FEMALE FERTILITY MARKERS

1. Molecular markers of female fertility
Jerome A, Inderjeet Singh

2. PHENOTYPE
PROD. & REPROD.
ENVIRONMENT
PHYSIOLOGY
GENOME
PROTEOME
TRANSCRIPTOME

3.  Fertility - measure of reproductive success.
 Complex feature - Influence of numerous genes, working together to produce
functional gametes, early embryonic and fetal development.
 Heritability: Relatively low for fertility (<5%)
 Recent developments in the area of gene mapping and molecular genetics have
now made it possible to search for candidate genes for markers controlling
reproductive traits
(Seidenspinner et al. 2010)

4. 
Markers: Gene , Protein , Phenotype
Phenotypic Markers
 Color, shape, size and performance of the individual
 Difficult to have a large number individuals with exact phenotype markers.
Molecular markers

Gene, protein: measurable or detectable in the presence of a specific genotype.

Tools to envisage genetic variation among individuals with respect to various
economic important traits.

For improved breeding programs in many livestock species
(Vermerris 2008)

Different classes based on the time of development and kind (protein and DNA
markers)

5. Molecular markers types
DNA Markers
 Have pattern of inheritance through generation and polymorphic.
 Detection is independent of tissue, age, environment or sex, Distributed
throughout the genome, and their detection is efficient and reliable.
 Mostly studied DNA markers:
Randomly amplified polymorphic DNA (RAPD-PCR),
& single nucleotide polymorphism (SNP).
microsatellites

6. Randomly Amplified Polymorphic DNAPolymerase
 RAPD-PCR: detecting polymorphisms for genetic mapping and strain
identification
 Faster, less expensive and does not require prior sequence information.
 Powerful tool in DNA fingerprint analysis, gene mapping studies,
population analysis and identification of breeds.
(Welsh et al. 1990)
Microsatellites Markers
Base repeats, Highly polymorphic, distributed throughout the genome,
locus specific and co-dominant.
For studying polymorphism and genetic diversity in many livestock species
(Welsh and McClelland 1990)

7.  In buffaloes 33 microsatellite markers:
distancing studies.
recommended by FAO for genetic
 Majority of the markers common for cattle and buffalo breeds and be used for
characterization of populations.
 Vijh et al. (2005) generated data on 24 microsatellite loci from 3 buffalo
populations viz. Bhadawari, Tarai and Kerala buffaloes
 In Mehsana and Bhadawari: single marker and four were found in Jaffarabadi
and three alleles in Murrah
(Rupinder et al. 2009 )
 Bhuyan et al.(2010) : large number of polymorphic loci are present in Murrah
breed
 Mishra et al. (2010): revealed the distinctness of Banni and Jaffarabadi
buffaloes from other river buffalo breeds of the region.

8. Single-Nucleotide Polymorphisms (SNPs)
 SNPs: change in the nucleotide at a particular location within the genome of
a individual.
 Have two alleles and potential number of SNP markers is very high, and
possible to find them throughout the genome.
 Unambiguous,
accuracy.
low cost and high number of SNPs detection with high
 Initiatives from ICAR and USDA: elucidation of numerous SNPs, which
needs to validated for various economic traits
(Van Tassell et al. 2010; Tantia et al. 2011)

9. Mitochondrial DNA Markers
 Mitochondrial DNA markers: markers of evolutionary significance;16355 bp in
length.
 Highly specific with no tandem repeats;Identification of wild ancestors,
localization of domestication centres and reconstruction of colonization and
trading routes
(Ajmone-Marsan et al. 2010)
Y-Chromosomal Markers
Y-chromosomal variation: tracing gene flow by male introgression, powerful marker
in human population genetics and nowadays its importance is felt in in domestic
animal as well.
(Sangwan 2012)

10. Protein markers
 Proteomics: product of gene expression and they provides unique capability to
demonstrate how cells can respond dynamically to changes in their environment.
 Application of proteomics : identification of new biomarkers, specific to certain
conditions, or more general health status.
 Proteomics analysis in bovine serum samples of pregnant and nonpregnant Holstein dairy cattle: key proteins in early pregnancy and
identified nine pregnancy-specific spots in Day 21 and Day 35 serum
samples.
(Jin et al. 2005)

11.  Bovine conceptus fluids proteomics: >200 spots: 74 individual protein
species identified; MS/MS peptide identification of 105 LC-ESIMS/MS generated protein identities; 179 individual protein species
specific for pregnancy (PAG, PRL)
(Kim 2009)
 Studies in buffalo serum during early pregnancy: differential
expression of pregnancy specific proteins exhibiting up and down
regulation.
 Identified spots: Synaptojanin-1, Apolipoprotein A-1, ApolipoproteinB, Keratin 10 and Von Willebrand factors – play role in pregnancy
(Balhara et al. 2012)

