US20160201128A1

US20160201128A1 - Methods for selecting competent oocytes and competent embryos with high potential for pregnancy outcome

Info

Publication number: US20160201128A1
Application number: US14/808,204
Authority: US
Inventors: Samir Hamamah; Said Assou
Original assignee: Institut National de la Sante et de la Recherche Medicale INSERM; Centre Hospitalier Universitaire de Montpellier; Universite de Montpellier
Current assignee: Institut National de la Sante et de la Recherche Medicale INSERM; Centre Hospitalier Universitaire de Montpellier; Universite de Montpellier
Priority date: 2013-08-06
Filing date: 2015-07-24
Publication date: 2016-07-14
Also published as: US20170067105A1; US10059994B2

Abstract

The present invention relates to a method for selecting a competent oocyte or a competent embryo.

Description

FIELD OF THE INVENTION

BACKGROUND OF THE INVENTION

In assisted reproductive technology (ART), pregnancy and birth rates following in vitro fertilization (IVF) attempts remain low. Indeed, 2 out of 3 IVF cycles fail to result in pregnancy (SART 2004) and more than 8 out of 10 transferred embryos fail to implant (Kovalevsky and Patrizio, 2005). In addition, more than 50% of IVF-born babies are from multiple gestations (Reddy et al., 2007). Preterm deliveries that result from multiple pregnancies caused by ART are estimated to account for approximately $890 million of U.S. health care costs annually (Bromer and Seli, 2008).
The selection of embryos with higher implantation potential has been one of the major challenges in ART. This selection is currently based on morphological criteria such as growth rate, early cleavage on day-1, degree of fragmentation and blastocyst formation (Ebner et al., 2003). However, the predictive power of this approach is still limited. With the emergence of new technologies like ‘omics’, there are new biomarkers as discovery tools that can be applied to IVF for oocyte and/or embryo selection (Hillier, 2008).
Legal and ethical considerations make biomarkers directly directed to oocytes or embryos difficult to implement. Thus, to avoid any invasive method, some studies have been focused on cumulus cells (CCs).
Indeed, transcriptomic approaches using microarray technology, allowing the simultaneous screening of thousands of genes, were intensively used to identify in CCs the biomarkers related to oocyte competence, which is defined as the intrinsic ability of oocytes to undergo meiotic maturation, fertilization and embryonic development (McKenzie et al., 2004; van Montfoort et al., 2008).
Using the same approach, genes expressed in CCs used as biomarkers associated with embryo quality (McKenzie et al., 2004; van Montfoort et al., 2008; Zhang et al., 2005) and pregnancy outcome (Assou et al., 2008; Hamel et al., 2008; Hamel et al., 2010; Assou et al. 2010) have also been identified.
Even if these studies target the gene expression profile of CCs, a source of cells reflecting the biology and competence of both oocytes and embryos, there is a need to investigate further to develop a non-invasive method of predicting IVF outcome easier to use and with higher reliability.

SUMMARY OF THE INVENTION

The present invention relates to a method for selecting an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy, comprising a step of measuring in a cumulus cell surrounding said oocyte the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1826, hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7f, hsa-mir-1244, hsa-mir-182, hsa-mir-21, hsa-mir-30a, hsa-mir-30d, hsa-mir-320a, hsa-mir-508, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-1974, hsa-mir-146b, hsa-mir-886, hsa-mir-210, hsa-mir-1979, hsa-mir-125a, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20 and SEQ ID NO: 21.
The present invention also relates to a method for selecting an embryo with a high implantation rate leading to pregnancy comprising a step of measuring in a cumulus cell surrounding said embryo the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1826, hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7f, hsa-mir-1244, hsa-mir-182, hsa-mir-21, hsa-mir-30a, hsa-mir-30d, hsa-mir-320a, hsa-mir-508, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-1974, hsa-mir-146b, hsa-mir-886, hsa-mir-210, hsa-mir-1979, hsa-mir-125a, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20 and SEQ ID NO: 21.
The method according to the invention may comprise a further step of measuring in a cumulus cell surrounding said oocyte or said embryo the expression level of one or more genes selected from the group consisting of ATF3, SIAT6, PRKACA, PLA2G5, GPC6, G0S2, RBMS1, NFIC, SLC40A1 and WNT6.
The present invention also relates to a method for selecting an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy, or an embryo with a high implantation rate leading to pregnancy, comprising a step of measuring in a bodily fluid the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1826, hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7f, hsa-mir-1244, hsa-mir-182, hsa-mir-21, hsa-mir-30a, hsa-mir-30d, hsa-mir-320a, hsa-mir-508, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-1974, hsa-mir-146b, hsa-mir-886, hsa-mir-210, hsa-mir-1979, hsa-mir-125a, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO:24 and SEQ ID NO: 25.
The present invention also relates to an isolated nucleic acid molecule having the nucleotide sequence as set forth in SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO:24 and SEQ ID NO: 25.

