Identification of Loci and Pathways Associated with Heifer Conception Rate in U.S. Holsteins

Galliou, Justine M; Kiser, J. N.; Oliver, Kayleen F; Seabury, Christopher M.; Moraes, J.G.N.; Burns, Gregory W.; Spencer, Thomas E.; Dalton, J.C.; Neibergs, Holly L.

doi:10.3390/genes11070767

Cited by 22 publications

(13 citation statements)

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“…Protein C is a potent anticoagulant and anti-inflammatory molecule which regulates the functions of different epithelial barriers by controlling inflammation [ 30 , 31 ]. Dipeptidyl peptidase-like protein 6 is a transmembrane protein that binds to voltage-gated potassium channels from the Kv4 family [ 32 ], associated with uterine capacity for pregnancy and fertility in beef heifers [ 33 ], and relevant for uterine function [ 34 ].…”

Section: Discussionmentioning

confidence: 99%

Progesterone differentially affects the transcriptomic profiles of cow endometrial cell types

et al. 2022

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Background The endometrium is a heterogeneous tissue composed of luminal epithelial (LE), glandular epithelial (GE), and stromal cells (ST), experiencing progesterone regulated dynamic changes during the estrous cycle. In the cow, this regulation at the transcriptomic level was only evaluated in the whole tissue. This study describes specific gene expression in the three types of cells isolated from endometrial biopsies following laser capture microdissection and the transcriptome changes induced by progesterone in GE and ST cells. Results Endometrial LE, GE, and ST cells show specific transcriptomic profiles. Most of the differentially expressed genes (DEGs) in response to progesterone are cell type-specific (96%). Genes involved in cell cycle and nuclear division are under-expressed in the presence of progesterone in GE, highlighting the anti-proliferative action of progesterone in epithelial cells. Elevated progesterone concentrations are also associated with the under-expression of estrogen receptor 1 (ESR1) in GE and oxytocin receptor (OXTR) in GE and ST cells. In ST cells, transcription factors such as SOX17 and FOXA2, known to regulate uterine epithelial-stromal cross-talk conveying to endometrial receptivity, are over-expressed under progesterone influence. Conclusions The results from this study show that progesterone regulates endometrial function in a cell type-specific way, which is independent of the expression of its main receptor PGR. These novel insights into uterine physiology present the cell compartment as the physiological unit rather than the whole tissue.

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Section: Discussionmentioning

confidence: 99%

Progesterone differentially affects the transcriptomic profiles of cow endometrial cell types

et al. 2022

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“…Functional genes associated with PY in the EARLY stage of lactation were ATF6 and ELMO1 , while MYOF was associated with PY at the PEAK stage of lactation. Galliou et al [ 43 ] reported that ATF6 is associated with the number of inseminations per conception and first service conception in Holstein dairy cows. This study showed that candidate genes found for PY participate in the regulation of transcription from the RNA polymerase II promoter in response to stress, which can be considered as a mechanism to relieve the stress caused by a negative energy balance in the EARLY stage of lactation.…”

Section: Discussionmentioning

confidence: 99%

Genome-Wide Association Study for Lactation Performance in the Early and Peak Stages of Lactation in Holstein Dairy Cows

Zare

Atashi

Hostens

2022

Animals

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This study aimed to detect genomic loci associated with the lactation performance during 9 to 50 days in milk (DIM) in Holstein dairy cows. Daily milk yield (MY), fat yield (FY), and protein yield (PY) during 9 to 50 DIM were recorded on 134 multiparous Holstein dairy cows distributed in four research herds. Fat- and protein-corrected milk (FPCM), fat-corrected milk (FCM), and energy-corrected milk (ECM) were predicted. The records collected during 9 to 25 DIM were put into the early stage of lactation (EARLY) and those collected during 26 to 50 DIM were put into the peak stage of lactation (PEAK). Then, the mean of traits in each cow included in each lactation stage (EARLY and PEAK) were estimated and used as phenotypic observations for the genome-wide association study. The included animals were genotyped with the Illumina BovineHD Genotyping BeadChip (Illumina Inc., San Diego, CA, USA) for a total of 777,962 single nucleotide polymorphisms (SNPs). After quality control, 585,109 variants were analyzed using GEMMA software in a mixed linear model. Although there was no SNP associated with traits included at the 5% genome-wide significance threshold, 18 SNPs were identified to be associated with milk yield and composition at the suggestive genome-wide significance threshold. Candidate genes identified for milk production traits showed contrasting results between the EARLY and PEAK stages of lactation. This suggests that differential sets of candidate genes underlie the phenotypic expression of the considered traits in the EARLY and PEAK stages of lactation. Although further functional studies are needed to validate our findings in independent populations, it can be concluded that in any genomic study it should be taken into account that the genetic effects of genes related to the lactation performance are not constant during the lactation period.

