Quantitative Trait Loci For Fertility Research Articles

Crossbred Bull Fertility Prediction Using a Transcriptome based SNP Methodology

Although various methods have been advanced and introduced to comprehend the most suitable approach for predicting fertility, extensive analysis has been undertaken. The utilization of high-throughput data sequencing has been instrumental in the generation of extensive datasets derived from diverse studies, with a primary focus on elements such as epigenetics, genomic variations, genome-wide associations, and differential gene expression in the context of bull fertility. However, the task of achieving effective prediction remains a formidable challenge. The current investigation aims to examine variations identified through RNA-Seq, with a particular emphasis on coding region alterations, and subsequently, map these variations to the region of genes associated with fertility functions and proximity. In this study, transcriptome analysis was carried over sperm samples obtained from 12 bulls, half of which exhibited high fertility (n = 6) and the other half low fertility (n = 6) based on their conception rates. Bioinformatics tools align the data, genetic variants were identified and mapped subsequently to known fertility quantitative trait loci (QTL). After filtering for fertility-specific single nucleotide polymorphisms (SNPs) with missense mutations, we identified a total of six significant biomarkers. This research demonstrates the efficacy of our innovative approach for screening genetic variants, ultimately leading to the identification of fertility markers within bovine spermatozoa.

Identification of genomic regions associated with total and progressive sperm motility in Italian Holstein bulls.

Sperm motility is directly related to the ability of sperm to move through the female reproductive tract to reach the ovum. Sperm motility is a complex trait that is influenced by environmental and genetic factors and is associated with male fertility, oocyte penetration rate, and reproductive success of cattle. In this study we carried out a GWAS in Italian Holstein bulls to identify candidate regions and genes associated with variations in progressive and total motility (PM and TM, respectively). After quality control, the final data set consisted of 5,960 records from 949 bulls having semen collected in 10 artificial insemination stations and genotyped at 412,737 SNPs (call rate >95%; minor allele frequency >5%). (Co)variance components were estimated using single trait mixed models, and associations between SNPs and phenotypes were assessed using a genomic BLUP approach. Ten windows that explained the greatest percentage of genetic variance were located on Bos taurus autosomes 1, 2, 4, 6, 7, 23, and 26 for TM and Bos taurus autosomes 1, 2, 4, 6, 8, 16, 23, and 26 for PM. A total of 150 genes for TM and 72 genes for PM were identified within these genomic regions. Gene Ontology enrichment analyses identified significant Gene Ontology terms involved with energy homeostasis, membrane functions, sperm-egg interactions, protection against oxidative stress, olfactory receptors, and immune system. There was significant enrichment of quantitative trait loci for fertility, calving ease, immune response, feed intake, and carcass weight within the candidate windows. These results contribute to understanding the architecture of the genetic control of sperm motility and may aid in the development of strategies to identify subfertile bulls and improve reproductive success.

An integrated approach to bovine oocyte quality: from phenotype to genes.

In cattle, early embryonic failure plays a major role in the limitation of reproductive performance and is influenced by genetic effects. Suboptimal oocyte quality, including an inadequate store of maternal factors, is suspected to contribute to this phenomenon. In the present study, 13 Montbeliarde cows were phenotyped on oocyte quality, based on their ability to produce viable embryos after in vitro maturation, fertilisation and culture for 7 days. This discriminated two groups of animals, exhibiting developmental rates below 18.8% or above 40.9% (relative to cleaved embryos). Using microarrays, transcriptomic profiles were compared between oocytes collected in vivo from these two groups of animals. The difference in oocyte development potential was associated with changes in transcripts from 60 genes in immature oocytes and 135 genes in mature oocytes (following Bonferroni 5% correction). Of these, 16 and 32 genes were located in previously identified fertility quantitative trait loci. A subset of differential genes was investigated on distinct samples by reverse transcription-quantitative polymerase chain reaction. For SLC25A16, PPP1R14C, ROBO1, AMDHD1 and MEAF6 transcripts, differential expression was confirmed between high and low oocyte potential animals. Further sequencing and searches for polymorphisms will pave the way for implementing their use in genomic selection.

Analysis of in vivo oocyte maturation, in vitro embryo development and gene expression in cumulus cells of dairy cows and heifers selected for one fertility quantitative trait loci (QTL) located on BTA3

We have previously shown that Holstein cows selected for their homozygous favorable (“fertil+”) or unfavorable (“fertil−”) haplotype at one quantitative trait loci (QTL) of female fertility located on chromosome 3 (QTL-F-Fert-BTA3) had a different success rate 35 and 90 days after the first artificial insemination. To determine whether the lower fertility in “fertil−” animals could be related to oocyte quality, we analyzed the embryo development rate in vitro and the oocyte meiotic maturation in vivo in “fertil+” and “fertil−” heifers. In vitro maturation and fertilization of immature oocytes recovered by ovum pick-up from “fertil+” and “fertil−” heifers resulted in similar cleavage and blastocyst rates in the two haplotypes. However the percentage of expanded blastocysts and the number of cells per blastocyst were significantly higher in “fertil+”. Oocytes from presumptive preovulatory follicles were analyzed after ovarian stimulation. A similar rate of immature (from prophase to metaphase-I) and mature oocytes (metaphase-II) was obtained in the two haplotypes, whereas a significantly higher percentage of oocytes from metaphase-I to metaphase-II was observed in “fertil+” compared to “fertil−” heifers. Since cumulus cells (CCs) could reflect the developmental competence of oocytes, we analyzed the expression of seven genes included in the QTL-F-Fert-BTA3 using real-time PCR in bovine CCs after in vivo or in vitro maturation, as a model of higher and lower competence, respectively. Transcript levels of TAGLN2, EEF1A1 and PIGM were higher in CCs after in vitro maturation (IVM) compared to in vivo maturation, whereas no difference was observed for IFI16, KIRREL, SPTA1 and PEX19 expression. The expression levels of all these genes in in preovulatory CCs were not significantly different between “fertil+” and “fertil−” heifers. In conclusion, the lower fertility of “fertil−” females could be partially due to a lowest quality of the oocytes and consequently of preimplantation embryo development.