DETAILED DESCRIPTION OF THE INVENTION

Definitions

A used herein the tem), “competent oocyte” refers to a female gamete or egg that when fertilized, i. e. upon fertilization, produces a viable embryo with a high implantation rate leading to pregnancy.
According to the invention, the oocyte may result from a natural cycle, a modified natural cycle or a stimulated cycle for cIVF or ICSI. The term “natural cycle” refers to the natural cycle by which the female or woman produces an oocyte. The term “modified natural cycle” refers to the process by which, the female or woman produces an oocyte or two under a mild ovarian stimulation with GnRH antagonists associated with recombinant FSH or hMG. The term “stimulated cycle” refers to the process by which a female or a woman produces one ore more oocytes under stimulation with GnRH agonists or antagonists associated with recombinant FSH or hMG.
The term “cumulus cell” refers to a cell comprised in a mass of cells that surrounds an oocyte. These cells are believed to be involved in providing an oocyte some of its nutritional, energy and or other requirements that are necessary to yield a viable embryo upon fertilization.
The term “embryo” refers to a fertilized oocyte or zygote. Said fertilization may intervene under a classical in vitro fertilization (cIVF) or under an intracytoplasmic sperm injection (ICSI) protocol.
The term “classical in vitro fertilization” or “cIVF” refers to a process by which oocytes are fertilised by sperm outside of the body, in vitro. IVF is a major treatment in infertility when in vivo conception has failed.
The term “intracytoplasmic sperm injection” or “ICSI” refers to an in vitro fertilization procedure in which a single sperm is injected directly into an oocyte. This procedure is most commonly used to overcome male infertility factors, although it may also be used where oocytes cannot easily be penetrated by sperm and occasionally as a method of in vitro fertilization, especially that associated with sperm donation.
The term “competent embryo” refers to an embryo with a high implantation rate leading to pregnancy. The term “high implantation rate” means the potential of the embryo when transferred in uterus, to be implanted in the uterine environment and to give rise to a viable foetus, which in turn develops into a viable offspring absent a procedure or event that terminates said pregnancy.
Set of Predictive microRNA
The inventors have identified a set of 42 predictive microRNA according to the invention expressed in cumulus cells and 4 predictive microRNA according to the invention expressed in oocyte.
MicroRNA are single-stranded RNA molecules that regulate the expression of messenger mRNA and play important roles in many physiological processes including growth, differentiation, apoptosis, cell cycle and development (Bushati N, et al. 2007, microRNA functions. Annu Rev Cell Dev Biol 23:175-205). Mature microRNA negatively regulate gene expression by targeting specific messenger mRNA for cleavage or translation repression. Growing body of evidence suggests that they are involved in the control of a wide range of physiological pathway (Bartel et al., 2009).
It was discovered that some microRNAs circulate in bodily fluid.
These circulating microRNA were found to be usefulness biomarker for diagnosis, prognosis and therapeutics, in particular in cancerology (Kosaka N. et al., 2010).
It was also been discovered than some miRNA can be transferred from a cell to adjacent cells and induce targeted inhibition of protein expression in the acceptor cells (Katakowski M. et al. 2010)
Table I shows the set of predictive microRNA according to the invention.
Some microRNA of the invention are known. They are identified by their name. All information concerning these microRNA, in particular their sequence, can be found on http://www.mirbase.org.
Other microRNA are new. They are identified by their sequence and a sequence identification number (SEQ ID NO) was allocated to each sequences.

TABLE I

set of predictive microRNA

		MicroRNA nucleotide sequence
	MicroRNA name	(only for new microRNA)

	SEQ ID NO: 6	AGAAGGAACGUCUGGAGUUUGUGCUGGU

	hsa-mir-103

	SEQ ID NO: 7	GUUUAUUCUAGAGAGAAUUCUUACUC

	SEQ ID NO: 8	AGACUUUCGGCCUAGGAUC

	hsa-mir-1826

	SEQ ID NO: 9	AGGUUCUGUCGUAUCAAUC

	hsa-mir-508

	hsa-mir-16

	SEQ ID NO: 10	CGAGCCGGGCCCUUCCGUC

	hsa-mir-182

	hsa-let-7b

	hsa-let-7c

	hsa-let-7f

	hsa-let-7a

	SEQ ID NO: 11	CGGAAAGGAGGGAAAGGGC

	hsa-mir-21

	SEQ ID NO: 12	CGGGCGGAGAGUAGGCAUC

	hsa-mir-1826

	hsa-mir-92a

	SEQ ID NO: 13	GUGGAGCCGGGCGUGGACU

	SEQ ID NO: 14	CUCUUCGUCUGUCCCUAUC

	hsa-mir-30d

	hsa-mir-30a

	SEQ ID NO: 15	UCCAUCAAAGAUCGGCAUC

	SEQ ID NO: 16	UGUGGGAAGAGGGCAUCCU

	SEQ ID NO: 17	AGGAGCAAGAGGGCAUCCU

	SEQ ID NO: 18	GCGAGGCACUGUGGAGAUC

	SEQ ID NO: 19	AGGCAGGUGAAGGCAUCCU

	SEQ ID NO: 20	UGGGAUCCCGAGGCAUCCU

	SEQ ID NO: 21	GCAGAUCUUCCUGGGUGGUGUGGAC

	SEQ ID NO: 22	GGUAGUGUCGCGGGGGUGC
		(found in oocyte)

	SEQ ID NO: 23	AAGGACUGUGAUCAUUGAA
		(found in oocyte)

	SEQ ID NO: 24	AGCGACGUUUCAUUGAAAA
		(found in oocyte)

	SEQ ID NO: 25	GGGGGCUGUAUCAUUGACA
		(found in oocyte)

	hsa-mir-1244

	hsa-mir-320a

The inventors have investigated the interaction between these microRNA and mRNA from genes identified to be interesting biomarkers in former studies (McKenzie et al., 2004; van Montfoort et al., 2008; Zhang et al., 2005; Assou et al., 2008; Hamel et al., 2008; Hamel et al., 2010; Assou et al. 2010; WO2010/118991).
MicroRNA of the present invention were found to interact with:

- genes whose overexpression is predictive of an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy or an embryo with a high implantation rate leading to pregnancy (group A),
- genes whose overexpression is predictive of a non competent oocyte or embryo, the embryo being unable to implant (group B),
- genes whose overexpression is predictive of a non competent oocyte or embryo due to early embryo arrest (group C),
- genes whose overexpression is inversely correlated with embryo quality (group D),
- genes whose overexpression is correlated with embryo quality (group E).

Genes are known per se and are identified by their symbol. More information about these genes as sequences or name corresponding to the symbol can be found on Targetscan (http://www.targetscan.org/) and MiRDB (http://mirdb.or/cgi-bin/search.cgi).
Tables A, B, C, D and E show the microRNA contingent to genes with which they interact.
Some microRNA, as hsa-let7a or hsa-mir-182, interact with several genes.
Each table correspond to one group A, B, C, D and E corresponding to specific oocyte or embryo qualities as capacity of an embryo to implant or to develop without arrest as described above.

