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Association study between microsatellite genotypes and layer performances in Rhode Island Red chicken

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This investigation aimed to study association between microsatellites and layer performances in Rhode Island Red selected line chicken. Genomic DNA samples isolated from the 12 randomly selected birds were investigated at 24 microsatellite loci. The microsatellite alleles were separated on 6% urea-PAGE and their molecular sizes were estimated. Locus specific alleles were identified according to their sizes, and their association with layer performance traits was assessed by least squares analysis of variance. Analysis revealed that age at sexual maturity of the birds had significant influence of 180bp/190bp and 184bp/196bp microsatellite genotypes in MCW0075 locus. Egg weight at 28th week of age was significantly associated with 210bp/244bp, 216bp/216bp, 216bp/238bp, 222bp/244bp genotypes in MCW0005; and 173bp/173bp, 175bp/175bp, 177bp/177bp in MCW0014. Egg production upto 40 weeks of age was also significantly associated with some genotypes in MCW0044 (133bp/151bp, 136bp/ 160bp), ADL0102 (136bp/166bp, 146bp/174bp, 166bp/166bp) and ADL0158 (178bp/214bp, 184bp/184bp, 184bp/ 214bp, 184bp/222bp). MCW0051 (90bp/118bp, 105bp/118bp, 118bp/118bp), MCW0014 (173bp/173bp, 175bp/ 175bp, 177bp/177bp) and ADL0176 (200bp/200bp, 200bp/236bp, 202bp/202bp) demonstrated significant influences on body weight at 40th week of age. Findings suggested faster genetic progress in RIR flocks by adapting microsatellite genotype based selection.
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*Part of Ph.D. thesis of first author
Present address: 1Subject Matter Specialist (Animal Science)
(dasugenvet@gmail.com), Howrah Krishi Vigyan Kendra,
Jagatballavpur, Howrah, West Bengal. 2Principal Scientist
(skgicar@gmail.com). 3Research Associate (choudhary633
@gmail.com), Artificial Breeding Research Centre, National
Dairy Research Institute, Karnal, Haryana. 4Assistant Director
(kokatels@gmail.com), MAFSU Sub-Centre, Udgir, Latur,
Maharashtra.
Microsatellite markers are extensively used in assessing
genetic structure, genetic diversity and relationship analyses
(Zhou et al. 2008). They are ideal for deciphering genetic
variability (Zhou et al. 2008) and provide a powerful tool
for marker-assisted selection (MAS) and QTL research
(Sewalem et al. 2002). The Rhode Island Red (RIR) chicken
population brought at the Central Avian Research Institute
almost 3 decades ago was well adopted, acclimatized and
genetically improved over last 33 years covering 29
generations of selection and being maintained as selected
line. The population has shown positive response for egg
production on long term selection based on part-period egg
production (Anonymous 2011), which however has been
slowing down in the last few generations, probably due to
reduction in genetic variability (Das et al. 2015a). Faster
genetic progress is possible using genomics data, which
may impact on layer breeding in the future (Albers and Van
Indian Journal of Animal Sciences 86 (9): 1021–1024, September 2016/Article
Association study between microsatellite genotypes and layer
performances in Rhode Island Red chicken*
ANANTA KUMAR DAS1, SANJEEV KUMAR2, ABDUL RAHIM3 and LAXMIKANT SAMBHAJI KOKATE4
ICAR-Central Avian Research Institute, Izatnagar, Uttar Pradesh 243 122 India
Received: 19 January 2016; Accepted: 17 February 2016
ABSTRACT
This investigation aimed to study association between microsatellites and layer performances in Rhode Island
Red selected line chicken. Genomic DNA samples isolated from the 12 randomly selected birds were investigated
at 24 microsatellite loci. The microsatellite alleles were separated on 6% urea-PAGE and their molecular sizes
were estimated. Locus specific alleles were identified according to their sizes, and their association with layer
performance traits was assessed by least squares analysis of variance. Analysis revealed that age at sexual maturity
of the birds had significant influence of 180bp/190bp and 184bp/196bp microsatellite genotypes in MCW0075
locus. Egg weight at 28th week of age was significantly associated with 210bp/244bp, 216bp/216bp, 216bp/238bp,
222bp/244bp genotypes in MCW0005; and 173bp/173bp, 175bp/175bp, 177bp/177bp in MCW0014. Egg production
upto 40 weeks of age was also significantly associated with some genotypes in MCW0044 (133bp/151bp, 136bp/
160bp), ADL0102 (136bp/166bp, 146bp/174bp, 166bp/166bp) and ADL0158 (178bp/214bp, 184bp/184bp, 184bp/
214bp, 184bp/222bp). MCW0051 (90bp/118bp, 105bp/118bp, 118bp/118bp), MCW0014 (173bp/173bp, 175bp/
175bp, 177bp/177bp) and ADL0176 (200bp/200bp, 200bp/236bp, 202bp/202bp) demonstrated significant influences
on body weight at 40th week of age. Findings suggested faster genetic progress in RIR flocks by adapting
microsatellite genotype based selection.
Key words: Association, Body weights, Egg production, Egg weights, Microsatellite genotypes, RIR chicken
Sambeek 2002). Hence, the present investigation was
carried out with the avowed objective of association study
between microsatellites and layer performances in RIR
selected line chicken.