Genome‐wide association mapping in Norwegian Red cattle identifies quantitative trait loci for fertility and milk production on BTA12

Reproductive performance is a critical trait in dairy cattle. Poor reproductive performance leads to prolonged calving intervals, higher culling rates and extra expenses related to multiple inseminations, veterinary treatments and replacements. Genetic gain for improved reproduction through traditional selection is often slow because of low heritability and negative correlations with production traits. Detection of DNA markers associated with improved reproductive performance through genome-wide association studies could lead to genetic gain that is more balanced between fertility and production. Norwegian Red cattle are well suited for such studies, as very large numbers of detailed reproduction records are available. We conducted a genome-wide association study for non-return rate, fertility treatments and retained placenta using almost 1 million records on these traits and 17 343 genome-wide single-nucleotide polymorphisms. Genotyping costs were minimized by genotyping the sires of the cows recorded and by using daughter averages as phenotypes. The genotyped sires were assigned to either a discovery or a validation population. Associations were only considered to be validated if they were significant in both groups. Strong associations were found and validated on chromosomes 1, 5, 8, 9, 11 and 12. Several of these were highly supported by findings in other studies. The most important result was an association for non-return rate in heifers in a region of BTA12 where several associations for milk production traits have previously been found. Subsequent fine-mapping verified the presence of a quantitative trait loci (QTL) having opposing effects on non-return rate and milk production at 18 Mb. The other reproduction QTL did not have pleiotropic effects on milk production, and these are therefore of considerable interest for use in marker-assisted selection.

A validated genome-wide association study in 2 dairy cattle breeds for milk production and fertility traits using variable length haplotypes

Genome-wide association studies (GWAS) were used to discover genomic regions explaining variation in dairy production and fertility traits. Associations were detected with either single nucleotide polymorphism (SNP) markers or haplotypes of SNP alleles. An across-breed validation strategy was used to narrow the genomic interval containing causative mutations. There were 39,048 SNP tested in a discovery population of 780 Holstein sires and validated in 386 Holsteins and 364 Jersey sires. Previously identified mutations affecting milk production traits were confirmed. In addition, several novel regions were identified, including a putative quantitative trait loci for fertility on chromosome 18 that was detected only using haplotypes greater than 3 SNP long. It was found that the precision of quantitative trait loci mapping increased with haplotype length as did the number of validated haplotypes discovered, especially across breed. Promising candidate genes have been identified in several of the validated regions.

Overlapping chromosomal regions for fertility traits and production traits in the Danish Holstein population

Before implementing selection based on quantitative trait loci (QTL) for fertility, it is important to determine the existence of correlated effects between the fertility QTL and QTL with effects on production traits. When a QTL is detected for a trait that is a composite of subtraits, it is of interest to validate which of the subtraits are affected by the QTL. Phenotypic and marker data were collected from 34 grandsire families from the Danish Holstein population. First, the trait data for “fertility treatments” were separated into their underlying subtraits: uterine infections, antibiotics placed in the placenta, and abortions. In addition, retained placenta was selected for analysis because it is related to uterine infections. A genome scan was performed using 416 microsatellite markers for the fertility treatment subtraits and retained placenta, and an additional genome scan for milk production traits conditional on the QTL regions for the subtraits and retained placenta was conducted. Second, we selected 24 genomic regions harboring QTL for fertility traits from a previous study. A QTL scan for milk production traits conditional on the selected regions was conducted. We found that 16 selected genomic regions containing a QTL for fertility (including the fertility treatment subtraits and retained placenta) also harbored QTL for milk yield or milk composition traits. Furthermore, 12 QTL regions corresponding to 9 different fertility traits (including the fertility treatment subtraits) did not harbor a QTL for milk production or milk composition traits; that is, the region was specific for the fertility trait. The genome scan for the fertility treatment subtraits did not correspond to the QTL found for fertility treatments. No QTL were detected for the subtrait abortion, however genome scans for retained placenta revealed 4 different QTL.

Mapping quantitative trait loci affecting life history traits in the nematode Caenorhabditis elegans.

We have identified chromosomal regions containing quantitative trait loci (QTLs) specifying life history traits in recombinant-inbred strains of the nematode Caenorhabditis elegans. This approach also allows us to examine epistatic interactions between loci and pleiotropic effects on different traits at specific loci. QTLs for mean life span were identified on chromosomes II (near stP101), IV (stP5) and the X (stP61), and QTLs for fertility were identified on II (maPI), III (stP19) and IV (stP51). The QTLs for mean life span accounted for 90% of the genetic component of variance. The loci for mean fertility accounted for 88% of the genetic component of variance. Additional QTLs for temperature-sensitive fertility [II (stP36) and V (stP6)] and internal hatching [IV (stP5)] were also mapped in these crosses. We found evidence for epistatic effects on mean life span between maP1 and bP1 (V), and for epistatic effects on mean fertility between stP36 and stP6, between stP98 (II) and stP192 (V), between maP1 and stP127 (III), between maP1 and stP103 (X), and between stP5 and stP6. Negatively correlated, pleiotropic effects on mean life span and internal hatching were found linked to stP5.