TABLE A

microRNA interacting with genes of group A

Gene with which the microRNA interacts

MicroRNA	Gene		Gene
name	symbol	Gene name	ID

hsa-mir-30d	CAMTA1	calmodulin binding transcription	23261
		activator 1
hsa-mir-30a	CAMTA1	calmodulin binding transcription	23261
		activator 1
SEQ ID NO: 15	PCK1	phosphoenolpyruvate carboxy-	5105
		kinase 1 (soluble)
SEQ ID NO: 16	PCK1	phosphoenolpyruvate carboxy-	5105
		kinase 1 (soluble)
SEQ ID NO: 17	PCK1	phosphoenolpyruvate carboxy-	5105
		kinase 1 (soluble)
SEQ ID NO: 24	SLAMF6	SLAM family member 6	114836
(found in oocyte)

TABLE B

microRNA interacting with genes of group B

Gene with which the microRNA interacts

MicroRNA	Gene		Gene
name	symbol	Gene name	ID

hsa-mir-182	EGR3	early growth response 3	1960
hsa-mir-508	FOSB	FBJ murine osteosarcoma viral	2354
		oncogene homolog B
SEQ ID NO: 6	FOSB	FBJ murine osteosarcoma viral	2354
		oncogene homolog B
hsa-let-7a	GPC6	glypican 6	10082
hsa-mir-103	GPC6	glypican 6	10082
SEQ ID NO: 7	GPC6	′glypican 6	10082
SEQ ID NO: 8	GPC6	glypican 6	10082
hsa-mir-1826	PDE5A	phosphodiesterase 5A, cGMP-	8654
		specific
SEQ ID NO: 9	PDE5A	phosphodiesterase 5A, cGMP-	8654
		specific
hsa-mir-508	SLC40A1	solute carrier family 40 (iron-	30061
		regulated transporter), member 1

TABLE C

microRNA interacting with genes of group C

Gene with which the microRNA interacts

MicroRNA	Gene		Gene
name	symbol	Gene name	ID

hsa-mir-16	G0S2	G0/G1switch 2	50486
SEQ ID NO: 10	GRIK5	glutamate receptor, ionotropic,	2901
		kainate 5
hsa-mir-182	IGF1R	insulin-like growth factor 1	3480
		receptor
hsa-mir-320a	IGF1R	insulin-like growth factor 1	3480
		receptor
hsa-let-7b	IGF1R	insulin-like growth factor 1	3480
		receptor
hsa-let-7c	IGF1R	insulin-like growth factor 1	3480
		receptor
hsa-let-7f	IGF1R	insulin-like growth factor 1	3480
		receptor
hsa-let-7a	IGF1R	insulin-like growth factor 1	3480
		receptor
SEQ ID NO: 11	IGF1R	insulin-like growth factor 1	3480
		receptor
hsa-mir-21	NFIB	nuclear factor I/B	4781
hsa-mir-30d	NFIB	nuclear factor I/B	4781
hsa-mir-30a	NFIB	nuclear factor I/B	4781
SEQ ID NO: 12	NFIC	′nuclear factor I/C (CCAAT-	4782
		binding transcription factor)
SEQ ID NO: 22	NFIC	′nuclear factor I/C (CCAAT-	4782
(found in oocyte)		binding transcription factor)
hsa-mir-1826	RBMS1	RNA binding motif, single	5937
		stranded interacting protein 1

TABLE D

MicroRNA interacting with genes of group D

Gene with which the microRNA interacts

MicroRNA	Gene		Gene
name	symbol	Gene name	ID

SEQ ID NO: 23	FAT3	FAT tumor suppressor homolog 3	120114
(found in oocyte)		(Drosophila)
hsa-mir-92a	SOX4	SRY (sex determining region Y)-	6659
		box 4
SEQ ID NO: 13	SOX4	′SRY (sex determining region Y)-	6659
		box 4
SEQ ID NO: 14	SOX4	′SRY (sex determining region Y)-	6659
		box 4

TABLE E

microRNA interacting with genes of group E

Gene with which the microRNA interacts

MicroRNA	Gene		Gene
name	symbol	Gene name	ID

SEQ ID NO: 20	EPOR	erythropoietin receptor	2057
(found in oocyte)
SEQ ID NO: 18	LRCH4	leucine-rich repeats and calponin	4034
		homology (CH) domain contain-
		ing
SEQ ID NO: 19	NLRP1	NLR family, pyrin domain con-	22861
		taining 1
SEQ ID NO: 20	PAX8	paired box 8	7849
SEQ ID NO: 21	SLC25A5	solute carrier family 25 (mito-	292
		chondrial carrier; adenine nucle-
		otide translocator), member 5
hsa-mir-1244	SLC5A12	solute carrier family 5 (sodium/	159963
		glucose cotransporter), member
		12
hsa-mir-320a	SLCO1A2	solute carrier organic anion	6579
		transporter family, member 1A2