12. Identification of Markers
 Candidate Gene Polymorphism and sequencing Technique
Labor intensive and time consuming.
 Next-generation sequencing Technologies/ Proteomics
Reduced cost with high throughput & accuracy
 Next-Generation DNA Sequencing (NGS) platforms:
454 FLX, Illumina Analyzer, Applied Biosystems
SOLiDTM
System,
Helicos
HeliscopeTM
and
Pacific
Biosciences
SMRT instruments.
 Proteomics:
2D-page Electrophoresis coupled with isolelectirc focusing,
Difference gel electrophoresis (DIGE), MALDI-TOFF, Liquid
Chromatography and Mass Spectroscopy
(Darshan Raj 2012 )

13. Markers controlling female reproductive functions
Hormones regulating estrus
 Regulated by endocrine and neuroendocrine mechanisms: by the hypothalamopituitary gonads axis.
 Changes in the levels of these hormones GnRH, LH, FSH, oestradiol and progesterone
through specific receptors.
Polymorphisms in GnRH receptors :hypogonadism & pathological pubertal
maturation in humans
(Huhtaniemi 2002)
SNPs associated with fertility: identified in the bovine
pituitary-gonadal axis
hypothalamic(Hastings et al. 2006)

14. Gonadotrophin releasing hormone receptor (GnRHR)

GnRHR a member of the seven-transmembrane domain G protein-coupled receptor
(GPCR) family
(Fanet et al. 1995)

Genetic correlations showed associations between SNPs identified and fertility traits
(Millar 2004)
Follicle stimulating hormone receptor (FSFR)
In Chinese Holstein cows by Yang et al. (2010): polymorphisms in FSH receptor gene and
their association with superovulation traits.
Follicle-stimulating hormone β : candidate gene for its role in maturation of small and
medium follicles into large follicles.
(Mannaertz et al. 1994)
 Marson et al. (2008) in European-Zebu composite beef heifers: polymorphism of
FSHR gene association with sexual precocity in these breeds.

15. Luteinizing hormone receptor (LHR)
 LHR is a 7-transmembrane domain G-protein coupled receptor
expressed in the ovary, testis and uterus.
 Sequencing revealed - 3 SNPs in coding region:- 2 missense and 1 silent
mutation.
 SNPs present in 4 haplotypes - related to variation in fertility traits
 Specific haplotype associated with calving interval, day of first service
and production index, but not NRR and BCS
(Hastings et al. 2006)

16. Progesterone receptor (PR)
 Plays a central role in the reproductive vents associated with ovulation,
luteinisation, pregnancy establishment and maintenance,
 Role in controlling the proliferation, differentiation, and development of
mammary and uterine tissues
(Lydon et al. 1995)
 Many SNPs : in human receptors; two were identified in the coding
region and two in the promoter region.
 Studies in cattle/buffalo are lacking but in human, these mutations were
reported to be associated with risk of human endometrial cancer
(De Vivo et al. 2002)

17. Estrogen receptors (ESR)
 Other nuclear receptors, are transcription factors, which after binding
to their ligand are capable of regulating gene expression
(Kuiper et al.1996)
 Considered candidate markers for production and functional traits in
farm animals.

Rothchild et al.(1996) : ESR gene as a candidate gene for prolificacy in
pigs as SNP associated with the number of piglets borne alive.
 In Meishan and Large White pig breeds, ESR identified as a major
gene for litter size as ESR can be utilized in marker-assisted selection
to increase litter size
(Omelka et al. 2005)

18. Folliculogenesis and luteal function
 Folliculogenesis, ovulation, fertilization, and early embryogenesis : many genes
and proteins
(Sirard et al. 2006)
 Growth differentiation factor-9 (GDF-9), bone morpho-genetic protein-15 (BMP15)
(Hsueh et al. 2000)

Survivin, apoptotic protein: related to the quality of cumulus-oocyte complexes
(COCS),
(Jeon et al. 2008)
 Monget and Bondy (2000): IGF-I an important mediator in follicualogenensis and
ovulation in cattle.
 Steriodogenic acute regulatory (STAR) protein: regulation of steroidogenesis as
in mammalian ovary, including buffaloes
(Malhotra et al. 2007)

19. Pregnancy and prenatal mortality
 Numerous genes and pathways affecting uterine function and conception rate
 Yamada et al. (2002): bPRP-1 key role before implantation - marker for
trophoblastic cell differentiation, as well as a candidate for pregnancy diagnosis.
 Cathepsins: lysosomal cysteine proteases- as modulators of invasive implantation
in cats
(Li et al. 1992)
 Cathepsin L (CTSL) : pig uterus increases at the time of trophoblast elongation
with peak activity on day 15 of pregnancy (Geisert et al. 1997)

