COMPARISON OF PHENOTYPIC AND GENOMIC SELECTION APPROACHES TO IDENTIFY PROMISING HYBRID PARENTAL LINES FOR YIELD AND NUTRITIONAL TRAITS IN PEARL MILLET [Pennisetum glaucum (L.) R. BR.]
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Date
2024-01-12
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PROFFESSOR JAYASHANKAR TELANGANA STATE AGRICULTURAL UNIVERSITY
Abstract
Pearl millet (Pennisetum glaucum (L.) R. Br. syn. Cenchrus americanus (L.)
Morrone) is a climate-resilient crop grown in the arid and semi-arid areas of the world.
It is the most widely grown millet species, accounting for approximately half of the total
worldwide production of millets. It can grow on poor soils with little or no inputs and it
has resistance or tolerance to many crop diseases and pests and can survive in adverse
climatic conditions. Pearl millet also known for nutritional security as it is the rich
source of Fe and Zn content. Pearl millet is most useful crop because of its nutritional
potential, multipurpose use as feed and fodder and as climate change ready crop with its
ability to sustain in harsh environmental conditions like drought and heat, has enormous
potential to give higher returns in marginal environments for poor farmers. Plant
breeders are constantly challenged to come up with new breeding techniques to
maximise selection gain per year. In large segregating material, it is critical to select the
best genotypes which act as parental lines in hybrid development programs. Here
breeders apply different selection strategies to screen and select best parental lines.
These strategies may be by the conventional approaches based on phenotypic data only
or/and by molecular approaches, where exploiting the same phenotypic data by adding
information from molecular markers. The present investigation was carried out during
summer-2020 to kharif-2021 at International Crops Research Institute for the Semi-arid
Tropics (ICRISAT), Hyderabad. The objective of the study was to compare selection
methods based on phenotypic and genomic information to derive hybrid parental lines
having high productivity and better nutritional traits, to investigate the optimum number
of testers required to select superior hybrid parental lines and to identify heterosis and
combining ability effects of hybrid parental lines.
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A study was conducted to compare selection efficiency of four selection
methods for selection of superior hybrid parental lines for grain yield and nutritional
traits. Among them general combining ability (gca), per se performance and visual
selection methods were phenotypic information-based selection methods and genomic
selection is genotypic information-based section method. The study was conducted on
two sets of hybrid parental lines, which consist of 72 seed parental (B) lines (Set-I) and
73 restorer (R) lines (Set-II). These parental lines were crossed with 2 respective testers,
generated hybrids and parental lines were evaluated in multilocation trials. Parental
lines were genotyped by t-GBS technique with 1217 mid density SNP markers. The
breeding values of parental lines were estimated by genomic best linear unbiased
prediction (GBLUP) model. Prediction accuracy of the model was ranged between 0.21
to 0.87. In both sets, from each selection method, top 10% lines were selected and
crossed with 5 testers and generated hybrids were evaluated in diverse agroclimatic
zones. The selection efficiency of methods was determined 1) by comparing the mean
performance of the top five (5), ten (10), twenty (20), and all hybrids developed by each
selection method 2) by comparing line contribution by each selection method in top
performing hybrids and 3) by cost-benefit analysis.
Comparison of mean performance revealed that in all four comparison groups
(top 5, 10, 20, and all hybrids) of set-I and set-II, hybrids developed by general
combining ability (GCA) performed better than other selection methods. In set-I,
hybrids developed by visual selection method showed superior performance after GCA
and in set-II, genomic selection showed superior performance after GCA. A paired t-test
was conducted to check the significant difference between selection methods for mean
grain yield performance of top 5, 10, 20 and all hybrids advanced by the four selection
methods. In Set-I, in all groups (top 5, 10, 20 and all hybrids advanced by methods) no
significant difference between selection methods was observed. Whereas as in Set-II,
except in all hybrids group, 1) no significant difference between general combining
ability and genomic selection, 2) no significant difference between per se performance
and agronomic score, 3) significant difference between GCA and GS methods with per
se performance and visual selection methods was observed. These results suggest that
selection efficiency of all four selection methods is similar, but among the four
methods, selection efficiency of genomic selection and GCA may be similar and
superior to per se performance and visual selection methods. Rank correlation analysis
between selection methods in both Set-I (B-lines) and Set-II (R-lines) revealed 1)
significant positive correlation between genomic selection and general combining
ability methods 2) significant positive correlation between per se performance and
visual selection methods 3) no correlation between GS and GCA methods with per se
performance and visual selection methods. This result also supports the similar selection
efficiency of GS and GCA selection methods. Cost benefit analysis indicated that initial
implementation of genomic selection costs more compared to other selection methods
due to requirement of both genotypic and phenotypic data to train the model. Once the
model is available then only genotypic data is sufficient to estimate the breeding value
of parental lines so cost involved in genomic selection will be reduced drastically. Then
genomic selection would be 74% cheaper than GCA method. The visual selection
method is the most affordable method among the four selection strategies.
