Genome-wide Analysis of CNVs in Three Populations of Tibetan Sheep using Whole-genome Resequencing

Abstract

Background: Copy number variation (CNV), an important source of genomic structural variation, can disturb genetic structure, dosage, regulation and expression, and is associated with phenotypic diversity and adaptation to local environments in mammals. In the present study, 24 resequencing datasets were used to characterize CNVs in three ecotypic populations of Tibetan sheep and assess CNVs related to domestication and adaptations in the Qinghai-Tibetan Plateau.

Results: A total of 87,832 CNV events accounting for 0.3% of the sheep genome were detected in three Tibetan sheep populations. After merging the overlapping CNVs, 2777 CNV regions (CNVRs) were obtained, among which 1098 CNVRs were shared by the three populations. The average length of these CNVRs was more than 3 kb, and duplication events were more frequent than deletions. Functional analysis showed that the shared CNVRs were significantly enriched in 56 GO terms and 18 KEGG pathways that were mainly concerned with ABC transporters, olfactory transduction and oxygen transport. Moreover, 188 CNVRs overlapped with 97 quantitative trait loci (QTLs), such as growth and carcass QTLs, immunoglobulin QTLs, milk yield QTLs and fecal counts QTLs. PCDH15, APP and GRID2 overlapped with body weight QTLs. Furthermore, Vst analysis at each CNVR showed that RUNX1, LOC101104348, LOC105604082 and PAG11 were highly divergent between HTS and VTS, and RUNX1 and LOC101111988 were significantly differentiated between VTS and OTS. Meaningfully, the duplication of RUNX1 may facilitate the hypoxia adaptation of OTS and HTS in QTP, which deserves further research in detail.

Conclusions: In this study, we represented the genome-wide distribution characteristics of CNVs in Tibetan sheep and provided a valuable genetic variation resource, which will facilitate the elucidation of the genetic basis underlying the distinct phenotypic traits and local adaptation of Tibetan sheep.

Background

Copy number variations (CNVs) and single nucleotide polymorphisms (SNPs), as significant genetic variations, play important roles in physiological and pathological processes. Unlike SNPs, which refer to the substitution, deletion or insertion of just a single nucleotide for another, CNVs involve fragmental variation even larger than 1000 bp in size. Therefore, it has been confirmed that CNVs have the potential to markedly affect organismal phenotype.

In the past twenty years, a large number of CNVs have been revealed and identified by using array comparative genome hybridization (aCGH) chips and high-density SNP chips in domestic animals, such as cattle, sheep, goats, horses, dogs, chickens, turkeys and ducks. Meanwhile, numerous CNV-covered genes have been shown to be associated with coat color, growth, fertility and production [1, 2], immune response [3–7], olfactory transduction [8–11], molecular function [12, 13], lipid metabolism [4, 9, 14–16] and environmental adaptability [17]. Compared with aCGH and SNP chips, the sensitivity of which is mainly limited by the density of the probes, whole genome resequencing can be used to detect new and rare CNVs. Therefore, an increasing number of CNVs have been detected by using high-throughput sequencing. In terms of sheep, in addition to whole genome detection of new CNVs, the primary focus was on uncovering the CNVs associated with economic traits. Yuan et al. found that 1855 CNVRs were associated with 166 quantitative trait loci (QTLs), including milk QTLs, carcass QTLs, and health-related QTLs in fine-wool sheep [18]. CNVR overlapping genes, such as SHE, ORMDL1, TOP2B, PIGY, and BAG4, were reported to be correlated with body size in sheep [19–23]. The CNVs of BTG3, PTGS1 and PSPH were involved in fetal muscle development, prostaglandin (PG) synthesis, and bone color [24]. Meanwhile, the correlation between CNVR-harboring genes and growth traits or phenotypic traits was also attractive. The agouti signaling protein (ASIP) gene duplication has been linked to typical white coat color [25]. Distal-less homeobox 3 (DLX3) CNV is related to wool curling in Tan sheep [26].

Tibetan sheep (TS) is one of the three ancient coarse-wool sheep breeds in China and is predominantly distributed in the Qinghai-Tibetan Plateau (QTP). Natural adaptation and artificial selection shaped the TS with the characteristics of resistance to cold, rough feeding, and hypoxic adaptation. As one of the two master domestic animals, TS can be divided into three ecotype populations, namely, Highland-type Tibetan sheep (HTS), Valley-type Tibetan sheep (VTS) and Oura-type Tibetan sheep (OTS). HTS is famous for its carpet wool production, with an average staple length of up to 25 cm. The proportion of dry head wool in the OTS was relatively high but had remarkable meat performance. The appearance of VTS is similar to that of HTS but with a smaller body size and shorter staple length. Meanwhile, the VTS was mainly distributed in valley regions with relatively low altitudes (~2000 m), in contrast to the HTS and OTS (both distributed above 3200 m).

