Birhan_Seminar presentation Bahir Dar .pptx

Candidate Genes and Genomic Regions Associated
with Egg Production Performance in layer Chickens: A
review
Birhan Kassa (BDU1500178)
Course Instructor: Wossenie Shibabaw (PhD)
A Senior Seminar Paper presentation
(AngbM742)
http://bdu.edu.et www.facebook.com/bduethiopia 1

Introduction
Literature review
Molecular approaches of identifying candidate genes
and genomic region
Candidate genes and genomic regions associated with
egg Production Traits
Molecular association of genomic regions and egg
production
Molecular association of candidate genes and egg
production traits
Conclusion and Recommendation
Presentation outline
2
http://bdu.edu.et www.facebook.com/bduethiopia

Introduction
Why do we
bother while
Selection is doing
so well?
Selection of best performing strains have been practiced
for several years now
Immense achievements were possible through selection
The need for more production, efficiency and robustness
remains critical
3
Changes mainly due to selection

Additional tool in
identifying the
right animal
The information can be used in selection programs that aimed at
increasing productivity, enhancing environmental suitability/
adaptation and thereby maintaining genetic diversity.
Therefore, to understand the genetic control of the trait of interest
and then to identify the genes involved.
The choice of breeds for such studies should be informed by a
knowledge of inbreeding, genetic diversity, and population
structure Selection of best performing strains have been practiced
for several years now
Direct selection: Based on the phenotype value
Indirect selection: Phenotypic indirect selection
(Based on correlation between trait)
Genotypic indirect selection
(Based on marker assisted with a gen or QTL)
4
Introduction cont..

Why
molecular
genetics and
techniques?
Molecular genetics
It investigates the genetic makeup of living things at the molecular
(DNA, RNA, and Protein) level
It involves the identification and mapping of genes and genetic
polymorphisms associated with adaptation and productive traits
Involves the manipulation and analysis of DNA, RNA, protein, and lipid
Conventional animal breeding is related to the phenotypic selection
where traits are measured directly, animals with superior performance
in the traits are used as parents of the next generation
Selection based on phenotypic traits have limitations associated with
data collection and precision of measurement unless proper measures
are taken
Can only be applied for traits measured easily and moderately to
highly heritable, and it is costly as it demands the maintenance of
the breeding stock during measurement
5
Introduction
cont..

Why molecular
genetics are
important in
selection over
convectional
selection?
Genetic progress may be enhanced with the knowledge of the
genetic architecture of quantitative traits: the underlying genetic
basis of a phenotypic trait and its variation properties
Molecular genetic information can be obtained at an early age that
selection decision can be made earlier and generations intervals
are quite short
Molecular genetic information can be obtained on all selected
candidates, which is especially beneficial for sex-limited traits,
traits that are expensive or difficult to record, or traits that require
the slaughter of the animal (carcass traits)
Molecular genetic information can result in greater genetic gain
than phenotypic information is with no genotyping error, the
molecular genetic information is free from environmental effects
resulting in highest heritability
6
Introduction
cont..

Introduction
Egg
production
and related
traits
Chicken production traits (egg number and egg weight) are the
most important economic traits (Liu et al., 2010)
Therefore, improving egg production is one of the main goals
in a chicken breeding program
Hen laying performance usually expresses reproductive
performance of chicken (Du Y et al., 2020)
Egg production performance of chicken can be evaluated in
terms of age at first egg, egg number and egg production rate
Egg number is of great significance to select hens with higher
capacity of egg laying in modern poultry breeding,
Especially for the country where the eggs are sold by
quantity, since it can efficiently evaluate the individual egg
production in a certain period (Zhuang et al., 2019).
7

Introduction
cont..
Worldwide, the consumption of chicken egg as a source of
animal protein has increased significantly
12.5 kg per year per person (Hjellnes et al., 2020)
Even alarmingly increase with accretion urban populations
(Goto et al., 2019)
Therefore, understandings of the genetic mechanisms of
chicken egg production and related traits have a great practical
and economic importance to improve egg production
performance
But egg production is a polygenic genetic trait: the function
of many genes and their interaction with different level of
effect
Low to medium heritability
Affected by both genetic components and environmental
factors (Zhang et al., 2012; Qin et al., 2015)
8