Owing to the role of microRNA in post-transcriptional gene regulation, the microRNA of the invention are involved in the regulation of genes listed in tables A, B, C, D and E and subsequently in the associated pregnancy outcome.
An object of the invention relates to a method for selecting an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy, comprising a step of measuring in a cumulus cell surrounding said oocyte the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1826, hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7f, hsa-mir-1244, hsa-mir-182, hsa-mir-21, hsa-mir-30a, hsa-mir-30d, hsa-mir-320a, hsa-mir-508, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-1974, hsa-mir-146b, hsa-mir-886, hsa-mir-210, hsa-mir-1979, hsa-mir-125a, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20 and SEQ ID NO: 21.
The present invention also relates to a method for selecting an embryo with a high implantation rate leading to pregnancy, comprising a step of measuring in a cumulus cell surrounding said embryo the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1826, hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7f, hsa-mir-1244, hsa-mir-182, hsa-mir-21, hsa-mir-30a, hsa-mir-30d, hsa-mir-320a, hsa-mir-508, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-1974, hsa-mir-146b, hsa-mir-886, hsa-mir-210, hsa-mir-1979, hsa-mir-125a, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20 and SEQ ID NO: 21.
Typically, the expression level of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41 or 42 microRNA may be measured.
In one embodiment, the redundancy is avoided by selecting no more than one microRNA for each gene listed in table A, B, C, D and E.
In one embodiment, the redundancy is avoided by selecting only one or two microRNA by group A, B, C, D or E.
In another embodiment, the methods of the present invention comprises a step of measuring the expression level of at least 5 microRNA selected from the consisting of hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1826, hsa-let-7b, hsa-let-7c, hsa-mir-1244, hsa-mir-182, hsa-mir-21, hsa-mir-30a, hsa-mir-30d, hsa-mir-320a, hsa-mir-508, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-1974, hsa-mir-146b, hsa-mir-886, hsa-mir-210, hsa-mir-1979, hsa-mir-125a, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20 and SEQ ID NO: 21.
In another embodiment, the methods of the present invention comprise a step of measuring the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-508, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1974, hsa-mir-1826, SEQ ID NO: 7, SEQ ID NO: 8 and SEQ ID NO: 12.
Indeed, the inventors have shown that these microRNAs present the more significant difference in level of expression between competent oocytes or embryos and oocytes or embryos that are not competent.
In another embodiment, the methods of the present invention comprise a step of measuring the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-508, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1974, hsa-mir-1826, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 12, hsa-let-7b, hsa-let-7c, hsa-mir-182, hsa-mir-21, hsa-mir-30a and hsa-mir-30d.
Indeed, the inventors have shown that these miRNAs interact with genes particularly relevant in the prediction of the competence of oocytes and embryos such as IGF1R and NFIB.
The present invention also relates to a method for selecting an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy or an embryo with a high implantation rate leading to pregnancy, comprising a step of measuring in a bodily fluid the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1826, hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7f, hsa-mir-1244, hsa-mir-182, hsa-mir-21, hsa-mir-30a, hsa-mir-30d, hsa-mir-320a, hsa-mir-508, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-1974, hsa-mir-146b, hsa-mir-886, hsa-mir-210, hsa-mir-1979, hsa-mir-125a, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO:24 and SEQ ID NO: 25.
It is well-known that microRNAs can circulate in bodily fluid.
Thus, Zheng et al. (2011) have shown that hsa-mir-182 is present in plasma and saliva.
Furthermore, Huang et al. (2009), Lawrie et al. (2008), Asaga et al. (2011) and Henegan et al. (2010) have respectively found that hsa-mir-320a, hsa-mir-210, hsa-mir-21 and hsa-let-7a-1 are circulating miRNAs.
Gunel et al. (2011) have shown that increased hsa-mir-210 levels in maternal serum can be used in noninvasive prenatal diagnosis. The expression level of microRNA may be measured in blood, urine, saliva or follicular liquid sample.
The blood sample to be used in the methods according to the invention may be a whole blood sample, a serum sample, or a plasma sample.
The bodily fluid may be taken from the oocyte donor or the host of the embryo.
In one embodiment, the methods of the present invention comprise a step of measuring the expression level of at least 5 microRNAs selected from the group consisting of hsa-mir-182, hsa-mir-320a, hsa-mir-210, hsa-mir-21, hsa-let-7a-1.
The methods of the invention may further comprise a step consisting of comparing the expression level of the microRNA in the sample with a control, wherein detecting differential in the expression level of the microRNA between the sample and the control is indicative whether the oocyte produces, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy or the embryo is with a high implantation rate leading to pregnancy.
The control for oocyte may consist in sample comprising cumulus cells associated with a competent oocyte or a non competent oocyte or in sample comprising cumulus cells associated with an embryo that gives rise to a viable foetus.
Preferably, the control consists in sample comprising cumulus cells associated with a competent oocyte.
The control for embryo may consist in sample comprising cumulus cells associated with an embryo that gives rise to a viable foetus or in a sample comprising cumulus cells associated with an embryo that does not give rise to a viable foetus.
Preferably, the control consists in sample comprising cumulus cells associated with an embryo that gives rise to a viable foetus.
The methods of the invention may further comprise a step of measuring in a cumulus cell surrounding said oocyte or said embryo the expression level of one or more genes selected from the group consisting of ATF3, SIAT6, PRKACA, PLA2G5, GPC6, GOS2, RBMS1, NFIC, SLC40A1 and WNT6.
Typically, the method of the invention may comprise a further step of measuring the expression level of 1, 2, 3, 4, 5, 6, 7, 8, 9 or 10 genes selected from the group consisting of ATF3, SIAT6, PRKACA, PLA2G5, GPC6, GOS2, RBMS1, NFIC, SLC40A1 and WNT6.
Indeed, as described in WO2010/18991, the inventors have identified a set of 45 genes whose measuring the level of expression in cumulus cells is predictive of pregnancy outcome.
After complementary studies, the inventors have determined a subset of 10 genes comprising ATF3, SIAT6, PRKACA, PLA2G5, GPC6, GOS2, RBMS1, NFIC, SLC40A1 and WNT6. This subset appeared to be one of the most reliable set to select an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy or an embryo with a high implantation rate leading to pregnancy in regard of different clinical conditions as shown in Table F.