MATERIALS AND METHODS
Birds (12) were randomly chosen from RIR selected line
chicken maintained at the Central Avian Research Institute,
Izatnagar. Their genomic DNA samples were extracted as
detailed in earlier literatures (Das et al. 2015a, 2015b) and
PCR ready DNA samples were prepared at a concentration
of 50 ng/µl. FAO (2011) recommended 24 microsatellite
loci as detailed in earlier literatures (Das et al. 2015a, 2015b)
were used for present study. The chicken specific
microsatellite synthesized primers (Custom Oligos, 0.01
µM) were obtained commercially and their annealing
temperatures were optimized as per Wimmers et al. (2000).
The PCR reactions and amplifications were carried out using
these DNA samples for each microsatellite marker as
detailed in earlier literatures (Das et al. 2015a, 2015b). The
molecular sizes of amplified products were adjudged for
their probable sizes through 1.4% horizontal agarose gel
electrophoresis (Das et al. 2015a, 2015b). The microsatellite
alleles were then identified by running the amplified
products on vertical denaturing polyacrylamide gel
electrophoresis (6% urea-PAGE) (Das et al. 2015a, 2015b)
1022 DAS ET AL.[Indian Journal of Animal Sciences 86 (9)
50
followed by silver staining (Beidler et al. 1982). Molecular
sizes of various alleles at different microsatellite loci were
determined using the Quantity One software on GelDoc
2000. The observed alleles in each sample at each
microsatellite loci and its probable genotypes were recorded.
Locus specific alleles were identified according to their
molecular sizes and assigned names from alphabet A to H
in ascending order of their molecular sizes.
The layer performances i.e. body weight at 20th weeks
of age (BW20), age at sexual maturity (ASM), egg weights
at 28 and 40th week of age (EW28, EW40), body weight at
40th week of age (BW40) and part period egg production
upto 40 weeks of age (EP40) were recorded.
The performance data recorded on the experimental birds
was analyzed for assessing their association with
microsatellite alleles by least squares analysis of variance
(Harvey 1990), incorporating microsatellite locus as fixed
effect in the statistical model:
Yjk = µ + Mj + ejk
where, Yjk, observation of kth individual of jth
microsatellite locus; µ, population mean; Mj, fixed effect
of jth microsatellite locus; ejk, random error associated with
mean zero and variance ó2. Critical Difference (CD) test at
the 5% level of probability of significance was performed
for assessing critical differences among the least squares
means under microsatellite genotypes.
RESULTS AND DISCUSSION
The Least squares analysis of variance elucidates that
some specific microsatellite genotypes in loci out of 24 loci
investigated in this study had significant (P<0.05) influence
on performance traits and are presented in Table 1.
Part period egg production upto 40 weeks of age (EP40)
was found to be significantly associated with some specific
microsatellite genotypes of loci MCW0044, ADL0102 and
ADL0158 (Table 1) in agreement to the earlier report (Das
et al. 2013). Similarly, body weight at 40th week of age
(BW40) was significantly influenced by loci MCW0051,
MCW0014 and ADL0176; age at sexual maturity (ASM)
by MCW0075; and egg weight at 28th week of age (EW28)
by MCW0005 and MCW0014 (Table 1) in agreement to
the earlier report (Das et al. 2013). In accordance to these
present findings, previously few workers also reported
significant association of some microsatellite alleles/
genotypes with age at sexual maturity (Van Kaam et al.
1999, 1998), body weights (Boschiero et al. 2009, Jennen
et al. 2006, Pandya et al. 2005, Van Kaam et al. 1999, 1998),
egg weights (Chatterjee et al. 2008, Van Kaam et al. 1999,
1998), and egg production (Chatterjee et al. 2010,
2008,Wardecka et al. 2002, Van Kaam et al. 1999, 1998) in
different chicken genotypes.
Critical Difference test (Table 2) demonstrated that the
microsatellite genotype DG heterozygote of MCW0044
locus had significantly higher EP40 than CF heterozygote
of the locus. BD and DD heterozygotes of MCW0051 locus
were statistically indifferent for BW40, though they had
significantly higher BW40 than CD heterozygote of the
locus. CF heterozygote of MCW0075 locus had
significantly lower ASM than BE heterozygote of the locus.
