Duplications in 19p13.3 are associated with male infertility

Singh, Vertika; Bala, Renu; Chakraborty, Arijit; Rajender, Singh; Trivedi, Sameer; Singh, Kiran

doi:10.1007/s10815-019-01547-1

Cited by 22 publications

(15 citation statements)

References 38 publications

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“…This suggests that this region located on chromosome 12 and the ITPR1 gene may be important for chicken egg number traits. GAMT located on GGA28 has been shown to be associated with the reproductive system and development [ 32 ]. CAMK4 located on chromosome Z is involved in the signaling pathway of OXT and may play a role in the development of follicles and ovulation [ 50 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of candidate genomic regions for chicken egg number traits based on genome-wide association study

et al. 2021

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Background Since the domestication of chicken, various breeds have been developed for food production, entertainment, and so on. Compared to indigenous chicken breeds which generally do not show elite production performance, commercial breeds or lines are selected intensely for meat or egg production. In the present study, in order to understand the molecular mechanisms underlying the dramatic differences of egg number between commercial egg-type chickens and indigenous chickens, we performed a genome-wide association study (GWAS) in a mixed linear model. Results We obtained 148 single nucleotide polymorphisms (SNPs) associated with egg number traits (57 significantly, 91 suggestively). Among them, 4 SNPs overlapped with previously reported quantitative trait loci (QTL), including 2 for egg production and 2 for reproductive traits. Furthermore, we identified 32 candidate genes based on the function of the screened genes. These genes were found to be mainly involved in regulating hormones, playing a role in the formation, growth, and development of follicles, and in the development of the reproductive system. Some genes such as NELL2 (neural EGFL like 2), KITLG (KIT ligand), GHRHR (Growth hormone releasing hormone receptor), NCOA1 (Nuclear receptor coactivator 1), ITPR1 (inositol 1, 4, 5-trisphosphate receptor type 1), GAMT (guanidinoacetate N-methyltransferase), and CAMK4 (calcium/calmodulin-dependent protein kinase IV) deserve our attention and further study since they have been reported to be closely related to egg production, egg number and reproductive traits. In addition, the most significant genomic region obtained in this study was located at 48.61–48.84 Mb on GGA5. In this region, we have repeatedly identified four genes, in which YY1 (YY1 transcription factor) and WDR25 (WD repeat domain 25) have been shown to be related to oocytes and reproductive tissues, respectively, which implies that this region may be a candidate region underlying egg number traits. Conclusion Our study utilized the genomic information from various chicken breeds or populations differed in the average annual egg number to understand the molecular genetic mechanisms involved in egg number traits. We identified a series of SNPs, candidate genes, or genomic regions that associated with egg number, which could help us in developing the egg production trait in chickens.

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Section: Discussionmentioning

confidence: 99%

Identification of candidate genomic regions for chicken egg number traits based on genome-wide association study

et al. 2021

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“…For example, deletions at 22q11.2 in idiopathic PD have been identified using an analytical method very similar to ours (the same datasets from UK Wellcome Trust Case Control Consortium 2 and the same analysis algorithms) . Recently, duplications in 19p13.3, including MIDN and other adjacent genes, were demonstrated to be associated with male infertility according to array‐based analysis . However, because genome‐wide copy number variation (CNV) detection power varies depending on platforms and analysis software, we recognize the necessity of multiple analysis algorithms and independent experimental validation for array‐based CNV detection studies.…”