Comparison of three selection methods (gca, per se performance and genomic
selection) for combination of grain yield and grain Fe content was done in seventy-two
(72) seed parental lines (B-lines). Top 10% lines from each method with the
combination of grain yield and Fe content was selected and crossed with 5 testers and
generated hybrids were evaluated in four locations. It was observed that in all three
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comparison groups (top 5, 10 and all hybrids) for grain yield, hybrids generated by
general combing ability performed best compared to other selection methods, whereas
for grain Fe content in each comparison group not much difference was observed
between selection methods. This result suggests that for grain yield, selection efficiency
of general combining ability is higher followed by per se performance and genomic
selection, but for grain Fe content, selection efficiency of all three methods is similar.
Cost-benefit analysis for grain yield and Fe content revealed that initially genomic
selection costs more compared to other selection methods, because of the requirement
of phenotypic and genotypic data, once the model is trained genomic selection would be
89% cheaper than gca. Then GS will be the most cost-effective selection method for
selection of parental lines for both grain yield and nutritional traits.
Optimum number of testers study was conducted to find out the number of
testers required from a set of 5 testers for selection of parental lines. With different
possible combinations of 5 testers, 31 testcross combinations were framed. Based on
mean grain yield performance of hybrids, top 10 lines from each of 31 combinations
were selected. It was observed that 4 B-lines (line 1, 13, 16 and 17) in Set-I and 3 R
lines (line 1, 2, 5) in Set-II were commonly selected in across testcross combinations.
Based on mean grain yield hybrid performance, top 5 lines from 5 tester combination
were selected. Then these lines were compared for their presence in top 5 lines of
testcross combinations of each tester group. In Set-I, the average chance of selecting top
5 lines of 5 tester combination by one, two, three and four tester groups are 56%, 66%,
76% and 92% respectively, whereas in Set-II, average chance observed as 52%, 62%,
74% and 84% respectively. Correlation analysis between mean grain yield of testcross
combinations in both sets revealed the less correlation of single tester combinations
with two or more tester combinations, but two or more tester group combinations
showed more significant positive correlation with other testcross combinations. Line x
tester biplot analysis was done to estimate the discriminating ability of 5 R-line testers
in Set-I and 5 B-line testers in Set-II for grain yield, grain Fe content and Zn content.
Based on vector length in biplot graph, in Set I, following testers have higher
discriminating ability: ICMR 1203 and ICMR 14888 for grain yield, ICMR 1202 and
ICMR 15222 for grain Fe content, and ICMR 1203 and ICMR 15222 for grain Zn
content. In case of Set II, following testers have higher discriminating ability: ICMB
04999 and ICMB 1508 for grain yield, ICMB 04999 and ICMB 98222 for grain Fe
content, and ICMB 04999 and ICMB 1508 for grain Zn content.
Combining ability and standard heterosis study was conducted in two stages of
material using line x tester analysis. Stage-I comprised of 84 B-lines and 75 R-lines,
which were crossed with 2 testers and stage-II comprised of 22 B-lines and 25 R-lines,
which were crossed with 5 testers. Generated hybrids were evaluated in four locations.
The analysis of variance for combining ability in both stages revealed the presence of
significant difference among the lines, testers and their hybrids for all the traits under
the study. In stage-I, out of 84 B-lines, 15 lines for grain yield, 29 for grain Fe content
and 20 lines for Zn content, 29 lines for days to 50% flowering, 25 lines for plant height
and 14 lines for 1000-seed weight have shown significant GCA effects in desirable
direction. Among them, ICMB 101716 and ICMB 18777 were found to be good
combiners for grain yield, grain Fe and Zn content. Out of 75 R-lines, 24 lines for days
to 50% flowering, 24 lines for plant height, 12 lines for 1000-seed weight, 23 lines for
grain yield, 32 lines for Fe content and 19 lines for Zn content showed significant GCA
effects in desirable direction. Among them, ICMR 100152 and ICMR 102502 were
identified as promising lines with significant GCA effects for all the traits except for
days to 50% flowering. Four lines (ICMR 1701, ICMR 1907, ICMR 100152, and ICMR
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102502) have shown significant GCA effects for grain yield, grain Fe content and Zn
content.