AE and BD heterozygotes of MCW0005 locus were
statistically indifferent for EW28, though they had
significantly higher EW28 than either CE heterozygote or
BB homozygote of the locus, CE and BB being statistically
indifferent. AA homozygote of MCW0014 locus had
significantly higher EW28 than either BB or CC
homozygotes of the locus, BB and CC being statistically
indifferent. Again, AA homozygote of MCW0014 locus had
significantly the highest BW40 followed by CC and BB
Table 1. Least squares analysis of variance of various layer performance traits under different microsatellite
loci in RIR selected line chicken
Source of variation df Mean sum of squares
BW20 ASM EW28 BW40 EW40 EP40
MCW 0044 1 19837.5 600.0 0.04 30104.2 0.04 1410.7**
Remainder 6 28875.0 170.3 7.1 17013.9 14.1 82.6
MCW 0051 2 8583.8 128.4 7.2 50093.8* 8.6 398.4
Remainder 5 35184.0 273.0 5.7 6400.0 13.5 221.8
MCW 0075 1 104.2 864.0* 12.0 8437.5 15.0 600.0
Remainder 6 32163.9 126.3 5.1 20625.0 11.6 217.7
MCW 0005 3 17470.8 170.0 11.9* 25104.2 15.6 292.0
Remainder 4 35168.8 278.0 1.8 14218.8 9.5 257.5
MCW 0014 2 12223.2 71.3 9.1* 36160.7* 10.7 185.1
Remainder 4 38781.3 338.4 1.3 2812.5 13.5 360.8
ADL 0102 2 4580.4 470.5 10.5 13348.2 15.6 595.7*
Remainder 4 41781.3 125.6 2.7 14218.8 9.1 75.5
ADL 0158 3 15640.3 368.1 0.13 21423.6 2.1 563.8*
Remainder 4 36541.7 129.4 10.6 16979.2 19.7 53.6
ADL 0176 2 18223.2 90.8 8.1 33348.2* 10.7 215.7
Remainder 4 35781.3 328.6 1.8 4218.8 13.5 345.5
* P<0.05; ** P<0.01; *** P<0.001. BW20/BW40, body weight in g at 20/40th week of age; ASM, age at sexual maturity in days;
EW28/EW40, egg weight in g at 28/40th week of age; EP40, part period egg production in numbers upto 40 weeks of age.
September 2016] MICROSATELLITES-PERFORMANCE ASSOCIATION IN RIR CHICKEN 1023
51
homozygotes of the locus. DD homozygote of ADL0102
locus had significantly higher EP40 than either BE or AD
heterozygotes of the locus, BE and AD being statistically
indifferent. DD homozygote of ADL0158 locus had
significantly higher EP40 than either CG or DH or DG
heterozygotes of the locus, CG and DH or DH and DG being
statistically indifferent. CE heterozygote of ADL0176 locus
had significantly higher BW40 than either DD or CC
homozygotes of the locus, DD and CC being statistically
indifferent. The present findings were in the line of earlier
reports of few researchers namely Chatterjee et al. (2010,
2008) and Pandya et al. (2005). One-to-one correspondence,
in the form of significance, between microsatellites and
phenotypes like age at sexual maturity, body weights, egg
weights and egg production traits may be the informative
indicator for elucidating QTL and microsatellite
relationships (Chatterjee et al. 2010). The genetic principle
of significant association of microsatellites and phenotypes
is possibly due to the phenomenon of linkage and if the
microsatellite be very closely linked (about 20 cM) with a
certain phenotype, it will specifically be observed in terms
of a significant association (Chatterjee et al. 2010) which
was observed in the present study, though the linkage
analysis (using the CRI-MAP program package) was not
carried out in this study because it would thrive to carry
out a research with a large number of samples to associate
microsatellite alleles with performance traits in more
accuracy.
It may be concluded that microsatellite alleles are
associated with performance traits suggesting faster genetic
progress in layer flocks by adapting microsatellite genotype
based selection. The results paved way for utilization of
microsatellite markers in molecular breeding for rapid
genetic improvement in layer chicken performance.
However, further study may be taken on larger sample size
to reach definite conclusion.
ACKNOWLEDGEMENT
The Indian Veterinary Research Institute-Fellowship for
pursuing first author’s Ph.D. programme is sincerely
acknowledged. The authors are thankful to the Head of the
Division of Avian Genetics and Breeding, CARI, Izatnagar
for providing the necessary facilities for this work.
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Table 2. The estimated least squares means of various layer performance traits under different
microsatellite (MS) genotypes in RIR selected line chicken
Microsatellite MS genotypes Least squares means ± standard errors
loci
Code allele:allele BW20 ASM EW28 BW40 EW40 (g) EP40
bp : bp (g) (days) (g) (g) (g) (nos.)
MCW 0044 CF 133:151 1600.00±69.37 163.50±5.33 44.83±1.09 1808.33±53.25 53.17±1.54 85.33±3.71b
DG 136:160 1715.00±120.16 143.50±9.23 45.00±1.89 1950.00±92.23 53.00±2.66 116.00±6.43a
MCW 0051 BD 90:118 1750.00±187.57 146.00±16.52 48.00±2.39 2050.00±80.00a57.00±3.68 112.00±14.89
CD 105:118 1616.00±83.89 162.40±7.39 44.00±1.07 1760.00±35.78b52.60±1.65 85.60±6.66
DD 118:118 1600.00±132.64 155.00±11.68 45.50±1.69 1950.00±56.57a52.50±2.60 102.0±10.53
MCW 0075 BE 180:190 1635.00±126.82 176.50±7.95b47.00±1.60 1900.00±101.55 55.50±2.41 78.00±10.43
CF 184:196 1626.67±73.22 152.50±4.59a44.17±0.93 1825.00±58.63 52.33±1.39 98.00±6.02
MCW 0005 AE 210:244 1520.00±187.53 169.00±16.67 49.00±1.35a2050.00±119.24 56.00±3.08 84.00±16.05
BB 216:216 1680.00±187.53 141.00±16.67 42.0±1.35b1850.00±119.24 49.00±3.08 120.0±16.05
BD 216:238 1750.00±132.61 165.00±11.79 46.50±0.95a1900.00±84.32 56.00±2.18 92.00±11.35
CE 222:244 1582.50±93.77 157.00±8.34 43.75±0.67b1762.50±59.62 52.00±1.54 89.00±8.02