mentioning

confidence: 64%

Reply to: MIDN locus structural variants and Parkinson’s disease risk

Obara

Sato

Nakayama³

et al. 2020

Ann Clin Transl Neurol

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Dear Editor,We thank Billingsley et al. for their interest in our study that showed a genetic association of MIDN deletions with Parkinson's disease (PD) in a British population. 1 In their letter to the editor, they noted that they could not identify any PD-associated deletions within 100 kb of MIDN in 3868 individuals analyzed by wholegenome sequencing (WGS) and raised issues regarding using SNP genotyping to identify structural variants. 2 We respect their analyzed data. However, as we obtained consistent results in British and Japanese cohort studies, our results may be reproduced in other cohorts if analyzed by array-based technology. In fact, a variety of deletions or multiplications within the MIDN locus have been identified in a general population and shown in public databases analyzed mainly by microarrays (Database of Genomic Variants; http://dgv.tcag.ca/dgv/app/ home or UCSC Genome Browser; https://genome.ucsc.ed u) 3,4 ( Fig. S1). Additionally, we examined the physiological functions of MIDN in neuronal cells using genome editing and RNA interference methodologies and demonstrated that MIDN is responsible for neurite outgrowth and expression of Parkin E3 ubiquitin ligase, which is associated with PD phenotypes. 5 High-resolution array-based analysis is widely used in basic research and clinical practice. For example, deletions at 22q11.2 in idiopathic PD have been identified using an analytical method very similar to ours (the same datasets from UK Wellcome Trust Case Control Consortium 2 and the same analysis algorithms). 6 Recently, duplications in 19p13.3, including MIDN and other adjacent genes, were demonstrated to be associated with male infertility according to array-based analysis. 7 However, because genome-wide copy number variation (CNV) detection power varies depending on platforms and analysis software, 8,9 we recognize the necessity of multiple analysis algorithms and independent experimental validation for array-based CNV detection studies. As in the case of array-based analysis, each different sequencing-based method (algorithms, experimental methods) has different strengths and weaknesses for detection, depending on the variant type or properties, and unique and common CNVs are often discovered using various approaches. 9 Furthermore, more than 90% of the lengths of discovered variants were less than 1 Kbp in sequence-based analysis, and the median length of deletions detected by sequencing was 742 bp, whereas that by SNP microarray was 50,265 bp. 9 In our analysis of the PD case group, the so-called CNV length was 42.6 Kbp (mean)/12.1 Kbp (median) in a British population and 169 Kbp (mean)/103 Kbp (median) in a Japanese population. Such large CNVs spanning the MIDN locus have been identified, suggesting that these 604 deletion or multiplication sizes are relatively insensitive range to identify efficiently by WGS-based analysis. 9 Long-read sequencing is assumed to be more preferable for detection of segmental duplications, gene loss, and fusion events in this case rather than short-r...

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“…Using Ensembl to annotate related SNPs, we found a total of 68 genes around signi cant peaks, and identi ed 32 candidate genes associated with egg production according to their functions (Table 3). Some genes such as NELL2, KITLG, GHRHR, NCOA1, ITPR1, GAMT, and CAMK4, which have been proved to be related to egg production, litter size, or reproductive traits, are worth a deeper exploration [19][20][21][22][23][24][25][26][27][28][29][30][31][32].…”

Section: Genome Wide Association Studymentioning

confidence: 99%

“…This suggests that this region located on chromosome 12 and the ITPR1 gene may be important for chicken egg production traits. GAMT (guanidinoacetate N-methyltransferase) located on GGA28 has been shown to be associated with the reproductive system and development [31]. CAMK4 (calcium/calmodulin-dependent protein kinase IV) located on chromosome Z is involved in the signaling pathway of OXT and may play a role in the development of follicles and ovulation [49].…”

Section: Candidate Genesmentioning

confidence: 99%

Identification of Candidate Genomic Regions for Chicken Egg Production Traits Based on Genome Wide Association Study

Zhao

Nie

Zhang

et al. 2021

Preprint

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Background: Since the domestication of chicken, various chicken breeds have been developed for food production, entertainment, and so on. Compared to indigenous chicken breeds which generally do not show elite production performance, commercial breeds or lines are selected intensely for meat or egg production. In the present study, in order to understand the molecular mechanisms underlying the dramatic egg yielding differences between commercial egg-type chickens and indigenous chickens, we performed a genome-wide association study (GWAS) in a mixed linear model. Results: We obtained 148 single nucleotide polymorphisms (SNPs) associated with egg production traits or reproductive traits (57 significantly, 91 suggestively). Among them, 18 SNPs overlapped with previously reported quantitative trait loci (QTL), including 13 for egg production and 5 for reproductive traits. Three SNPs were significantly associated with multiple egg production traits, such as egg number, age at first egg, and egg production rate in chickens. Furthermore, we identified 32 candidate genes based on the function of the screened genes. These genes were found to be mainly involved in regulating hormones, playing a role in the formation, growth, and development of follicles, and in the development of the reproductive system. Some genes such as NELL2, KITLG, GHRHR, NCOA1, ITPR1, GAMT, and CAMK4 deserve our attention and further study since they have been reported to be closely related to reproductive traits. In addition, the most significant genomic region obtained in this study was located at 48.61-48.84Mb on GGA5. In this region, we have repeatedly annotated four genes, in which YY1 and WDR25 have been shown to be related to oocytes and reproductive tissues, respectively, which implies that this region may be a candidate region underlying egg production traits. Conclusion: Our study utilized the genomic information from various chicken breeds or populations differed in egg production to understand the molecular genetic mechanisms involved in reproduction traits. We identified a series of SNPs, candidate genes, or genomic regions that associated with reproductive traits, which could help us in developing egg production in chickens.

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Duplications in 19p13.3 are associated with male infertility

Cited by 22 publications

References 38 publications

Identification of candidate genomic regions for chicken egg number traits based on genome-wide association study

Identification of candidate genomic regions for chicken egg number traits based on genome-wide association study

Reply to: MIDN locus structural variants and Parkinson’s disease risk

Identification of Candidate Genomic Regions for Chicken Egg Production Traits Based on Genome Wide Association Study

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