Nevertheless, there have been few reports on the analysis of CNVs in TS. Therefore, in the present study, we exploited a large number of CNVs in 24 individuals from the three TS populations using whole genome resequencing and identified CNVs associated with the molecular basis of phenotype differences, domestication and adaptation to QTPs.

Results

Discussion

To date, there are many reports regarding CNVs of sheep using aCGH, SNP array and genome resequencing. Due to the difference in CNV detection platforms, the quantity of detected CNVs varies widely in different studies. In terms of the CNVs captured by aCGH and SNP chips, the number usually ranges from dozens to hundreds, and the average length is approximately 100-300 kb [28–32]. Using whole genome resequencing, Cheng et al [33] reported that 4301 CNVRs were identified in three Chinese breeds. A total of 7228 CNVRs were obtained, including 861 duplications, 6345 deletions, and 22 both events in Chinese indigenous fine-wool sheep [18]. Similarly, there were differences in the amounts of CNVR, and the proportion accounted for chromosomes. In the present study, we obtained 2777 CNVRs, including 1965 duplications and 812 deletions. These CNVRs accounted for ∼0.3% of the sheep reference genome. This coverage ratio is comparable with previous reports [29, 33] but lower than the 10% reported by Salehian-Dehkordi et al. [34]. There is no rule about which (duplication or deletion) happened more frequently in previous studies. In addition to the detection platform, the reason for these variations may be the differences in calling algorithms and standards. Meanwhile, the breed and sample size used in the study were other considerable factors [35].

The GO enrichment analysis showed that the detected CNVRs harboring genes shared by the three populations were significantly enriched in ion transport, sensory perception system, gas transport and pigmentation. Among them, sensory perception was also significantly enriched in yaks [36, 37] and other sheep breeds [18, 29]. The three TS populations live in alpine grasslands where the weather conditions are much harsher. As yak, TS faced the same living conditions as the lack of herbage in the cold season. The well-developed sensory perception system was important to improve the yak and sheep’s ability to acquire food and avoid noxious weeds. The gas transport term was also enriched in TS, and efficient oxygen exchange may facilitate hypoxia adaptation. In the KEGG pathway analysis, it is noteworthy that the CNVR-harboring genes shared by the three populations were significantly enriched in nutrition metabolism, ABC transporters, disease defense and hematopoietic cell lineage. The enrichment of nutrient metabolism terms, including nitrogen metabolism, citrate cycle, and bile secretion, was important for the digestion of nutrients in TS, especially in the cold season. Similar results showing the enrichment of CNVR-harboring genes in ABC transporters were also reported in humans [38, 39], cattle [10, 40, 41] and goats [42]. In mammals, ABC transporters can carry a broad array of endogenous metabolites, such as amino acids, peptides, and sugars, across lipid membranes, which facilitate the absorption and utilization of these nutrients. Hypoxia can promote hematopoiesis. Here, CNVR-harboring genes were enriched in the hematopoietic cell lineage in Tibetan sheep, which may make it suitable for their adaptation to high altitudes with low oxygen. Overall, the number of enriched CNVR overlapping genes associated with forage consumption and oxygen transport may be helpful for their adaptation to the local environment.

Notably, the olfactory transduction pathway was significantly enriched specifically in OTSs. Enrichment of the olfactory transduction pathway has been reported in cattle [11, 16, 43, 44], yaks [45], sheep [18, 28, 46] and goats [42]. It has been revealed to influence food consumption [47] and as a factor to assess feed efficiency and performance in crossbred beef cattle [48] and residual feed intake in pigs [49]. Meanwhile, more CNVR havrboring genes were enriched in amino acid and VFA metabolism pathways in the OTS. OTS has a much better meat performance than HTS and VTS. More CNVR harboring genes enriched in the olfactory transduction pathway, together with protein and energy metabolism pathways, may explain the better production performance in OTS.

QTLs, which contain genetic variants affecting the economic traits of domestic animals, can be used to select candidate CNVR-harboring genes that affect phenotypes in sheep. After integrating CNVs into QTLs, we found 188 CNVRs overlapping with 97 sheep QTL regions in this study. Many CNVs harboring genes, such as PCDH15, APP and GRID2, are located in growth and carcass QTL regions. The PCDH15 gene was identified to be associated with the concentration of the neurotransmitter glutamate (Glu) in cattle [50]. APP is one of the well-known pathogeneses in Alzheimer's disease. Zheng et al. indicated that homozygous APP deficiency leads to a 15–20% reduction in body weight [51]. An et al. reported that adipocyte-specific and mitochondria-targeted APP-overexpressing mice display increased body mass [52]. GRID2 was also identified as being associated with body weight in rats [53].