MCW 0014 AA 173:173 1750.00±196.93 146.00±18.40 48.00±1.15a2050.00±53.03a57.00±3.67 112.0±19.00
BB 175:175 1565.00±139.25 159.50±13.01 44.50±0.81b1725.00±37.50c52.00±2.60 92.50±13.43
CC 177:177 1657.50±98.47 158.50±9.20 43.25±0.57b1800.00±26.52b52.00±1.84 90.75±9.50
ADL 0102 AD 136:166 1635.00±144.54 176.50±7.93 47.00±1.16 1900.00±84.32 55.50±2.14 78.00±6.14b
BE 146:174 1582.50±102.20 157.00±5.60 43.75±0.82 1762.50±59.62 52.00±1.51 89.00±4.35b
DD 166:166 1680.00±204.41 141.00±11.21 42.00±1.64 1850.00±119.24 49.00±3.02 120.00±8.69a
ADL 0158 CG 178:214 1565.00±135.17 159.50±8.04 44.50±2.31 1725.00±92.14 52.00±3.14 92.50±5.18b
DD 184:184 1715.00±135.17 143.50±8.04 45.00±2.31 1950.00±92.14 53.00±3.14 116.00±5.18a
DG 184:214 1750.00±191.16 184.00±11.38 45.00±3.26 1750.00±130.30 55.00±4.44 72.00±7.32c
DH 184:222 1573.33±110.37 159.33±6.57 45.00±1.88 1883.33±75.23 53.33±2.56 85.00±4.23bc
ADL 0176 CC 200:200 1582.50±94.58 157.00±9.06 43.75±0.67 1762.50±32.48b52.00±1.84 89.00±9.29
CE 200:236 1750.00±189.16 146.00±18.13 48.00±1.35 2050.00±64.95a57.00±3.67 112.0±18.59
DD 202:202 1715.00±133.76 162.50±12.82 43.50±0.95 1800.00±45.93b52.00±2.60 96.00±13.14
Means within a microsatellite locus having different superscripts differ significantly (P<0.05); BW20/BW40, body weight in g at
20/40th week of age; ASM, age at sexual maturity in days; EW28/EW40, egg weight in g at 28/40th week of age; EP40, part period egg
production in numbers upto 40 weeks of age.
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... There a useful method in determining genetic variation and its association with economic traits of domestic birds [12,13] where a number of microsatellite markers were used as a means of selection in laying hens and broiler. [14,15] also used microsatellite markers to know their effect on egg production in Egyptian domestic chickens. Therefore, the study aimed to know the effect of the genotype marker LEI0258 on some productive traits and to study the genetic diversity in Iraqi local chickens. ...
... The results in Table (4) indicated that there were no significant differences in consumption periods (14,28,42) production, respectively also showed that there were significant (P ≤ 0.05 ) differences The results also showed that there were no significant differences in the seventh and last productive period (98, 100), respectively .As for the presence of significant differences between the alleles, the reason for this may be due to following a good management system by controlling the temperature and following ventilation and lighting programs as recommended or disease. The positive effect on this trait can be used in genetic improvement and selection experiment. ...
... The results in Table (8) revealed that there were significant differences (P ≤ 0.05) differential in (14,42,70,100) days of productive, with showed non-significate difference for (28, 56, 84, 98) days, respectively. The remarkable improvement in the average weight of eggs is attributed to following a good nutritional program and using a balanced diet that included all elements and nutritional needs as well as following a good management system and then it can be used in genetic improvement. ...
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This study was used 100 laying hens, for the period from 10/26/2021 till 3/5/2022 to studying the effect of LEI0258 marker on some productive traits of Iraqi local chickens, Productive traits were measured from the sexual maturity up to 100 days for each chicken, the blood samples were collected from 100 laying hens at the age of 38 weeks from a brachial vein. The LEI0258 marker have 11 alleles were (A1, A2, A3, A4, B1, B2, B3, C1, C2, C3, D1). The results showed that there were a high significant differences (P ≤0.01) for (A1, B1) alleles compared with different alleles of percentage number and genetic distribution with a percentage of (18 %). there was a significant effect (P ≤0.05) in age at sexual maturity for different alleles, while in weight at sexual maturity there were non-significant difference between different alleles. Egg weight trait showed that there was a significant difference (P ≤ 0.05) for the periods (14, 42, 70, 100) day, and non-significant differences in the productive periods (28, 56, 84, 98) day. Feed intake ratio recorded non-significant differences in the period (14, 28, 42, 98, 100) day, while it recorded a significant difference (P ≤0.05) in the productive periods (56, 70, 84) day between different alleles. The qualitative traits revealed a significant difference (P ≤ 0.05) for (shell weight, yolk weight, yolk height, yolk diameter, egg white weight, egg diameter, egg white height, and HU unit), While non-significant differences in shell thickness between the different alleles.
... DNA of good quality having intact band without smearing and satisfactory purity were used for further analysis. A panel of 10 microsatellite loci (Table 1) was selected based on earlier reports having relationships with egg production traits (Chatterjee et al. 2008, Chatterjee et al. 2010, Das et al. 2016 and their primers were synthesized from M/s Xcelris Genomics Labs Ltd., Ahmedabad (India). The PCR conditions were optimized (Rahim et al. 2017) for amplification of all these microsatellite loci (Table 1). ...