In stage-II, out of 22 B-lines, 9 lines for days to 50% flowering, 9 lines for plant
height, 6 lines for 1000-seed weight, 7 lines for grain yield, 6 lines for Fe content and 5
lines for Zn content were as significant good combiners in desired direction. ICMB
101810 was found to be as promising line with significant GCA effects for all traits
except Fe content. ICMB 101793 has shown significant GCA effects for grain yield and
grain Fe content along with other agronomic traits. Out of 25 R-lines, 8 lines for days to
50% flowering, 11 lines for plant height, 7 lines for 1000-seed weight, 5 lines for grain
yield, 12 lines for Fe content and 7 lines for Zn content showed significant GCA effects
in desired direction. Parental lines ICMR 101206 and ICMR 102502 are promising lines
with significant GCA effects for grain yield, Fe content and Zn content. Across two
stages, 7 parental lines including 3 B-lines (ICMB 101810, ICMB 101793 and ICMB
17333) and 4 R-lines (ICMR 101206, ICMR 102502, ICMR 102506 and ICMR
102149) were significant good combiners for grain yield, nutritional and agronomic
traits.
An estimation of SCA effects of crosses in pooled analysis revealed that in
stage-I, hybrids ICMA 19222 x ICMR 1202 and ICMA 101790 x ICMR 1203 were
observed as best hybrid combinations with significant positive SCA effects for grain
yield. For grain Fe and Zn content, 27 and 12 hybrid combinations showed significant
positive SCA effects respectively. Hybrid, ICMA 04999 x ICMR 100048 has been
identified as best combination with significant SCA effects for grain yield, Fe content,
days to 50% flowering and 1000-seed weight. Five hybrids, ICMA 04999 x ICMR
100048, ICMA 04999 x ICMR 1804, ICMA 04999 x ICMR 15555, ICMA 04999 x
ICMR 100004 and ICMA 04999 x ICMR 102503 have significant SCA effects for both
grain yield and Fe content.
In stage-II, out of 103 B-line hybrids, 8 hybrids showed significant positive SCA
effects for at least 2 traits along with grain yield. Hybrid ICMA 101780 x ICMR 14888
is the best combination with significant positive SCA effects for grain yield, plant
height and 1000-seed weight. Out of 115 R-line hybrids, 5 crosses for days to 50%
flowering, 18 crosses for plant height, 6 crosses for 1000-seed weight, 18 crosses for
grain yield, 11 crosses for grain Fe content and 9 crosses for Zn content showed
significant SCA effects in desirable direction. Among them 8 crosses showed
significant positive SCA effects for at least two traits along with grain yield.
Standard heterosis analysis revealed that in stage-I out of 168 B-line hybrids, for
grain yield, 5 hybrids (ICMA 101795 x ICMR 1203, ICMA 101838 x ICMR 1202,
ICMA 17333 x ICMR 1203, ICMA 101828 x ICMR 1203 and ICMA 101832 x ICMR
1203) showed positive standard heterosis over 86M84, 10 hybrids showed positive
standard heterosis over Kaveri super boss and 31 crosses showed significant positive
standard heterosis over ICMH 1202. For grain Fe content, 8 hybrids showed significant
positive standard heterosis over ICMH 1202 which is the major check for Fe and Zn
content. In stage II, out of 103 B-line hybrids for grain yield, 6 hybrids showed
significant positive standard heterosis for grain yield over ICMH 1203. Hybrids ICMA
101794 x ICMR 1202 and ICMA 101780 x ICMR 1203 showed significant positive
standard heterosis over ICMH 1203 for Fe content and Zn content respectively. Out of
115 R-line hybrids for grain yield, 7 hybrids over 86M84, one hybrid over Kaveri Super
Boss and 8 hybrids over MP7171 showed positive standard heterosis and 5 hybrids
showed significant positive standard heterosis over ICMH 1203. For grain Fe content,
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23 hybrids showed positive standard heterosis and no hybrid showed significant positive
standard heterosis over ICMH 1203. For Zn content 3 hybrids (ICMA 1508 x ICMR
102149, ICMB 98222 x ICMR 102149 and ICMA1 98222 x ICMR 102503) showed
significant positive standard heterosis for grain Zn content over ICMH 1203. These
promising hybrids and parental lines will be further tested for combination of yield and
nutritional superiority and used in line breeding and hybrid development in ICRISAT
pearl millet breeding program.