Introduction
cont..
Therefore, understanding of genes and genomic regions of
chicken with their main and interaction effect with various
molecular markers have opened the opportunity to select for
genes that are directly related to egg production traits
Candidate genes as molecular techniques are considered as one of
the primary methods to determine the specific genes related to the
economic traits in chickens
QTL could be used to identify these specific genes or their
chromosomal regions
This approach has enabled opportunities to enhance genetic
improvement programs in chickens by direct selection based on
genes or genomic regions that affect economic traits through
MAS
9

Introduction
cont..
In chickens, selection programs through quantitative genetics
are time consuming in case of lowly heritable traits
The identification and utilization of QTL provide more
potentiality for rapid genetic improvement in selection
programs, especially for traits that are difficult to be improved
with traditional selection (Ikeobi et al., 2002)
In a recent studies the associations between candidate genes
and egg production and egg quality traits have been confirmed
in chickens (Cui et al., 2006; Li et al., 2009; Xu et al., 2011a,b; Zhu
and Jiang, 2014; Ngu et al., 2015; Vu and Ngu, 2016; Charoensook
et al., 2016; Osman et al., 2017; Nguyen et al., 2018; Azmal et al.,
2019; Bhattacharya et al., 2019)
Therefore, the objective of this paper is to review molecular
association of candidate genes and genomic regions with egg
production performance traits of layer chickens.
10

2. Literature review
2.1. Molecular approaches of identifying candidate genes
and genomic Regions
The advent of the era of molecular genetics in 1970s
provided new opportunities to enhance breeding
programs in the use of DNA markers associated with
traits of interest
Because of being highly polymorphic and abundant in the
genome, SNP, the third generation marker is becoming
popular in various genetic applications including
Identification and wide genome scans
Candidate gene approaches
High density SNP genotyping for whole-genome
selection
11

Literature review
conti….
2.1.1. Genome wide scans
The genetic control of quantitative traits is expected to be
distributed throughout the genome which control the
quantitative traits of interest, were described as
quantitative trait loci (QTL)
The identification of QTL and the development of DNA tests
were the important steps in the practical application of QTL
through marker-assisted selection (MAS)
i.e., selection on a combination of information derived from
genetic markers associated with QTL and the traditional
phenotypic information (Fulton, 2014)
Most of these QTL searches were done using 200–350 MS
markers and crosses between very diverse breeds, such as
heavy meat-type birds and lighter egg-laying varieties or
specialized inbred lines
12

Literature review
conti….
The implementation of MAS in breeding programs was,
however, limited for various reasons (Dekkers , 2004), viz.
Majority of work on QTL is restricted to experimental
crosses having wider linkage disequilibrium rather than
original populations undergoing genetic improvement
program.
The effects identified by QTL analysis are able to explain a
limited amount of genetic variation affecting a trait
Due to the several genetic and non-genetic variations as
well as interactions, replication of many associations
determined through QTL analysis are difficult to be
replicated
The high-cost of routine genotyping yielding few markers
also limits the application of QTL analysis in large
breeding operations. Existence of negative correlations
between traits of commercial interest also hurdles MAS
13

Literature review
conti….
2.1.2. Candidate gene approach
The candidate genes are the gene with direct and large effect
on the trait of interest.
Basing on prior information certain candidate gene may be
hypothesized to be responsible for a known major genetic
effect.
The sequence variations in that gene are identified and then
finally various alleles are associated with variation in the trait
of interest
The genes which are directly associated with production
traits like growth hormone (GH), growth hormone receptor
(GHR), insulin-like growth factor-1 (IGF-1), IGF-1R,TGF
betas, myostatin, etc. have been the candidate genes analyzed
and molecular markers like SNPs, indel/dels were identified
(Zhou et al., 2005; Nie et al., 2005)
Three physiological candidate genes (i.e., genes for GH) and
gonadotropin-releasing hormone receptor (GnRHR) and
neuropeptide Y (NPY) were analyzed to find out their
association with egg production, number of double yolk egg,
and age at first egg.
14