TABLE F

Clinical conditions predicted by the set of predictive genes

Gene
Symbol	Gene name	Gene ID

B: genes whose overexpressions are predictive

of embryos unable to implant

PLA2G5	phospholipase A2, group V	5322
GPC6	glypican 6	10082
ATF3	activating transcription factor 3	467
SIAT6	ST3 beta-galactoside alpha-2,3-sialyltrans-	6487
	ferase 3
PRKACA	protein kinase, cAMP-dependent, catalytic,	5566
	alpha
SLC40A1	solute carrier family 40 (iron-regulated trans-	30061
	porter), member 1
WNT6	wingless-type MMTV integration site family,	7475
	member 6

C: genes whose overexpressions are predictive

of early embryo arrest

NFIC	nuclear factor I/C (CCAAT-binding trans-	4782
	cription factor)
RBMS1	RNA binding motif, single stranded inter-	5937
	acting protein 1
G0S2	G0/G1 switch 2	50486

Preferably, genes and microRNA of the present invention aren't measured in a redundant way that is to say that if a microRNA is selected, the gene with which it interacts won't be selected.
In one embodiment, to avoid any redundancy, the method of the invention may comprise a further step of measuring the expression level of 1 or 2 genes selected from group B and 1 or 2 genes selected from group C.
Alternatively, said one or more genes may be selected for example from group B alone or group C alone.
Typically, 1, 2, 3, 4, 5, 6 or 7 genes may be selected from group B.
Typically, 1, 2 or 3 genes may be selected from group C.
The present invention also relates to a method for selecting an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy or an embryo with a high implantation rate leading to pregnancy, comprising a step of measuring in the culture medium of cumulus cell having surrounded said oocyte or said embryo the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1826, hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7f, hsa-mir-1244, hsa-mir-182, hsa-mir-21, hsa-mir-30a, hsa-mir-30d, hsa-mir-320a, hsa-mir-508, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-1974, hsa-mir-146b, hsa-mir-886, hsa-mir-210, hsa-mir-1979, hsa-mir-125a, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20 and SEQ ID NO: 21.
The methods of the invention are particularly suitable for assessing the efficacy of an in vitro fertilization treatment. Accordingly the invention also relates to a method for assessing the efficacy of a controlled ovarian hyperstimulation (COS) protocol in a female subject comprising:
i) providing from said female subject at least one oocyte with its cumulus cells;
ii) determining by a method of the invention whether said oocyte is an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy e.
Then after such a method, the embryologist may select the oocytes that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy and in vitro fertilized them through a classical in vitro fertilization (cIVF) protocol or under an intracytoplasmic sperm injection (ICSI) protocol.
A further object of the invention relates to a method for monitoring the efficacy of a controlled ovarian hyperstimulation (COS) protocol comprising:
i) isolating from said woman at least one oocyte with its cumulus cells under natural, modified or stimulated cycles;
ii) determining by a method of the invention whether said oocyte is an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy;
iii) and monitoring the efficacy of COS treatment based on whether it results in an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy.
The COS treatment may be based on at least one active ingredient selected from the group consisting of GnRH agonists or antagonists associated with recombinant FSH or hMG.
The present invention also relates to a method for determining whether an embryo is an embryo with a high implantation rate leading to pregnancy, comprising:
i) providing an oocyte with its cumulus cells
ii) in vitro fertilizing said oocyte
iii) determining whether the embryo that results from step ii) has a high implantation rate leading to pregnancy by determining by a method of the invention whether said oocyte of step i), is an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy.
The methods of the invention are particularly suitable for enhancing the pregnancy outcome of a female. Accordingly the invention also relates to a method for enhancing the pregnancy outcome of a female comprising:
i) selecting an embryo with a high implantation rate leading to pregnancy by performing a method of the invention
iii) implanting the embryo selected at step i) in the uterus of said female.
The method as above described will thus help embryologist to avoid the transfer in uterus of embryos with a poor potential for pregnancy out come.
The method as above described is also particularly suitable for avoiding multiple pregnancies by selecting the competent embryo able to lead to an implantation and a pregnancy.
The invention also relates to a kit for performing the methods as above described, wherein said kit comprises means for measuring the expression level of the microRNA of Table I that are indicative whether the oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy or the embryo with a high implantation rate leading to pregnancy.
It is to note that the methods of the invention leads to an independence from morphological considerations of the embryo. Two embryos may have the same morphological aspects but by a method of the invention may present a different implantation rate leading to pregnancy.
The methods of the invention are applicable preferably to women but may be applicable to other mammals (e.g., primates, dogs, cats, pigs, cows . . . ).
The present invention also relates to an isolated nucleic acid molecule having the nucleotide sequence as set forth in SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO:24 and SEQ ID NO: 25.
In one embodiment, the nucleic acid molecule according to the invention is used in diagnosis of infertility.
The present invention also relates to a method for the diagnosis of infertility comprising the step of measuring the expression level of at least 5 microRNA selected from the group consisting of SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO:24 and SEQ ID NO: 25.

The invention will be further illustrated by the following figures and examples. However, these examples and figures should not be interpreted in any way as limiting the scope of the present invention.

FIGS. 1 to 4 are diagrams illustrating molecular pathways and functional groupings between microRNA and biomarkers genes.

These diagrams were done by using the Ingenuity Pathways Analysis (IPA) system (Ingenuity Systems, Redwood City, Calif., USA) thank to published literature related to above mentioned miRNA and genes. Above mentioned miRNA and genes were uploaded into IPA and overlaid onto a global molecular network developed from information contained in the application. Networks of these miRNA and genes were generated by IPA based on their connectivity (FIG. 1 to 4). The biological relationship between two nodes is represented as an edge (line). All lines are supported by at least one reference in literature, textbook, or from canonical information stored in the Ingenuity Pathways knowledge database.