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“…Infertility or subfertility is a critical barrier to sustainable cattle production [2], including in heifers. For example, approximately 15% [3] and 5% [4] of beef and dairy heifers, respectively, do not calve at 24 months of age. Heifers that calve at an optimum age have greater productivity and longevity in the herd [5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…Another potential avenue for the identification of infertile heifers is the use of molecular phenotyping [24]. The pioneering efforts focused on genome-wide association studies (GWAS) to identify genetic markers associated with heifer fertility [4,12,[25][26][27][28][29][30][31][32][33][34][35][36][37][38], but only a few seem to be reproducible across populations [37]. More recent efforts have also focused on transcriptome [39][40][41] and metabolome [42] datasets characterizing these molecules in blood samples.…”

Section: Introductionmentioning

confidence: 99%

A multi-omics analysis identifies molecular features associated with heifer fertility in a case-control design including Angus and Holstein cattle

Marrella

Biase

2022

Preprint

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Background: Infertility or subfertility is a critical barrier to sustainable cattle production, including in heifers. The development of heifers that do not produce a calf within an optimum window of time is a critical factor for the profitability and sustainability of the cattle industry. The early identification of heifers with optimum fertility using molecular phenotyping is a promising approach to improving sustainability in beef and dairy cattle production. Results: Using a high-density single nucleotide polymorphism (SNP) chip, we collected genotypic data from 575,053 SNPs. We also produced quantitative transcriptome data for 12,445 genes (12,105 protein-coding genes, 228 long non-coding RNAs, and 112 pseudogenes) and proteome data for 213 proteins. We identified two SNPs significantly associated with heifer fertility (rs110918927, chr12: 85648422, P = 6.7x10-7; and rs109366560, chr11:37666527, P = 2.6x10-5). We identified two genes with differential transcript abundance (eFDR ≤ 0.002) between the two groups (Fertile and Sub-Fertile): Adipocyte Plasma Membrane Associated Protein (APMAP, 1.16 greater abundance in the Fertile group) and Dynein Axonemal Intermediate Chain 7 (DNAI7, 1.23 greater abundance in the Sub-Fertile group). Our analysis revealed that the protein Alpha-ketoglutarate-dependent dioxygenase FTO was more abundant in the plasma collected from Fertile heifers relative to their Sub-Fertile counterparts (FDR < 0.05). Interestingly, two proteins did not reach the significance threshold in the model accounting for all samples (Apolipoprotein C-II, APOC2 (FDRglmm = 0.06) and Lymphocyte cytosolic protein 1, LCP1 (FDRglmm = 0.06)), but both proteins were less abundant in the plasma of Fertile Holstein heifers (P < 0.05). Lastly, an integrative analysis of the three datasets identified a series of features (SNPs, gene transcripts, and proteins) that can be useful for the discrimination of heifers based on their fertility. When all features were utilized together, 21 out of 22 heifers were classified correctly based on their fertility category. Conclusions: Our multi-omics analyses confirm the complex nature of female fertility. Very importantly, our results also highlight differences in the molecular profile of heifers associated with fertility that transcend the constraints of breed-specific genetic background.

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Identification of Loci and Pathways Associated with Heifer Conception Rate in U.S. Holsteins

Cited by 22 publications

References 84 publications

Progesterone differentially affects the transcriptomic profiles of cow endometrial cell types

Progesterone differentially affects the transcriptomic profiles of cow endometrial cell types

Genome-Wide Association Study for Lactation Performance in the Early and Peak Stages of Lactation in Holstein Dairy Cows

A multi-omics analysis identifies molecular features associated with heifer fertility in a case-control design including Angus and Holstein cattle

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