Literature review
conti….
2.1.2. High-density SNP genotyping for whole-genome
selection
Development of NGS technologies and high-throughput
genotyping platforms has led to the creation of high-density
SNP array as a state-of-the-art tool for genetics and genomics
analyses of domestic animals
The most promising applications of these arrays in agriculture
could be genomic selection for the improvement of
economically important traits (Fan B et al., 2010)
Genomic selection is an advanced form of marker-assisted
selection (MAS), which concentrates on all markers across the
whole genome (Calus, 2010).
15

Literature
review conti….
It precisely predicts the breeding values of animals by utilizing
the information related to the distribution of abundant SNPs
across the genome
Genomic estimated breeding value, GEBV, with an
assumption that abundant SNPs are scattered throughout
the genome and there exist LD relationships between SNPs
and QTL.
The large number of SNPs essentially required for the design
and construction of arrays can be obtained through different
methods and resources
e.g., predicted SNPs generated from genome sequencing
and HapMap studies, completing reduced representation
library sequencing (Amaral et al., 2011) downloading SNP
information from dbSNP of NCBI
(http://www.ncbi.nlm.nih.gov/projects/SNP/).
16

Literature
review
conti….
2.2. Candidate genes and genomic regions associated with egg
Production Traits
2.2.1 Molecular association of genomic regions and egg production traits in
layer chicken genome
QTL mapping was the perfect approach to identify genes related to
complex traits at genome-wide level
The chicken genome consists of 38 pairs of autosomal chromosomes
and sex Z and W chromosomes
The chromosomes can be classified into two size groups, nine macro-
chromosomes and 30 micro chromosomes (Bloom et al., 1993)
Recent development of statistical methods and comprehensive linkage
maps of the chicken genome has provided tools for mapping loci affecting
quantitative traits (Mackay et al., 2009)
17

Literature review
conti….
The most significant peak genomic region of egg
production traits was located at 48.61–48.84 Mb region on
GGA5
In this region, YY1, SLC25A29, WDR25, and BEGAIN were
annotated.
Among them, YY1 and WDR25 have been shown to be
related to oocytes and reproductive tissues, respectively
(Griffith GJ, et al., 2011)
At the same time, interestingly enough, a number of studies
have detected regions associated with egg number traits on
chromosome 5 (Zhang GX et al., 2015)
18

Different result proven that chromosome 5 is an
important candidate region that affects the reproductive
traits of chickens
In Germany, Goraga et al. (2012) reported highly
significant QTL region
On chromosome 4 for egg production traits
on chromosomes 1, 5 and 9 for egg weight
on chromosomes 5 and 7 for number of eggs
on chromosome 1 for age at first egg
Literature review
conti….
19

Literature review conti….
2.2.1. Molecular association of genomic regions and egg production traits in layer chicken
genome
Figure 1: In Manhattan plot, the x-axis is the position of each SNP on the chicken chromosomes
(34, 40, 63 indicate LEG64, W, and Z respectively), and the y-axis is the -log10 P-value. The horizontal red
dotted line at the top indicates the genome-wide significant thresholds is 3.91 × 10− 7, line at the bottom
represents the genome-wide suggestively thresholds is 7.82 × 10−6 (Xiurong Zhao et al., 2021)

