scholarly journals Litter Size of Sheep (Ovis aries): Inbreeding Depression and Homozygous Regions

Genes ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 109
Author(s):  
Lin Tao ◽  
Xiaoyun He ◽  
Xiangyu Wang ◽  
Ran Di ◽  
Mingxing Chu
Keyword(s):  
Litter Size ◽  
Inbreeding Depression ◽  
Embryo Implantation ◽  
Ovis Aries ◽  
Runs Of Homozygosity ◽  
Nucleotide Polymorphism ◽  
Genetic Management ◽  
Single Nucleotide ◽  
Important Trait ◽  
Hu Sheep

Ovine litter size (LS) is an important trait showing variability within breeds. It remains largely unknown whether inbreeding depression on LS exists based on genomic homozygous regions, and whether the homozygous regions resulted from inbreeding are significantly associated with LS in sheep. We here reanalyze a set of single nucleotide polymorphism (SNP) chip of six breeds to characterize the patterns of runs of homozygosity (ROH), to evaluate inbreeding levels and inbreeding depressions on LS, and to identify candidate homozygous regions responsible for LS. Consequently, unique ROH patterns were observed among six sheep populations. Inbreeding depression on LS was only found in Hu sheep, where a significant reduction of 0.016, 0.02, and 0.02 per 1% elevated inbreeding FROH4–8, FROH>8 and the total inbreeding measure was observed, respectively. Nine significantly homozygous regions were found for LS in Hu sheep, where some promising genes for LS possibly via regulation of the development of oocytes (NGF, AKT1, and SYCP1), fertilization (SPAG17, MORC1, TDRD9, ZFYVE21, ADGRB3, and CKB), embryo implantation (PPP1R13B, INF2, and VANGL1) and development (DPPA2, DPPA4, CDCA4, CSDE1, and ADSSL1), and reproductive health (NRG3, BAG5, CKB, and XRCC3) were identified. These results from the present study would provide insights into the genetic management and complementary understandings of LS in sheep.

Effects of prolactin receptor genotype on the litter size of Mangalica

2011 ◽  
Vol 59 (2) ◽  
pp. 269-277 ◽  
Author(s):  
Károly Tempfli ◽  
Gergely Farkas ◽  
Zsolt Simon ◽  
Ágnes Bali Papp
Keyword(s):  
Litter Size ◽  
Fragment Length Polymorphism ◽  
Prolactin Receptor ◽  
Hair Follicles ◽  
Nucleotide Polymorphism ◽  
Allelic Discrimination ◽  
Single Nucleotide ◽  
Breed Group ◽  
Pcr Rflp ◽  
Polymerase Chain

The aim of this study was to detect different alleles of the prolactin receptor (PRLR) gene and to examine their effects on the litter size of the indigenous Hungarian pig, the Mangalica. G1789A single nucleotide polymorphism (SNP) was investigated as a candidate for litter size. Samples from 80 purebred Mangalica sows and data of their 335 litters were provided by Olmos & Tóth Ltd. Hair follicles were used to isolate the required DNA. Allelic discrimination was performed by means of the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method using the AluI restriction enzyme and agarose gel electrophoresis. In the population examined, the A allele was found to be preferable in the Mangalica breed group. The most advantageous AA genotype was the least prevalent (8.75%), while the frequencies of AB and BB were 40% and 51.25%, respectively. Remarkably, the average number of piglets born alive per litter was 1.11 ± 0.39 higher in sows with AA as compared to those with BB genotype. By raising the frequency of the AA genotype, the litter size is likely to increase. However, the effect of PRLR genotypes can differ among pig breeds and even lines. Further studies may be required to observe and estimate possible pleiotropic effects of this polymorphism on other traits.

scholarly journals The expression and mutation of <i>BMPR1B</i> and its association with litter size in small-tail Han sheep (<i>Ovis aries</i>)

