RNA-Seq based genetic variant discovery provides new insights into controlling fat deposition in the tail of sheep

Abstract

Genetic basis of fat deposition in sheep tail have not been completely elucidated yet. Understanding the genetic mechanisms controlling fat-tail size can improve breeding strategies to modulate fat deposition. RnA sequencing has made it possible to discover genetic variants that may underlie various phenotypic differences. Hence, to identify genetic variants that are important for describing different fat-tail phenotypes in sheep, RNA sequencing was used for single nucleotide polymorphism (SNP) calling in two Iranian sheep breeds (Lori-Bakhtiari, fat-tailed; n = 4, vs Zel, thin-tailed; n = 4). Using a stringent pipeline, a total of 112,344 known SNPs were genotyped, of which 30,550 and 42,906 SNPs were shared by at least two Lori-Bakhtiari and Zel, respectively. Comparing these SNPs showed 2,774 (including 209 missense and 25 deleterious SNPs) and 10,470 (including 1,054 missense and 116 deleterious SNPs) breed-specific SNPs in Lori-Bakhtiari and Zel sheep, respectively. Potential breed-specific SNPs were detected by considering those located in QTL regions associated with fatness or reported as important candidates in previous similar studies. Of the breed-specific SNPs, 724 and 2,905 were located in the QTL regions. Functional enrichment analysis of the affected genes revealed several enriched gene ontologies and KeGG pathways related to fat metabolism. Based on the results, several affected genes were proposed to be strongly linked with fat deposition such as DGAT2,

Integrative analysis of Iso-Seq and RNA-seq data reveals transcriptome complexity and differentially expressed transcripts in sheep tail fat

“…Among these DETs, 21 DETs are differentially expressed lncRNAs, including 14 known lncRNAs and seven novel lncRNAs. The correlation between differentially expressed lncRNAs and DETs which transcribed from tail fat related candidate genes, including diacylglycerol O-acyltransferase 2 ( DGAT2 ) ( Bakhtiarizadeh & Alamouti, 2020 ), acetyl-CoA carboxylase alpha ( ACACA ) ( Bakhtiarizadeh & Alamouti, 2020 ; Bakhtiarizadeh & Salami, 2019 ), ATP citrate lyase ( ACLY ) ( Bakhtiarizadeh & Alamouti, 2020 ), fatty acid synthase ( FASN ) ( Bakhtiarizadeh & Alamouti, 2020 ), stearoyl-CoA desaturase ( SCD ) ( Kang et al, 2017a ), and acyl-CoA synthetase short chain family member 2 ( ACSS2 ) ( Guangli et al, 2020 ), was investigated. The result suggests that 20 out of 21 lncRNAs (except lncRNA ENSOART00020017088) were significantly correlated with at least one transcripts ( Fig.…”

“…Here, we highlight an example. ACACA is a candidate gene related to tail fat deposition ( Bakhtiarizadeh & Alamouti, 2020 ; Bakhtiarizadeh & Salami, 2019 ). In the current study, we found ten DETs (11.99.3, 11.689.28, 1.689.18, 11.265.3, ENSOART00020040904, 11.99.15, 11.689.14, 13.624.23, ENSOART00020006006, and 15.327.19) directly interactives with ENSOART00020037575 which was transcribed from ACACA ( Fig.…”

“…Many studies have attempted to identify the candidate gene associated with tail fat and understand the underlying mechanisms of fat deposition ( Ahbara et al, 2018 ; Amane et al, 2020 ; Baazaoui et al, 2021 ; Bakhtiarizadeh & Alamouti, 2020 ; Dong et al, 2020 ; Han et al, 2021 ; Li et al, 2018a ; Mastrangelo et al, 2019a ; Mastrangelo et al, 2019b ; Moioli, Pilla & Ciani, 2015 ; Moradi et al, 2012 ; Wei et al, 2015 ; Xu et al, 2017 ; Yuan et al, 2017 ; Zhang et al, 2019 ; Zhao et al, 2020 ; Zhi et al, 2018 ; Zhu et al, 2016 ). Previous studies suggested that microRNAs ( Miao et al, 2015a ; Pan et al, 2018 ), lncRNAs ( Bakhtiarizadeh & Salami, 2019 ; He et al, 2020 ) and mRNAs ( Bakhtiarizadeh et al, 2019 ; Kang et al, 2017a ; Miao et al, 2015b ; Wang et al, 2014 ) may regulate tail fat deposition in sheep.…”

Genetic differentiation of mainland-island sheep of Greece: Implications for identifying candidate genes for long-term local adaptation

“…With regard to STEAP4 , associated GO BP terms revealed its involvement in iron and copper import/transport that is critical to the maintenance of cellular homeostasis [ 54 ]. In humans, the gene has been linked to obesity [ 55 – 57 ], while in sheep, STEAP4 [ 58 ] and other members of the same gene family ( STEAP3) have been associated with excess fat accretion in tails [ 59 ]. The latter is a valuable energy reserve, playing a particular role in adaptation to harsh conditions (e.g.…”

Combining Multiple RNA-Seq Data Analysis Algorithms Using Machine Learning Improves Differential Isoform Expression Analysis

“…In addition, the continuously dropping sequencing costs and the emergence of new technologies and less costly protocols such as Quant-Seq 3 mRNA sequencing [3], have contributed to an ever-expanding landscape of data generation in order to characterize gene expression changes across tissues, organs, biological conditions and whole organisms. Furthermore, RNA-Seq has been deployed for a plethora of applications including but not limited to de novo transcriptome assembly [4], investigation of alternative splicing [5], discovery of fused transcripts [6], interrogation of allele-specific gene expression [7], genetic variant discovery [8] and detection of non-coding genes [9]. Therefore, it is evident that RNA-Seq has become the standard technique for experimental designs involving gene expression and often gene sequence alterations and has permanently replaced outdated techniques such as DNA microarrays [9].…”