Example

Samples:
Cumulus cells and mature MII oocytes were collected from patients consulting for conventional IVF (cIVF) or for ICSI (male infertility). Cumulus cells were removed from a mature oocyte (MII). CCs were partially separated mechanically from the corresponding oocyte as previously described (Assou et al., 2008). Unfertilized MII oocytes were collected 21 or 44 h after insemination or after microinjection by ICSI. Cumulus cells and oocytes were frozen at −80° C. in RLT buffer (RNeasy Kit, Qiagen, Valencia, Calif.) before miRNA extraction.
Methods for Determining the Expression Level of the microRNA:
Determination of the expression level of the microRNA can be performed by a variety of techniques known in the art.
Preferably, small RNA from cumulus cells and mature MII oocyte samples was extracted after storage of samples at −80° C. in RLT RNA extraction buffer supplemented with 1 μM of 2-β-mercaptoethanol (M-3148, Sigma) as described in the manufacturer's protocol (miRNeasy mini Kit, Qiagen, Valencia, Calif.).
The 5′ RNA adapter (5′-GUUCAGAGUUCUACAGUCCGACGAUC-3′ (SEQ ID NO: 1)) was ligated to the RNA pool with T4 RNA ligase (Ambion) in the presence of RNase Out (Invitrogen) overnight at 25° C. The ligation reaction was stopped by the addition of 2× formamide loading dye. The ligated RNA was size fractionated on a 15% TBE urea polyacrylamide gel and a 40-60 base pair fraction was excised. RNA was eluted from the polyacrylamide gel slice in 600 μL of 0.3 M NaCl overnight at 4° C. The RNA was eluted from the gel and precipitated as described above followed by resuspension in DEPC-treated water.
The 3′ RNA adapter ((SEQ ID NO: 2) 5′-pUCGUAUGCCGUCUUCUGCUUGidT-3; p, phosphate; idT, inverted deoxythymidine) was subsequently ligated to the precipitated RNA with T4 RNA ligase (Ambion) in the presence of RNase Out (Invitrogen) overnight at 25° C. The ligation reaction was stopped by the addition of 10 μL of 2× formamide loading dye. Ligated RNA was size fractionated on a 10% TBE urea polyacrylamide gel and the 60-100 base pair fraction was excised. The RNA was eluted from the polyacrylamide gel and precipitated from the gel as described above and resuspended in 5.0 μL of DEPC water. The RNA was converted to single-stranded cDNA using Superscript II reverse transcriptase (Invitrogen) and Illumina's small RNA RT-Primer (5′-CAAGCAGAAGACGGCATACGA-3′ (SEQ ID NO: 3)) following the manufacturer's instructions. The resulting cDNA was PCR-amplified with Hotstart Phusion DNA Polymerase (NEB) in 15 cycles using Illumina's small RNA primer set (5′-CAAGCAGAAGACG GCATACGA-3′ (SEQ ID NO: 4); 5′-AATGATACGGCGACCACCGA-3′ (SEQ ID NO: 5)).
PCR products were purified on a 12% TBE urea polyacrylamide gel and eluted into elution buffer (5:1, LoTE: 7.5 M ammonium acetate) overnight at 4° C. The resulting gel slurry was passed through a Spin-X filter (Corning) and precipitated by the addition of 1100 μL of ethanol, 133 μL of 7.5 M ammonium acetate and 3 μL of mussel glycogen (20 mg/mL; Invitrogen). After washing with 75% ethanol, the pellet was allowed to air dry at 25° C. and dissolved in EB buffer (Qiagen) by incubation at 4° C. for 10 min. The purified PCR products were quantified on the Agilent DNA 1000 chip and diluted to 10 nM for sequencing on the Illumina 1G.
Small RNA Annotation
We trimmed all reads at 30 nt to reduce the number of unique sequences. We counted the occurrences of each unique sequence read and used only the unique sequences for further analysis. All sequence tags are mapped onto the human reference genome using the SOAP program following the mirTools web server procedure (Zhu E L, Zhao F Q, et al., NAR 2010). Subsequently, these unique sequence tags are also aligned against miRBase (Griffiths-Jones, S et al. NAR 2008), Rfam (Griffiths-Jones, S et al, NAR 2005), repeat database produced by RepeatMasker (Tarailo-Graovac, M. and Chen, N. (2009) Curr. Protoc. Bioinform., Chapter 4, Unit 4. 108.) and the coding genes of the reference genome. In this way, the unique sequence tags can be classified into the following categories: known microRNA, degradation fragments of non-coding RNA, genomic repeats and mRNA. In case of conflict, a hierarchy is conducted to assign the tag into a unique category, which starts with non-coding RNA, then known microRNA and followed by repeat associated RNA and mRNA. Sequences that are assigned to none of these annotations but can be mapped to the reference genome are classified as ‘unclassified’.
A microRNA target prediction were done using known microRNA and TargetScan data (release 4.0) which provides predicted targets for known microRNAs (http://www.targetscan.org/).
Differential Expression Detection
To compare differentially expressed microRNA between multiple samples, read count of each identified microRNA is normalized to the total number of microRNA read counts that are matched to the reference genome in each sample. The statistical significance (P-value) is inferred based on a Bayesian method (Audic, S. and Claverie, J. M. (1997) Genome Res.,), which was developed for analyzing digital gene expression profiles and could account for the sampling variability of tags with low counts. In default, a specific microRNA will be deemed to be significantly differentially expressed when the P-value given by this method is 0.01 and there is at least a 2-fold change in normalized sequence counts.
Novel microRNA Prediction
Sequences that do not fall into above annotation categories but matched on the reference genome are used to detect candidate novel microRNA genes. In default, 100 nucleotides of genomic sequence flanking each side of these sequences are extracted and their RNA secondary structures are predicted using RNAfold (Hofacker, I. L. NAR 2003). Novel microRNAs are identified by folding the flanking genomic sequence using the miRDeep program.
Methods for Determining the Expression Level of the Genes:
Determination of the expression level of genes as ATF3, SIAT6, PRKACA, PLA2G5, GPC6, G0S2, RBMS1, NFIC, SLC40A1 or WNT6 can be performed by a variety of techniques. Generally, the expression level as determined is a relative expression level.
Some of these methods are well described in WO2010/118991.
Results
Analysis of level of expression of microRNA in CCs has permitted to identify candidate microRNA biomarkers.
Known microRNA
Known microRNA from CCs group are listed in Table G.