... loci had a significant influence on age at first egg (AFE) of the birds. Das et al. (2016) recorded their non-significant associations in RIR chicken. Chatterjee et al. (2008) also reported significant association of ADL0023 microsatellite genotypes with age at sexual maturity in White Leghorn chicken. ...
... Chatterjee et al. (2008) also reported significant association of ADL0023 microsatellite genotypes with age at sexual maturity in White Leghorn chicken. Birds' age at first egg trait was also reported earlier to be associated with different microsatellite genotypes in different chicken breeds, for instance, with MCW0075 in RIR chicken (Das et al. 2016), ADL0273, MCW0241, MCW0246 in other chickens (Roushdy et al. 2008). Variation in different studies might be affected by genetic architecture and most importantly by sample size. ...
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Randomly selected 76 pullets of RIR selected strain were screened for microsatellite polymorphs and investigated for their association with layer economic traits. Microsatellite alleles were separated from genomic DNA samples through 3.4% MetaPhor® agarose gel electrophoresis. Data were recorded on age at first egg (AFE), egg weights and egg production (EP) at certain age. Microsatellite analysis revealed nine polymorphic loci and genotypes at ADL0020 locus were significantly (P≤0.05) associated with EP at 40 and 64 weeks of age; CC (110bp/110bp) genotype had the highest EP, whereas AD (126bp/102bp) and BD (118bp/102bp) genotypes recorded the lowest. Genotypes at ADL0023 locus were associated (P≤0.05) with AFE, EP at 40 weeks of age; CC (176bp/176bp) genotype followed by AB (202bp/188bp) genotype had earlier AFE, whereas AC (202bp/176bp) genotype followed by BB (188bp/188bp) genotype demonstrated late AFE. ADL0210 locus had significant impact on AFE, egg weight at 28/40/64 weeks of age; BB (124bp/124bp) genotype followed by AA (132bp/132bp) genotype had earlier AFE than AB (132bp/124bp) genotype. Both AB and AA genotypes revealed significantly higher egg weight at 28/40/64 weeks of age than BB genotype. BB (176bp/176bp) genotype followed by AB (192bp/176bp) genotype at MCW0014 locus revealed higher (P≤0.05) egg weight at 28 weeks of age in comparison to AA (192bp/192bp) genotype. Allele C (110 bp) at ADL0020 and A (132 bp) at ADL0210 either in homozygous or heterozygous condition were linked to the traits of egg weight and egg production performance, respectively. The results might impact on genomic selection aided poultry breeding program.
... It has undergone a long-term selection on the basis of 40-weeks part-period egg production over last 33 years covering 30-generations of selection at ICAR-Central Avian Research Institute (CARI, Izatnagar) (Anonymous 2014). For last few generations, part-period egg production has been slowly declining due to reduction in genetic variability, and utilizing genomics data for faster genetic progress was suggested in future (Das et al. 2016). The present investigation was carried out to assess the impact of selection based on ADL0176 microsatellitegenotypes and to reveal the underlying association of microsatellite-genotypes at ADL0176 and MCW0044 located on chromosomal number-2 with grower and layer economic traits in RIR chicken. ...
... The microsatellite-genotypes at ADL0176 locus demonstrated significant effect on BW28, BW40 and EW40, while the genotypes at MCW0044 had significant effect only on BW40. Previously, microsatellite-genotypes at ADL0176 locus were reported for having significant association with body weights at 40 th weeks of age in a selected line of RIR chicken (Das et al. 2016) and in three pure lines of White Leghorn populations (Chatterjee et al. 2008b). Abasht et al. (2006) also reported significant association of microsatellite-genotypes at ADL0176 and MCW0044 with egg numbers and egg weights. ...
... Pullets with CC-genotype at ADL0176 locus laid eggs with the highest weight at 40 th weeks of age followed (P>0.05) by those with EE and DDgenotype, while the lowest egg weight at 40 th weeks of age was found under AD-genotype followed (P>0.05) by ACgenotype. Significant association between microsatellitegenotypes and traits like age at sexual maturity, body weights, egg weights and egg production could be quite informative indicator for revealing relationships between QTL and microsatellites (Das et al. 2016, Chatterjee et al. 2010, probably due to their linkage if the microsatellite be very closely linked (about 20 cM) with the QTL associated to a certain phenotype (Das et al. 2016, Chatterjee et al. 2010. It may be concluded that significant associations of microsatellite-genotypes with production traits are suggestive of rapid genetic improvement in growth and layer economic traits of RIR chicken by adapting microsatellite-marker based selection strategies. ...
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The present study aiming to assess impact of selection based on microsatellite-genotypes at ADL0176 and the association of microsatellite-genotypes at ADL0176 and MCW0044 located on chromosome number-2 with growth and layer economic traits in RIR chicken could reveal impact when the sire component influenced the growth and layer economic traits of the progeny-birds with different genotypes at ADL0176 and MCW0044 microsatellites. DD, EE and CC/AD-genotypes at ADL0176 microsatellite had corresponding higher (P≤0.05) BW28, BW40 and EW40 of the progeny than other genotypes, while BB-genotype at MCW0044 had higher (P≤0.05) BW40. Present findings could suggest the use of microsatellite-marker based selection for faster genetic improvement of economic traits in RIR chicken, provided its validation by taking larger sample sizes.