Literature
review conti….
In Egypt, the chromosomal map to be used for detecting growth
and egg traits in F2 population is reported by Abdel A’al et al.
(2016)
which is a total of 19 significant genome QTL located
on seven macro chromosomes (chromosome1, 2, 3, 4, 6, 8 and
Z) and one micro-chromosome (chromosome 11) affecting
growth traits,
on chromosomes 1 and 5 for egg weight,
on chromosomes 5 and 7 for number of eggs,
on chromosome 1 for age at first egg
For QTL mapping and their positions detected for egg production
and egg quality traits, Abdel A’al et al. (2016 and 2017) have been
illustrated the chromosomal group, number of informative
microsatellite markers and chromosomal map length (cM) for the
whole genome scan of egg production traits in F2 cross (Table 1)
This study has reported that the total chromosomal map length for
egg production and egg quality traits was 1949 cM ranging from 52
cM on chromosome 11 to 542 cM on chromosome 1, with marker
spacing ranging from 15.3 cM on chromosome 4 to 71.5 cM on
chromosome 6.
21

Chromoso
me
Number of
microsatellite
markers
Chromosome
map length
Average marker spacing
by the chromosome (cM)
1 9 542 60.2
2 8 401 50.1
3 6 144 24
4 4 286 15.3
6 3 123 71.5
8 2 88 44
9 2 112 56
11 3 52 17.3
13 2 69 34.5
Z 6 132 22
Total 45 1949
Literature review
conti….
22
Table 1: Chromosome group, number of microsatellite markers and map length (cM)
that was used for a whole genome scan of egg production traits in F2 cross

Literature
review conti….
2.2.2. Molecular association of candidate genes and egg production
traits in layer chicken genome
Many studies have been confirmed recently the associations
between candidate genes and egg production and egg quality traits
in layer chciken (e.g. Osman et al., 2017; Nguyen et al., 2018; Azmal
et al., 2019; Bhattacharya et al., 2019)
Candidate genes located on chromosome 1, 3, 4, 5, 7, 9, 13, 20, 24,
27 and Z associated with egg production and egg quality traits in
chickens are presented (Table 2)
Xiurong Zhao et al. (2021) identified 32 candidate genes based on
their function.
23

Literature
review conti….
These genes mainly affect egg number in three ways
Some genes regulate hormone levels, including gonadotropin-
releasing hormone (GNRH), oxytocin (OXT), growth hormone
(GH), and thyroid hormone (TH)
All these hormones play a vital role in the female reproductive
system (Prapaiwan et al., 2017; Ma Y et al., 2020; Ji H et al., 2018)
Some genes affect egg number traits by affecting the growth and
development of follicles (Example: LRIG3, KITLG, PCDH17,
GHRHR, ADGR L3, CCDC88C, YY1, CSNK2A2, POLR2C,
ITPR1, SMURF2, AGO1, CHIA, DAZAP1, DIRAS1, MUSK,
CAMK4).
The growth and development of follicles are critical for
reproductive function, especially in layer chickens
24

Literature
review conti….
The remaining genes directly affect reproductive system development
like (WDR25, ENSGALG00000029896, SLC39A3, HYDIN, ENSG
ALG00000039201, GAMT, DAZAP1, ENSGALG00000005652)
Among these 32 candidate genes, the 7 important genes that have been
identified as related to reproductive traits such as egg production and
egg number
NELL2 and KITLG are located on GGA1
NELL2 not only affects the synthesis and secretion of
GNRH (Zhou SS et al., 2014), but has also been shown to be
involved in maintaining the normal female reproductive
cycle of mammals
KITLG plays an important role in the growth and development of
follicles (An XP, 2012)
25

Literature
review
conti….
GHRHR located on GGA2 participates in the secretion and
synthesis of GH.
It is believed to be involved in the growth and reproduction of
livestock.
ITPR1 has been reported to be involved in the transport of Ca2+
and may be associated with egg number (Tarsani E et al., 2020)
This suggests that this region located on chromosome 12 and
the ITPR1 gene may be important for chicken egg number
traits
CAMK4 located on chromosome Z is involved in the signaling
pathway of OXT and may play a role in the development of
follicles and ovulation and it is believed to play a significant role
in the reproductive
26