2021 ◽  
Vol 64 (1) ◽  
pp. 211-221
Author(s):  
Yu-Liang Wen ◽  
Xiao-Fei Guo ◽  
Lin Ma ◽  
Xiao-Sheng Zhang ◽  
Jin-Long Zhang ◽  
...  
Keyword(s):  
Litter Size ◽  
Quantitative Polymerase Chain Reaction ◽  
Follicular Development ◽  
Follicular Phase ◽  
Ovis Aries ◽  
Negative Effects ◽  
Single Nucleotide ◽  
Ovarian Granulosa Cell ◽  
Polymerase Chain ◽  
Genotype And Allele Frequencies

Abstract. Previous studies have shown that BMPR1B promotes follicular development and ovarian granulosa cell proliferation, thereby affecting ovulation in mammals. In this study, the expression and polymorphism of the BMPR1B gene associated with litter size in small-tail Han (STH) sheep were determined. The expression of BMPR1B was detected in 14 tissues of STH sheep during the follicular phase as well as in the hypothalamic–pituitary–gonadal (HPG) axis of monotocous and polytocous STH sheep during the follicular and luteal phases using quantitative polymerase chain reaction (qPCR). Sequenom MassARRAY® single nucleotide polymorphism (SNP) technology was also used to detect the polymorphism of SNPs in seven sheep breeds. Here, BMPR1B was highly expressed in hypothalamus, ovary, uterus, and oviduct tissue during the follicular phase, and BMPR1B was expressed significantly more in the hypothalamus of polytocous ewes than in monotocous ewes during both the follicular and luteal phases (P<0.05). For genotyping, we found that genotype and allele frequencies of three loci of the BMPR1B gene were extremely significantly different (P<0.01) between the monotocous and polytocous groups. Association analysis results showed that the g.29380965A>G locus had significant negative effects on the litter size of STH sheep, and the combination of g.29380965A>G and FecB (Fec – fecundity and B – Booroola; A746G) at the BMPR1B gene showed that the litter size of AG–GG, AA–GG, and GG–GG genotypes was significantly higher compared with other genotypes (P<0.05). This is the first study to find a new molecular marker affecting litter size and to systematically analyze the expression of BMPR1B in different fecundity and physiological periods of STH sheep.

scholarly journals Genome-wide selection signatures analysis of litter size in Dazu black goats using single-nucleotide polymorphism

3 Biotech ◽  
2019 ◽  
Vol 9 (9) ◽  
Author(s):  
Guang-Xin E ◽  
Xing-Hai Duan ◽  
Jia-Hua Zhang ◽  
Yong-Fu Huang ◽  
Yong-Ju Zhao ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Litter Size ◽  
Nucleotide Polymorphism ◽  
Selection Signatures ◽  
Single Nucleotide ◽  
Genome Wide

scholarly journals HandyCNV: Standardized Summary, Annotation, Comparison, and Visualization of CNV, CNVR and ROH

2021 ◽  
Author(s):  
Jinghang Zhou ◽  
Liyuan Liu ◽  
Thomas J Lopdell ◽  
Dorian Garrick ◽  
Yuangang Shi
Keyword(s):  
Copy Number Variants ◽  
R Package ◽  
Single Nucleotide Polymorphism Genotyping ◽  
Runs Of Homozygosity ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Livestock Species ◽  
One Stop ◽  
Analysis System ◽  
User Friendly

Here we present an R package for summarizing, annotating, converting, comparing and visualizing CNV (copy number variants) and ROH (runs of homozygosity) detected from SNP (single nucleotide polymorphism) genotyping data. This one-stop post-analysis system is standardized, comprehensive, reproducible, timesaving and user friendly for research in humans and most diploid livestock species.

scholarly journals PSVIII-41 Study of functional variants in homozygous islands in Nelore cattle

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 260-261
Author(s):  
Ana Fabricia Braga Magalhães ◽  
Maria Eugênia Zerlotti Mercadante ◽  
Danielly Beraldo dos Santos Silva ◽  
Gerardo Alves Fernandes Júnior ◽  
Ana Cristina Herrera Rios ◽  
...  
Keyword(s):  
Bovine Genome ◽  
Untranslated Regions ◽  
Causative Mutation ◽  
Runs Of Homozygosity ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Missense Variants ◽  
Functional Variants ◽  
Nellore Cattle ◽  
Nelore Cattle