20.  Epidermal growth factor (EGF), transforming growth factor α (TGFα),
heparin-binding EGF, and amphiregulin: in pig endometrium during early
pregnancy
(Kim et al. 1995)
 In cattle, uterine serpins (SERPINA14) : roles during pregnancy in the farm
animals.
 In buffaloes by Kandasamy et al. (2010): spatio-temporal expression of
SERPINA14 in the uterine endometrium mRNA and high during stage II of
the estrous cycle.
 Osteopontin: implicated in transport and buffering of Ca2 + from the maternal
circulation to the conceptus and expression of the gene in cells of mouse
placenta
(Waterhouse et al. 1992)

SNPs in IFN-tau, Growth hormone, Prolactin Growth hormone receptor,
single transducers and activators, osteopontin and uterine milk protein
genes:associated embryonic mortality
( Khatib et al. 2008; 2009)

21. Anestrum
 Anestrum: low level of estrogens: due to cytochrome P450 aromatase mutations,
key enzyme in estrogen biosynthesis.
 Expression profile of CYP19 gene expression: significantly higher in granulosa cells
of large follicles as compared to the other tissues
(Sharma et al. 2009)
 Kumar et al. (2009): polymorphism in this CYP19 gene polymorphism in of
different fertility performance in buffaloes
Calving interval
 Mostafa et al. (2011) in Egyptian buffaloes deduced that FSHR, IGF-IR and
STAT5A genes had correlation with calving interval but not IGF-I and INHBA
genes.

GALNT6 variants exhibited a significant association with calving interval.
Variants of the genes FST, DAP and ALB, were also strongly associated with
calving interval.
(Sinead Waters et al. 2012)

22. Diagnostics and therapeutics
 Development of immunoassay, for general health screening of the herds for
reproductive disease Brucellosis etc.
 Identification of a estrus/pregnancy reliable biomarker in livestock species
 Used for predicting fertility potential of males and females.
 Specific protein can be used as additives in semen and embryo cryopreservation
and culture to improve their competence.
Improvement of genetic diversity
 Study of genetic diversity : Maintenance of animal genetic diversity in various
local environments, to sustain genetic improvement and adaptation
(Karp et al. 1997)
 Studies in cattle and sheep: genetic characterization and superior indigenous gene
markers in sheep breeds resulted in genetic improvement programs in Egypt
(Erhardt and Weimann 2007)

23. Markers assisted selection
 Genetic markers provide information about allelic variation at a given
locus
(Buddenberg et al. 1989)
 MAS: DNA sequences that are associated with a specific trait to
supplement phenotypic data used in the quantitative approaches for
selection
(Parmentier et al. 2001)

24. 
For reproductive traits, MAS is a promising technique that may aid in genetic
improvement due to its low heritability and availability of genetic markers
(Doyle et al. 2000)

Marker-assisted selection is best implemented for traits that are lowly heritable
and sex-limited

MAS: effective for traits affected by a small number of genes with large effects
(Pimentel et al. 2010)
Marker assisted introgression
 Introgression a major gene in another population by means of backcrosses assisted
by molecular markers.

Key markers of economic importance (production, reproduction, growth, disease
resistance) can be introgressed to form desired population at faster rate
(Groen and Smith 1995)

25. Genome selection
 Use of genome-wide genetic marker information for use in animal breeding
was proposed by Meuwissen et al. (2001)
 Markers originated from information generated in research, primarily metaanalyses of controlled experiments
(Georges et al. 1995)
 Modern-day genomic selection : larger number of genetic markers and the
effects of each marker estimated in the genomic selection process.
 Number of markers: dependent on the methodology used and original set of
genetic markers.
 Genomic selection: assumes genetic variation for a trait should be explained
by markers.
(Hayes et al. 2009)

26.  Genomic selection: lead to using genotypes defined by a set of
polymorphisms to select for preferred phenotypes
 Implementation of genomic selection in any population requires:
o Genotypes of a large population of animals
o Pertinent phenotypes for the system of production
o Statistical methodologies
 Based on the breeding program : already optimal and includes an
accurate genetic evaluation system based
o
o
Access to relevant and heritable phenotypes,
Pertinent breeding objective and scheme
(Seidel 2010)

27. Scope and future perspective
 Fertility: a lowly heritable needs improved strategies
comparison to traditional selection methods.
in
 Identification and usage of molecular markers: expedite the
rate of genetic improvement in domestic livestock species
including buffalo.
 Molecular
markers
with
the
other
reproductive
biotechnological tools : faster genetic improvement and
dissemination of superior germplasm.

28. THANK YOU