Will AI in pigs become more efficient?

Roca, Jordi; Parrilla, Inmaculada; Bolarín, Alfonso; Martı́nez, Emilio A.; Rodriguez‐Martinez, Heriberto

doi:10.1016/j.theriogenology.2015.11.026

Cited by 66 publications

(70 citation statements)

References 50 publications

(56 reference statements)

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“…As in human, the boar ejaculate is expelled in fractions, the SRF and the post-SRF being the two main fractions, with relevant differences in SP-composition [43] including cytokine-contents [44] and antioxidant enzymes [45]. Further research is required to verify possible divergences in the SP-proteome among ejaculate fractions/portions, particularly in the light of the ongoing discussions as to whether to use only the SRF or the entire ejaculate for both AI and sperm technologies, such as cryopreservation and sex-sorting [2]. Noticeable all expressed SP-proteins were present in each of the three ejaculate portions, which would indicate that the possible influence of SP-proteins on boar sperm performance, both AIfertility and aid overcome sperm technologies, would be more linked to quantitative rather than qualitative differences.…”

Section: Discussionmentioning

confidence: 99%

“…Nowadays, commercial semen AI-doses are used as liquid state, but increasing research is done for the practical incorporation of frozen-thawed semen and even sex-sorted spermatozoa into commercial swine AI-programs [2]. Boar ejaculates are selected if most relevant sperm attributes, such as motility, morphology or membrane sperm integrity, are within acceptable limits when evaluated using innovative technologies such as computer assisted analysis and flow-cytometry based procedures [3].…”

Section: Introductionmentioning

confidence: 99%

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Characterization of the porcine seminal plasma proteome comparing ejaculate portions

Pérez-Patiño

Barranco

Parrilla

et al. 2016

Journal of Proteomics

102

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Full identification of SP-proteins remains challenging, particularly in some livestock species such as porcine. This experimental study aims to provide an extensive proteomic analysis of boar SP and to generate a public accessible database of boar SP-proteome. A SP-pool from 33 entire ejaculates from 11 boars (3 ejaculates per boar) was analyzed to characterize the boar SP-proteome. Moreover, 20 ejaculates collected in fractions (P1: first 10 mL of sperm rich ejaculate fraction (SRF), P2: rest of SRF and P3: post-SRF) from 5 boars (4 ejaculates per boar) were analyzed to evaluate differentially expressed SP-proteins among portions. SP-samples were subjected to a combination of SEC, 1-D SDS PAGE and NanoLC-ESI-MS/MS followed by functional bioinformatics analysis.The identified proteins were quantified from normalized LFQ intensity data. A total of 33,557 spectra corresponding to 8,189 peptides and 536 SP-proteins were identified with ≥ 95% Confidence (Unused Score > 1.3) and a false discovery rate (FDR) ≤ 1%. Of the 536 SP-proteins, 409 were identified in Sus Scrofa taxonomy and 374 of them were Biological Significance: This proteomic study provides the major characterization of the boar SP-proteome with more than 250 proteins first reported. The boar SP-proteome is described so that a spectral library can be built for relative 'label free' protein quantitation with SWATH approach. This proteomic profiling allows the creation of a publicly accessible database of the boar SP-proteome, as a first step for further understanding the role of SP-proteins in reproductive outcomes as well as for identification of biomarkers for sperm quality and fertility.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Characterization of the porcine seminal plasma proteome comparing ejaculate portions

Pérez-Patiño

Barranco

Parrilla

et al. 2016

Journal of Proteomics

102

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“…Uterine activity plays a key role in natural and assisted reproduction. In pig production units, the use of various reproductive technologies has become routine in an effort to increase the efficiency of production (Kirkwood, Aherne, Monaghan, & Misutka, ; Knox, ; Roca et al., ). The hormonal induction of oestrus and ovulation effectively manages the timing of behavioural oestrus and ovulation, decreasing AI numbers per oestrus (Kirkwood & Kauffold, ; Tummaruk, Roongsitthichai, & De Rensis, ).…”

Section: Discussionmentioning

confidence: 99%

Computational multivariate modelling of electrical activity of the porcine uterus during spontaneous and hormone‐induced oestrus