... Breeders exploit phenotypic variability in selection program for developing highly productive chicken genotypes for more egg and meat production. The ICAR-Central Avian Research Institute has developed and improved a selected line of RIR chicken population covering 29 generations of selection based on part-period egg production (Das et al. 2016), however the progress in response to selection has been slowing down in the last few generations probably due to reduction in genetic variability (Das et al. 2015a). Using genomic selection further faster genetic progress may be possible, which may have impact on layer breeding in future, and for which the microsatellites strive for its exploitation more widely. ...
... Samples showing intact DNA band and optical density ratio (260 nm : 280 nm) between 1.7 and 1.9 were used in subsequent experiments and PCR ready DNA samples were prepared at a final concentration of 50 ng/µl (Debnath et al. 2017). Eight microsatellite markers reported elsewhere for having association with various economic traits in different chicken breeds were identified from the published literatures (Das et al. 2016, Radwan et al. 2014, Chatterjee et al. 2010, Chatterjee et al. 2008 and their forward and reverse primers were procured from M/S Xcelris Genomics Labs Ltd., Ahmedabad (India). Annealing temperature for each of the primer pairs was optimized and PCR amplifications of the DNA samples were carried out for each microsatellite marker as described earlier (Debnath et al. 2017). ...
... Similarly, body weight at eighth week of age (BW8) was significantly influenced by microsatellites ADL0158 and MCW0258; 16 th week body weight (BW16) by MCW0103; 20 th week body weight (BW20) by ADL0158 and age at sexual maturity (ASM) by ADL0273 and MCW0103 microsatellites (Table 1). In agreement to these findings, earlier few researchers also reported significant association of some microsatellites with age at sexual maturity (Wardecka et al. 2002, Chatterjee et al. 2008, Chatterjee et al. 2010, Radwan et al. 2014, Das et al. 2016, chick weight (Chatterjee et al. 2008, Chatterjee et al. 2010 and pre-housing body weights (Wardecka et al. 2002, Sewalem et al. 2002, Chatterjee et al. 2008, Chatterjee et al. 2010 in different chicken genotypes, thus paving way to microsatellite marker assisted selection of these traits in molecular breeding program for achieving further genetic progress in these chicken lines/strains while phenotypic variability gets exhausted. ...
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Present study was aimed to investigate microsatellites for their association with pre-housing body weights and age at sexual maturity of RIR chicken. Genomic DNA samples were isolated from 114 birds maintained at institute. PCR amplified products of selected microsatellite loci were separated on 3.4% MetaPhore TM agarose gel and their sizes were determined by Quantity One software on GelDoc system. Locus specific alleles were identified according to their sizes, and their association with the quantitative traits was assessed by least squares analysis of variance. The analysis revealed significant association of microsatellite MCW0069 locus with chick weight, ADL0158 and MCW0258 loci with eighth week body weight (BW8), MCW0103 locus with BW16, ADL0158 locus with BW20, ADL0273 and MCW0103 loci with age at sexual maturity (ASM). The highest chick weight estimates were found in AB (183:174 bp) genotype of MCW0069 locus, whereas EE (189:189 bp) and BE (219:189 bp) genotypes of ADL0158, AB (280:273 bp) and CC (267:267 bp) genotypes of MCW0103, CD (107:102 bp) genotype of MCW0110, AE (216:147 bp) genotype of MCW0258 demonstrated the highest pre-housing body weight estimates. AB (160:147 bp) genotype of ADL0273 locus demonstrated the least age at sexual maturity (127.39±4.23 days) followed by its BB (147:147 bp) genotype. CC genotype of MCW0103 also had the least ASM (132.46±2.46 days) among its other genotypes and was better than BB genotype of ADL0273 locus. These findings suggest faster genetic progress in RIR chicken line by adapting microsatellite genotype based selection.
... Microsatellites are highly polymorphic tract of repetitive DNA in which some DNA motifs of 1-6 base pairs (bp) are repeated in length, typically 5-50 times (Gulcher 2012). Microsatellites are regarded as an ideal DNA marker for deciphering genetic variability (Das et al. 2016). ...
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Swiss albino mice have been widely utilized in various biological researches worldwide. Phenotypic and fitness related traits of F0 and F1 inbred mice were estimated on 918 and 707 individual offsprings, respectively. The influence of fixed effects (litter size and sex) on birth weight (BW), weaning weight (WW) and adult body weight (ABW) in both the generations were found to be statistically significant. Genetic characterization of F0 outbred and the F1 inbred strain of Swiss albino mice were evaluated by using 10 microsatellites markers. The results indicated that total number of alleles per locus ranged from 3 (D2Mit61, D3Mit55, D8Mit14, D9Mit27, D10Mit180, D11Mit167) to 4 (D1Mit15, D2Mit51, D5Mit18, D7Mit323) in F0 and F1 inbred population, with a mean value of 3.4 indicating polymorphism in all 10 loci. The mean of effective number of alleles was 2.935 and 2.733 in F0 and F1 population, respectively. Estimates of the FIS ranged from 0.139 (D10Mit180) to 0.999 (D9Mit27); and from 0.109 (D3Mit55) to 0.679 (D2Mit51) in F0 and F1 inbred population, respectively. The estimated mean markerbased FIS was 0.294 and 0.372 in F0 and F1 populations, respectively. The mean values of observed heterozygosity (Ho) and expected heterozygosity (He) were 0.460 and 0.654, respectively for F0 and 0.390 and 0.627, respectively for F1 inbred mice population. Slight reduction in heterozygosity and 7.8% increase in inbreeding coefficient were observed in F1 inbred in comparison to F0 population. The results suggested that genome wide microsatellite genotyping might be more useful for accurate measuring and reliable estimation of population genetic parameters and inbreeding coefficient.