TABLE G

Set of known predicitve microRNA:

microRNAs	Length	startend	location	e_value

hsa-mir-1974	26	1 . . . 26	45 . . . 70	2.00E−10
hsa-let-7b	18	1 . . . 18	6 . . . 23	7.00E−06
hsa-mir-1244	22	1 . . . 22	57 . . . 78	4.00E−08
hsa-mir-30d	24	1 . . . 24	6 . . . 29	3.00E−09
hsa-mir-182	19	1 . . . 19	28 . . . 46	2.00E−06
hsa-mir-146b	24	1 . . . 24	9 . . . 32	3.00E−09
hsa-let-7c	19	1 . . . 19	11 . . . 29	2.00E−06
hsa-mir-92a-2	22	1 . . . 22	48 . . . 69	4.00E−08
hsa-mir-92a-1	22	1 . . . 22	48 . . . 69	4.00E−08
hsa-mir-886	25	1 . . . 25	15 . . . 39	7.00E−10
hsa-mir-508	22	1 . . . 22	61 . . . 82	4.00E−08
hsa-mir-320a	18	1 . . . 18	52 . . . 69	7.00E−06
hsa-mir-30a	24	1 . . . 24	6 . . . 29	3.00E−09
hsa-mir-210	19	1 . . . 19	66 . . . 84	2.00E−06
hsa-mir-21	22	1 . . . 22	9 . . . 30	4.00E−08
hsa-mir-1979	24	1 . . . 24	6 . . . 29	3.00E−09
hsa-mir-1826	24	1 . . . 24	1 . . . 24	3.00E−09
hsa-mir-16-2	19	1 . . . 19	10 . . . 28	2.00E−06
hsa-mir-16-1	19	1 . . . 19	14 . . . 32	2.00E−06
hsa-mir-125a	24	1 . . . 24	15 . . . 38	3.00E−09
hsa-mir-103-2	22	1 . . . 22	48 . . . 69	4.00E−08
hsa-mir-103-1	22	1 . . . 22	48 . . . 69	4.00E−08
hsa-let-7a-3	20	1 . . . 20	4 . . . 23	5.00E−07
hsa-let-7a-2	20	1 . . . 20	5 . . . 24	5.00E−07
hsa-let-7a-1	20	1 . . . 20	6 . . . 25	5.00E−07
hsa-let-7f	22	1 . . . 22	7 . . . 28	4.00E−07

The interaction between these microRNA and mRNA from gene identified to be potential biomarkers by the inventors (WO2010/118991, Assou et al., 2008; Assou et al. 2010) was studied by using TargetScan.
TargetScan predicts biological targets of miRNAs by searching for the presence of conserved 8mer and 7mer sites that match the seed region of each miRNA (Lewis et al., 2005). As an option, nonconserved sites are also predicted. Also identified are sites with mismatches in the seed region that are compensated by conserved 3′ pairing (Friedman et al., 2009). In mammals, predictions are ranked based on the predicted efficacy of targeting as calculated using the context scores of the sites (Grimson et al., 2007). TargetScanHuman considers matches to annotated human UTRs and their orthologs, as defined by UCSC whole-genome alignments. Conserved targeting has also been detected within open reading frames (ORFs).
Other database as MiRDB (http://mirdb.org/cgi-bin/search.cgi) and Ingenuity (IPA) have also been used.
Some of these interactions are illustrated in FIGS. 1 to 4.
New microRNA Biomarkers
The inventors have identified novel microRNA among the unclassified sequences in their libraries. After annotation, 5,165 of the microRNA sequences in the CCs library remained unclassified because they derived from unannotated regions of the human genome. Novel microRNA were identified. These microRNA regulate the expression of 7 gene biomarkers such as: (PCK1 (3 microRNA:SEQ ID NO: 15; SEQ ID NO: 16; SEQ ID NO: 17); GPC6 (2 microRNA:SEQ ID NO: 7, SEQ ID NO: 8); SOX4 (2 microRNA:SEQ ID NO: 13, SEQ ID NO: 14); SLC25A5 (1 microRNA:SEQ ID NO: 21); NFIC (1 microRNA:SEQ ID NO: 12; SEQ ID NO: 22); IGF1R (1 microRNA:SEQ ID NO:11); GIRK5 (1 microRNA:SEQ ID NO: 10)).
Interactions microARN and Genes Identified to be Interesting Biomarkers
The inventors have investigated the interaction between these microRNA and mRNA from genes identified to be interesting biomarkers in former studies (McKenzie et al., 2004; van Montfoort et al., 2008; Zhang et al., 2005; Assou et al., 2008; Hamel et al., 2008; Hamel et al., 2010; Assou et al. 2010; WO2010/118991).
MiRNA are known to be post-transcriptional regulators that bind to complementary sequences on target messenger RNA transcripts (mRNAs), usually resulting in translational repression or target degradation and gene silencing (Bartel et DP (2009)).
Thus, without being bound by theory, the under-expression of most microRNA that interact with a gene whose overexpression is predictive of a competent oocyte or a competent embryo is predictive of an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy or of an embryo with a high implantation rate leading to pregnancy.
In the same way, the under-expression of most microRNA that interact with a gene whose overexpression is predictive of an oocyte or an embryo that is not competent is predictive of an oocyte or an embryo that is not competent.
For example, SEQ ID NO: 23, hsa-mir-92a, SEQ ID NO: 13 and SEQ ID NO: 14 interact with genes of group D. Thus, their under-expression can be predictive of a bad quality embryo.
Conversely, the overexpression of most microRNA that interact with a gene whose under-expression is predictive of a competent oocyte or a competent embryo is predictive of an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy or of an embryo with a high implantation rate leading to pregnancy.
By extension, the overexpression of most miRNA that interact with a gene whose overexpression is predictive of embryo unable to implant, early embryo arrest or a bad quality embryo is predictive of an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy or of an embryo with a high implantation rate leading to pregnancy.
For example, overexpression of a miRNA interacting with genes of groups B, C and D can be predictive of an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy or of an embryo with a high implantation rate leading to pregnancy when it is under-expressed.