Domino

Pawliński

et al. 2019

Experimental Physiology

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New Findings What is the central question of this study?Does oestrous cycle synchronization influence myoelectrical activity of porcine myometrium? What is the main finding and its importance?Exogenous hormones used to synchronize oestrus in pigs altered myoelectrical activity, which was effectively modelled. Higher‐order multivariate statistic modelling provided evidence of similar activity in both types of oestrus, but a larger order of EMG signals during induced oestrus. Higher‐order statistical analysis of the probabilistic model suggests the beginning of the early follicular phase and the mid‐luteal phase to be most important in evaluation of the natural patterns of myoelectrical activity. Higher‐order multivariate cumulants are more informative than classical statistics in characterization of myoelectrical activity changes in porcine myometrium. Abstract In pig production units, control of the oestrous cycle and synchronization of ovulation have become routine herd management procedures. During the oestrous cycle, in both induced and spontaneous conditions, the ovaries and the uterus undergo hormone‐dominated physiological changes, which are consistent with the hypothesis that there is a functional role of uterine contractions in promoting fertilization. We have used electromyography to determine whether the use of exogenous hormones, such as equine chorionic gonadotrophin and human chorionic gonadotrophin, which have the potential to control the timing of ovulation in female pigs, changes the multivariate relationships between parameters of electrical bursts and modulates the patterns of myoelectrical activity. We used the mathematical approach of higher‐order multivariate cumulants in complex modelling of the myometrial electrical activity. The experiment was conducted on 12 mature Polish Landrace sows, and uterine activity was recorded during both spontaneous and induced oestrous cycles. The burst parameters were determined using six features in the time domain and, after Fast Fourier transformation, in the frequency domain. Evaluation of myoelectrical activity patterns was conducted based on classical univariate statistical methods and multivariate probabilistic modelling. The classical statistical approach indicated weaker myoelectrical activity after hormonal stimulation, whereas the higher‐order multivariate statistical model showed evidence of similar status of activity and a larger order of signals during induced oestrus. Routine oestrous cycle synchronization affects the multivariate probabilistic model of myometrial electrical activity.

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“…Uzyskiwane wskaźniki płodno-ści są podobne do skuteczności krycia. Metoda ta nie jest w pełni efektywna, ponieważ przechowywanym nasieniem płynnym pochodzącym od jednego knura można unasiennić 2000 macior/loch rocznie (56). Korzystanie z nasienia płynnego ogranicza handel międzynarodowy i spowalnia postęp genetyczny.…”

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“…Obecne badania próbują ten scenariusz zmienić. Szczególną uwagę przywiązuje się do badań mają-cych na celu zmniejszenie liczby plemników w dawce inseminacyjnej, ułatwiając praktyczne wykorzystanie seksowanego nasienia mrożonego u świń w warunkach komercyjnych (54)(55)(56).…”

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Sex-sorted sperm in farm animals: scale of use, the effectiveness of insemination, risk factors

Jaśkowski

Woźna

Gehrke

2017

Medycyna Weterynaryjna

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The aim of the study was to present the scale of use, risk factors and possibilities, which sorter semen gives in biotechnics used in reproduction of cattle. Modern sorters allow for the evaluation of 6 million X and Y spermatozoa per hour. Sex-sorted semen, which is commercially used, contains 2.1 x 106 of spermatozoa. It is used mostly in AI of milk heifers, mainly in large cattle herds. Sorted semen containing Y spermatozoa is sold less often in the world than the one with X spermatozoa. The percentage of the desired sex of the young is higher than 90. The pregnancy rate after application of sorted semen is about 20–25% lower than after insemination of non-sorted semen and depends on a number of factors. The main factors are: breed of female, service number, the herd of origin, the depth of semen deposition, the bull producing semen, ambient temperature and technical parameters during sperm sorting. A number of methods have been developed to improve conception rate, including timed artificial insemination (TAI) and synchronization of heat and ovulation. Results of donor inseminations with the use of sorter semen are presented, with the lower percentage of embryos suitable for the transfer and embryos of the highest quality highlighted. Previous studies do not indicate a reduction of the conception rate after the transfer of embryos obtained in vitro and in vivo after fertilization using sorted semen. It remains difficult to justify a significant increase in the frequency of stillbirths of bulls after using sorted sperm. Similarly, 16% of stillbirths of bulls were observed after embryo transfer, when donors were inseminated with sorter semen. The percentage of stillbirths of bulls after embryo transfer with the use of conventional semen is 9%. The sorted semen is not often used for inseminations in pigs, sheep and goats.

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Will AI in pigs become more efficient?

Cited by 66 publications

References 50 publications

Characterization of the porcine seminal plasma proteome comparing ejaculate portions

Characterization of the porcine seminal plasma proteome comparing ejaculate portions

Computational multivariate modelling of electrical activity of the porcine uterus during spontaneous and hormone‐induced oestrus

Sex-sorted sperm in farm animals: scale of use, the effectiveness of insemination, risk factors

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