Abstract The aim of this study was to identify functional variants within runs of homozygosity (ROH) islands present in the genome of Nellore cattle. Genotypic information of 3,492 animals and 755,319 single nucleotide polymorphism (SNPs), were used. ROH segments were detected using PLINK software. Only ROH segments shared by more than 50% of the population individuals were used for identifying homozygosity islands. The islands functional variants were classified using the VEP tool (predictor of variant effect) from ENSEMBL software. If the variant SIFT score was less than 0.05 it was considered to be “deleterious,” otherwise it was “tolerant.” We found five islands of homozygosity, located in chromosome 5, 7, 12, 21 and 26. Within the islands, a total of 1,181 variants were processed by VEP and all of them were recognized as existing variants. In total, 51 overlapped genes and 69 overlapped transcripts were found. Most of the variants were SNPs located in the intronic regions (55%), followed by intergenic spaces (14%), upstream (13%) and downstream gene variants (12%). The intronic variants can be related to specific QTLs, either because they are associated with regions affecting gene expression or in linkage disequilibrium with the causative mutation or even because they have an unknown function. Only a small portion of the variants is in synonymous regions (4%), splice regions (1%), untranslated regions (UTRs) (1%) or are missense variants (1%). We have found 11 missense variants, being three considered deleterious and eight tolerant. The deleterious variants were annotated: INHBC, SMIM33 e FBXW4 genes. The knowledge of functional variants distribution is important for improving annotation of the bovine genome. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001 and by São Paulo Research Foundation FAPESP (grants 2018/04313-7 and 2017/10630–2).

scholarly journals The value of genomic relationship matrices to estimate levels of inbreeding

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Beatriz Villanueva ◽  
Almudena Fernández ◽  
María Saura ◽  
Armando Caballero ◽  
Jesús Fernández ◽  
...  
Keyword(s):  
Inbreeding Depression ◽  
Inbreeding Coefficient ◽  
Relationship Matrix ◽  
Base Population ◽  
Genomic Relationship ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Inbreeding Coefficients ◽  
Locus Model ◽  
Genomic Inbreeding

Abstract Background Genomic relationship matrices are used to obtain genomic inbreeding coefficients. However, there are several methodologies to compute these matrices and there is still an unresolved debate on which one provides the best estimate of inbreeding. In this study, we investigated measures of inbreeding obtained from five genomic matrices, including the Nejati-Javaremi allelic relationship matrix (FNEJ), the Li and Horvitz matrix based on excess of homozygosity (FL&H), and the VanRaden (methods 1, FVR1, and 2, FVR2) and Yang (FYAN) genomic relationship matrices. We derived expectations for each inbreeding coefficient, assuming a single locus model, and used these expectations to explain the patterns of the coefficients that were computed from thousands of single nucleotide polymorphism genotypes in a population of Iberian pigs. Results Except for FNEJ, the evaluated measures of inbreeding do not match with the original definitions of inbreeding coefficient of Wright (correlation) or Malécot (probability). When inbreeding coefficients are interpreted as indicators of variability (heterozygosity) that was gained or lost relative to a base population, both FNEJ and FL&H led to sensible results but this was not the case for FVR1, FVR2 and FYAN. When variability has increased relative to the base, FVR1, FVR2 and FYAN can indicate that it decreased. In fact, based on FYAN, variability is not expected to increase. When variability has decreased, FVR1 and FVR2 can indicate that it has increased. Finally, these three coefficients can indicate that more variability than that present in the base population can be lost, which is also unreasonable. The patterns for these coefficients observed in the pig population were very different, following the derived expectations. As a consequence, the rate of inbreeding depression estimated based on these inbreeding coefficients differed not only in magnitude but also in sign. Conclusions Genomic inbreeding coefficients obtained from the diagonal elements of genomic matrices can lead to inconsistent results in terms of gain and loss of genetic variability and inbreeding depression estimates, and thus to misleading interpretations. Although these matrices have proven to be very efficient in increasing the accuracy of genomic predictions, they do not always provide a useful measure of inbreeding.

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