CONCLUSION

CC gene and microRNA expression analysis begins to be a valuable tool for improving embryo selection, either for fresh embryo replacement or for freezing. According to our preliminary data, there is no relationship between the gene expression profile of CCs and the embryo morphological aspects. It is time to reconsider the notion that embryos presenting a low grade according morphological aspects are able to achieve pregnancy. Indeed, during the last decade, the availability of technical platforms, small RNA library sequencing and whole genome microarrays has rapidly generated data on the molecular mechanisms of the CC-oocyte complex. Today, these technologies provide potential predictive biomarkers as non-invasive tools for clinical applications. Finally, this concept reveals the potential of CCs microRNA to serve as molecular biomarkers for embryo selection.

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Throughout this application, various references describe the state of the art to which this invention pertains. The disclosures of these references are hereby incorporated by reference into the present disclosure.

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Claims

1. A method for selecting an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy, comprising a step of measuring in a cumulus cell surrounding said oocyte the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1826, hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7f, hsa-mir-1244, hsa-mir-182, hsa-mir-21, hsa-mir-30a, hsa-mir-30d, hsa-mir-320a, hsa-mir-508, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-1974, hsa-mir-146b, hsa-mir-886, hsa-mir-210, hsa-mir-1979, hsa-mir-125a, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20 and SEQ ID NO: 21.

2-10. (canceled)

11. The method according to claim 1 wherein said at least 5 microRNA are selected from the group consisting of hsa-mir-508, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1974, hsa-mir-1826, SEQ ID NO: 7, SEQ ID NO: 8 and SEQ ID NO: 12.

12. The method according to claim 1 wherein said at least 5 microRNA are selected from the group consisting of hsa-mir-508, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-103-1, has-mir-103-2, hsa-mir-1974, hsa-mir-1826, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 12, hsa-let-7b, hsa-let-7c, hsa-mir-182, hsa-mir-21, hsa-mir-30a and hsa-mir-30d.

13. The method according to claim 1 wherein said at least 5 microRNA are selected from the group consisting of hsa-mir-182, hsa-mir-320a, hsa-mir-210, hsa-mir-21 and has-let-7a-1.

14. The method according to claim 1 comprising a further step of measuring in a cumulus cell surrounding said oocyte the expression level of one or more genes selected from the group consisting of ATF3, SIAT6, PRKACA, PLA2G5, GPC6, GOS2, RBMS1, NFIC, SLC40A1 and WNT6.

15. A method for selecting an embryo with a high implantation rate leading to pregnancy, comprising a step of measuring in a cumulus cell surrounding said embryo the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1826, hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7f, hsa-mir-1244, hsa-mir-182, hsa-mir-21, hsa-mir-30a, hsa-mir-30d, hsa-mir-320a, hsa-mir-508, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-1974, hsa-mir-146b, hsa-mir-886, hsa-mir-210, hsa-mir-1979, hsa-mir-125a, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20 and SEQ ID NO: 21.

16. The method according to claim 15 wherein said at least 5 microRNA are selected from the group consisting of hsa-mir-508, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-103-1, has-mir-103-2, hsa-mir-1974, hsa-mir-1826, SEQ ID NO: 7, SEQ ID NO: 8 and SEQ ID NO: 12.

17. The method according to claim 15 wherein said at least 5 microRNA are selected from the group consisting of hsa-mir-508, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-103-1, has-mir-103-2, hsa-mir-1974, hsa-mir-1826, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 12, hsa-let-7b, hsa-let-7c, hsa-mir-182, hsa-mir-21, hsa-mir-30a and hsa-mir-30d.

18. The method according to claim 15 wherein said at least 5 microRNA are selected from the group consisting of hsa-mir-182, hsa-mir-320a, hsa-mir-210, hsa-mir-21 and has-let-7a-1.

19. The method according to claim 15 comprising a further step of measuring in a cumulus cell surrounding said embryo the expression level of one or more genes selected from the group consisting of ATF3, SIAT6, PRKACA, PLA2G5, GPC6, GOS2, RBMS1, NFIC, SLC40A1 and WNT6.

20. A method for selecting an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy or an embryo with a high implantation rate leading to pregnancy, comprising a step of measuring in the culture medium of cumulus cell having surrounded said oocyte or said embryo the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1826, hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7f, hsa-mir-1244, hsa-mir-182, hsa-mir-21, hsa-mir-30a, hsa-mir-30d, hsa-mir-320a, hsa-mir-508, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-1974, hsa-mir-146b, hsa-mir-886, hsa-mir-210, hsa-mir-1979, hsa-mir-125a, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20 and SEQ ID NO: 21.

21. A method for selecting an oocyte that will produce, upon fertilization, a viable embryo with a high implantation rate leading to pregnancy or an embryo with a high implantation rate leading to pregnancy, comprising a step of measuring in a bodily fluid the expression level of at least 5 microRNA selected from the group consisting of hsa-mir-103-1, hsa-mir-103-2, hsa-mir-1826, hsa-let-7a-1, hsa-let-7a-2, hsa-let-7a-3, hsa-let-7b, hsa-let-7c, hsa-let-7f, hsa-mir-1244, hsa-mir-182, hsa-mir-21, hsa-mir-30a, hsa-mir-30d, hsa-mir-320a, hsa-mir-508, hsa-mir-92a-1, hsa-mir-92a-2, hsa-mir-16-1, hsa-mir-16-2, hsa-mir-1974, hsa-mir-146b, hsa-mir-886, hsa-mir-210, hsa-mir-1979, hsa-mir-125a, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO:24 and SEQ ID NO: 25.

22. An isolated nucleic acid molecule having the nucleotide sequence as set forth in SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO:24 and SEQ ID NO: 25.

23. A kit comprising means for measuring the expression level of the microRNA of Table I.