Literature review conti….
Candidate gene associated with egg production and related
traits
Chromosome
number
Reference
NELL2, ITPR2, POLA1, LATS2, Insulin -like Growth Factor I
(IGF-I), Melatonin Receptor 1B (MTNR1B), Matrix
metallopeptidase 13 (MMP13)
1 Zhao et al. (2021), Li et al. (2021), Sun et al.
(2021), Li et al. (2009), Li et al. (2013), Ngu et
al. (2015), Yuan et al. (2016)
ESR1, Vasoactive Intestinal Peptide (VIP), Follicle Stimulating
Hormone Receptor (FSHR)
3 Niu et al. (2017), Zhou et al. (2010), Li et al.
(2011), Nguyen et al. (2018)
NCAPG, SLIT2, Melatonin Receptor 1A and 1C (MTNR1A and
MTNR1C), Gonadotropin Releasing Hormone II (GnRHII)
4 Xu et al. (2018), Sun et al. (2015), Li et al.
(2013), Bhattacharya et al. (2019)
Gremlin 1 (GREM1) and Gremlin 2 (GREM2), WDR25, 5 Tyasi et al. (2018), Zhao et al. (2021)
Inhibin α (INHA) 7 Cui et al. (2019)
Ovocalyxin-32 9 Fulton et al. (2012)
Growth Differentiation Factor 9 (GDF9), Dopamine receptor D1
(DRD1), Rap Guanine Nucleotide Exchange Factor 6
(RAPGNEF6)
13 Tempfli et al. (2015), Liu et al. (2018), Azmal
et al. (2019)
Matrix Metalloproteinases 9 (MMP9) 20 Zhu and Jiang (2014)
Dopamine D2 Receptor (DRD2) 24 Xu et al. (2011a; 2011b)
Growth Hormone (GH), Single Transducers and Activators of
Transcriptions 5B (STAT5B)
27 Su et al. (2014), Kulibaba (2015), Ngu et al.
(2015), Charoensook et al. (2016), Vu and Ngu
(2016)
Prolactin Receptor (PRLR), CAMK4, Growth Hormone Receptor
(GHR)
Z Kulibaba (2015)
27

3. Conclusion
Most of the identification of candidate genes and
genomic regions associated with egg production in layer
chicken is done with genome wide association studies
Those genome-wide association studies (GWAS) have
been used successfullyin identify single nucleotide
polymorphisms (SNPs), candidate genes and genomic
regions associated with egg production and related
traits in chicken
Using Ensembl to annotate related SNPs, genome wide
association study found a total of 68 genes around
significant peaks, and identified 32 candidate genes
associated with egg number according to their
functions
28

These results help us to better understand the molecular
mechanisms underlying egg production and related traits
in layer
GWAS showed that five identified SNPs in chromosome
13 were associated with egg production traits
Significant associations for age at first egg, body weight and
egg weight were observed on chromosome 2
Genes identified by annotating sixteen genome-wide
significant SNPs that can be considered as candidate genes
associated with egg numbers.
Conclusion
conti….
29

4. Recommendations
A part from the convectional breeding, genome-wide
association studies creates a convenient environment to
conduct genomic selection to fasten the genetic
improvement in layer chicken
On the scope of this review, layer chicken breed
improvement program should be designed by
incorporating genomic selection to fasten the improvement
Therefore, molecular application procedure to run layer
chicken genetic improvement program are summarized as:
Recording the phenotypic data from full pedigree file to
evaluate the birds genetically through estimating the
breeding values for hens and cocks
Collecting the blood samples from birds and
performing DNA extraction
30

Recommendations
conti…
Reporting candidate genes from QTLs data base
(http://www.animalgenome.org/QTLdb)
Preparing the genotyping files using SNP markers
Applying SNP association test to detect the genes
closely associated with economic traits in chicken
Estimating the genomic breeding values (GBV) to be
applied in genomic selection
Applying the Genome-Wide Association Study (GWAS)
Applying genomic selection program (GS) using GBV of
cocks and hens to be the parents of the next generation
31

Thank you!

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