... In addition to their association with the economic characteristics of domestic birds was used as a method of selection in the herds (Rudresh et al 2015). Among the most related studies, number of microsatellites markers as a method of selection in laying hens and broiler chickens were used (Das et al 2016). Soltan et al (2018) also used microsatellites markers to find out their effect on egg production in local Egyptian chickens. ...
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The study was conducted for the purpose of identifying the effect of MCW0330 marker alleles on production performance and thus selecting individuals distinguished from others, which has a positive impact on economic returns. The number of breeding chickens was 113 commercial egg-laying hens (ISA Brwon) at a pre-maturity age of 16 weeks, the birds were distributed in individual cages numbered sequentially in order to record the egg production of each chicken for a period of 100 days (from the age of sexual maturity until the age of 100 days of production). The eggs produced for each chicken were numbered, collected, and weighed individually for each egg, and the weekly feed consumption, age, weight at sexual maturity, were calculated. The effect of the different alleles of this marker on different characteristics was observed. The allelic effect resulted in six alleles of the marker MCW0330 were (A, B, C, a1, b1, c1). The alleles percentages of this marker showed highly significant differences where the A alleles exceeded the rest of the different alleles, as it reached 35.40%. Microsatellite technology was used to investigate the effect of these alleles on the age characteristic at sexual maturity, which recorded high significant differences between the different alleles of the marker MCW0330. In the characteristic of weight at sexual maturity, significant differences were recorded between the different alleles of the marker MCW0330. Finally, the feed consumption characteristic recorded high significant differences in the weekly periods (22-29) except for the period 23 weeks, the significant differences were recorded between the different alleles (A, B, C, a1, b1, c1) for the marker MCW0330.
... Faster genetic progress is possible through genomics, which will have a significant impact on future layer breeding (Albers and Van Sambeek 2002). Scanty information is available on molecular genetic characterization of RIR using microsatellite markers and their association with egg production traits (Das et al. 2016). Therefore, present investigation was carried out with the objectives of analyzing allelic profiles of some eggproduction associated microsatellite loci, average heterozygosity and polymorphic information content (PIC) at these loci, to evaluate Hardy-Weinberg disequilibrium and determine Wright's fixation indices in selected strain of Rhode Island Red (RIR S ) chicken. ...
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Present investigation was carried out in 114 birds belonging to selected strains of Rhode Island Red chicken maintained at institute experimental layer farm with the objective to analyze polymorphism in egg production associated microsatellite loci and to determine various population genetics statistics based on allelic polymorphism. Genomic DNA samples were isolated from all experimental birds and PCR was performed using primers for ten microsatellite loci, reported to be associated with egg production traits in chicken. Alleles were separated on 3.4% MetaPhore™ agarose and their sizes were determined by Quantity One software. Allelic data were analyzed by POPGENE. Allele numbers varied from 2 to 5 and average number of alleles per locus was 4.00±0.37 (Na). Allele sizes ranged from 99-280 bp. Allele frequency per locus ranged from 0.0225-0.8919. Nei's heterozygosity, Botstein's polymorphic information content (PIC) and Wright's fixation indices at each locus were estimated. All studied microsatellite loci were polymorphic and estimated PIC ranged from 0.19 (ADL0273) to 0.72 (MCW0110). Seven loci were moderate to highly polymorphic (PIC>0.50). Nei's heterozygosity per locus ranged from 0.20 (ADL0273) to 0.77 (MCW0110). Averaged effective number of alleles (Ne), Shannon's Information index (I) and Wright's fixation indices were 2.71±0.26, 1.0654±0.1046 and 0.5126±0.0757, respectively. Average observed (Ho) and expected (He) heterozygosities were 0.3036±0.0625 and 0.5930±0.0505, respectively. Study revealed prevalence of heterozygosity as the Ne was lesser than the Na. It further revealed that the population was under Hardy-Weinberg disequilibrium as (He) was more than (Ho).Chi square and G-square estimates were significant, which suggested that the studied microsatellite loci might have some association with ongoing selection for 40-week part-period egg production in RIR chicken.
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This investigation aimed to analyze microsatellites after long term selection for egg production in the selected line (RIRS) of Rhode Island Red chicken and its control line (RIRC) maintained at the institute. Genomic DNA samples isolated from 24 randomly selected birds of RIRS and RIRC line were investigated at 24 microsatellite loci. Microsatellite alleles were separated on 6% urea-PAGE and their sizes were estimated with the help of Gel Doc 2000 system. Allelic data was analyzed. Analysis revealed 2 to 7 alleles in RIRS and 2 to 9 alleles in RIRC line across 24 loci with their sizes ranged from 84 to 276 bp. Observed number of alleles per locus was 4.04 +/- 0.23 in RIRS and 4.42 +/- 0.33 in RIRC. Allele frequency ranged from 0.083 to 0.667 in RIRS and 0.042 to 0.833 in RIRC. Approximately 34.02% of alleles in RIRS and 39.62% alleles in RIRC were line specific. The frequencies of the specific alleles ranged from 0.083 to 0.667 in RIRS and 0.083 to 0.883 in RIRC. Line specific alleles with higher frequencies can be used in line identification. Corresponding effective number of alleles and Shannon's information index averaged 3.32 +/- 0.19 and 1.25 +/- 0.06 in RIRS and 3.66 +/- 0.32 and 1.30 +/- 0.08 in RIRC. These diversity estimates indicated that the control line was more diverse than the selected line and certain specific microsatellite alleles were getting fixed in the selected line.
