials: The following supporting information can be downloaded at
https://www.mdpi.com/article/10.3390/agronomy14092122/s1, Figure S1: The total monthly rain-
fall and average monthly temperature. Average monthly temperature (
◦
C) and total monthly rainfall
(mm) for Serere (A) and Sendusu (B); Figure S2: Amplification plots and standard curve. PCR
amplification plots and the standard curve of serial dilution of linearized plasmid from Taqman assay
probe chemistry. A: Amplification plots of CBSV clone (pFer2) and B: the standard curves of CBSV
clone (pFer2). The efficiency of amplification was 104.8%, and the coefficient of correlation of 0.999
with a slope of −3.21 was achieved for CBSV absolute quantification.
Author Contributions: Conceptualization, K.L.S. and H.K.; Data curation, K.L.S.; Formal analysis,
K.L.S. and S.I.K.; Funding acquisition, H.K., R.E. and E.K.; Investigation, K.L.S.; Methodology, K.L.S.
and M.A.O.; Project administration, E.K. and H.K.; Resources, E.K., R.E. and H.K.; Validation, R.E.;
Supervision, E.K., P.R. and S.I.K.; Visualization, K.L.S. and R.E.; Writing—original draft, K.L.S.;
Writing, review and editing, K.L.S., P.R., E.K., S.I.K. and M.A.O. All authors have read and agreed to
the published version of the manuscript.
Funding: This research was funded by Cornell University through a sub-award agreement (N0.84941-
11056) between TARI and Cornell University through the Next Generation Cassava Breeding Project.
Data Availability Statement: The data presented in this study are available upon request from the
corresponding author because of legal and institutional regulations. The data are part of ongoing
research projects; sharing them may compromise the integrity of these studies and violate data
usage agreements.
Agronomy 2024,14, 2122 17 of 18
Acknowledgments: The NextGen cassava Project provided a research grant to the Makerere Regional
Centre for Crop Improvement (MaRCCI) for the first author’s research and training. The International
Institute for Tropical Agriculture (IITA), Uganda, hosted field experiments at their experimental field
stations and provided field assistance. IITA Dar es Salaam provided the necessary equipment for
virus activity analysis in their Biotechnology Laboratory.
Conflicts of Interest: The authors declare no conflicts of interest.
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