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This study aimed to estimate microsatellite based genetic diversity in two lines (the selected RIRS and control line RIRC) of Rhode Island Red (RIR) chicken. Genomic DNA of 24 randomly selected birds maintained at Central Avian Research Institute (India) and 24 microsatellite markers were used. Microsatellite alleles were determined on 6% urea-PAGE, recorded using GelDoc system and the samples were genotyped. Nei's heterozygosity and Botstein's polymorphic information content (PIC) at each microsatellite locus were estimated. Wright's fixation indices and gene flow were estimated using POPGENE software. All the microsatellite loci were polymorphic and the estimated PIC ranged from 0.3648 (MCW0059) to 0.7819 (ADL0267) in RIRS and from 0.2392 (MCW0059) to 0.8620 (ADL0136) in RIRC. Most of the loci were highly informative (PIC>0.50) in the both lines, except for five loci in RIRS and six loci in RIRC line. Nei's heterozygosity per locus ranged from 0.4800 (MCW0059) to 0.8056 (ADL0267) in RIRS and from 0.2778 (MCW0059) to 0.875 (ADL0136) in RIRC. Out of 24 loci, 15 (62.5%) in RIRS and 14 loci (58.33%) in RIRC revealed moderate to high negative FIS index indicating heterozygote excess for these loci in corresponding lines, but the rest revealed positive FIS indicating heterozygosity deficiency. A mean FIS across the both lines indicated overall 10.77% heterozygosity deficit and a mean FIT indicated 17.19% inbreeding co-efficient favoring homozygosity over the two lines. The mean FST indicated that 10.18% of the microsatellite variation between the two lines was due to their genetic difference.
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Associations between four microsatellite markers on chromosome 11 and five on chromosome 13 with performance, carcass and organs traits were investigated in chickens using a least-squares approach applied to single-marker analysis. Three hundred and twenty seven F2 chickens from the EMBRAPA broiler x layer experimental population were evaluated for 16 traits: five related to performance, five to carcass and five to organs, plus the hematocrit. Two significance thresholds were considered: p<0.05 and p<0.0056; the last value resulted from the application of a multiple tests analyses correction. On chromosome 11, six associations (p<0.05) between the genotypes of two markers with four growth related and one carcass trait were found. On chromosome 13, six associations (p<0.05) between marker genotypes and three performance traits, eight associations (p<0.05) between marker genotypes and two carcass traits and eight associations (p<0.05) between marker genotypes and four organs traits were detected. These associations were indications of the presence of quantitative trait loci on these chromosomes, especially on chromosome 13. In this chromosome, the strongest evidence was for body weight at 41 days of age and percentage of carcass because the p-values exceeded the multiple test threshold (p<0.0056), but also for breast percentage and heart weight due to the large number of markers (four) on chromosome 13 associated with each one of these traits. These associations should be further investigated by interval mapping analyses to find QTL positions and to allow the estimation of their effects.
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The present study was conducted on six crossbred chicken populations of White Leghorn to estimate variability of microsatellites and their association with egg production traits. Five microsatellite markers located on chromosome 1, 2, 5 and 30 were explored and the association study was performed employing least square-maximum likelihood method. All the microsatellites were found to be polymorphic showing three to six alleles in the population. Genotype and allelic frequency was estimated showing a large variability in different microsatellites. The association study of microsatellite variability with egg production traits showed that only ADL023 microsatellite was significantly associated with egg production upto 64 and 72 weeks and egg weight at 28 weeks of age. Genotype 11, 12, 13 and 23 produced more number of eggs at 64 and 72 weeks of age than the genotype 22. Egg weight was higher in genotype 12, 13 and 23 and lower with genotype 11 and 22.
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Variability of microsatellites and a possible relationship with growth, egg production, and immunocompetence traits were estimated for six crossbred chicken populations of White Leghorn. Nine microsatellite markers were explored; an association study used the least square maximum-likelihood method on 170 birds of six genetic groups. Seven microsatellites were polymorphic, with two to four alleles. The polymorphism information content (PIC) of five markers was more than 52%. Microsatellites MCW0041, ADL0210, and MCW0110 were significantly (P < 0.05) associated with egg production traits. Genotype 33 of MCW0041 had the highest egg production, up to 64 and 72 weeks of age. Genotypes 11 and 13 of this marker produced the lowest number of eggs. The heterozygous genotype 34 of ADL0210 had the highest egg production, up to 52, 64, and 72 weeks of age. Homozygote 11 of MCW0110 produced the highest number of eggs, up to 28 weeks of age. MCW0041 was significantly (P < 0.05) associated with body weight at 28 and 40 weeks of age. No microsatellite was significantly associated with egg weight at any age, with age at sexual maturity, or with immune response to sheep RBC.