Selective sweeping can reveal putative regions that undergo environmental and artificial selection during local adaptation and domestication. To screen the critical CNVR significantly divergent between different populations, the pairwise Vst value was estimated [18, 50, 54]. Here, the five CNVR horboring genes RUNX1, LOC101104348, LOC105604082, PAG11 and LOC101111988 showed significant pairwise differentiation among HTS, OTS and VTS. It is well known that RUNX1 plays a crucial role in hematopoiesis, leukemogenesis and neural development. Lin et al. reported that GWAS hit SNPs associated with colostrum albumin concentration were enriched in RUNX1 in Chinese Holsteins, and these mutations might initiate the hyperactivation of inflammatory and innate immunity [55]. The GWAS hit SNP within RUNX1 is associated with the mean corpuscular volume level in pigs [56]. Moreover, HIF-1α facilitates RUNX1 transcriptional activity under hypoxic conditions and triggers hematopoietic stem cell differentiation, which ultimately improves oxygen transport to peripheral tissues [57]. Chaka sheep were a cultivated breed mainly with Tibetan sheep as basic ewes and adapted to a low oxygen environment for a long time. Hence, we speculated that CNVR-harboring RUNX1 underwent strict selection pressure in Tibetan and Chaka sheep, possibly helpful for their adaptation to a low oxygen environment at high altitudes. PAG11 is a pregnancy-associated glycoprotein that is expressed in the trophoblast of the ruminant placenta and influences embryo growth and survival [58]. HTS should face a shortage of forage and cold environments in their late pregnancy stage, in contrast to VTS. We thought the divergence of CNVR-harboring PAG11 between HTS and VTS may be related to their different habitat conditions, especially in the pregnancy stage. Notably, the ASIP gene, duplication of CNVR-harboring LOC101111988, located upstream of ASIP, was divergent between VTS vs OTS (Vst = 0.489) and HTS vs OTS (Vst = 0.284). The ASIP gene has been widely studied in mammals for its effect on animal coat color. Individuals with normal or duplication alleles of the ASIP gene are generally white or gray coat color, but individuals with normal or single deletion alleles in ASIP almost entirely have solid-black coat color in sheep [59–61]. In our study, the duplication of the LOC101111988 gene in VTS and HTS might account for their mainly white coat color. Meanwhile, the deletion in LOC101111988 CNV might be the basis for the primary brown covering color, especially in the neck in OTS.

Conclusions

In this study, the whole genomic characteristics were described in three ecotypic populations of Tibetan sheep. A total of 87,802 CNV events and 2777 CNVRs covering 0.3% of the sheep genome were captured. A few CNVR-harbored genes, such as PCDH15, APP, RUNX1, PAG11, and ASIP, were uncovered and may be associated with body weight, environmental adaptation, fertility, and coat color. Above all, our results provide a valuable genome-wide variation resource in Tibetan sheep for the elucidation of the genetic basis underlying the distinct phenotypic traits and local adaptation of Tibetan sheep.

Materials And Methods

Animals and resequencing

Twenty-four blood samples of Tibetan sheep were collected from their core distribution region in this study, including 8 highland-type sheep (HTS, Qilian County), 8 valley-type sheep (VTS, Huangyuan County) and 8 outer-type sheep (OTS, Henan County). The samples were stored in EDTA antifreezing tubes at -20℃. Genomic DNA was extracted with a Qiagen DNA purification kit (Qiagen, Dusseldorf, DE), and then the DNA integrity and concentration were checked with 1% agarose gel electrophoresis and Qubit^® 3.0 Flurometer (Invitrogen, USA), respectively. A sequencing library was built with 0.2 μg genomic DNA from each sample using the NEB Next^® Ultra^TM DNA Library Prep Kit (NEB, USA) following the manufacturer’s recommendations. Briefly, genomic DNA samples were fragmented by sonication to a size of 350 bp, and then DNA fragments were endpolished, A-tailed, and ligated with the full-length adapter, followed by further PCR amplification. After PCR products were purified by the AMPure XP system (Beckman Coulter, Beverly, USA), DNA concentration was measured by a Qubit^® Flurometer (Invitrogen, USA). The DNA libraries were sequenced using an Illumina HiSeq X-Ten platform (Illumina, USA), and 150 bp paired-end reads were generated and stored in FASTQ format. Paired reads with more than 10% unidentified nucleotides in either read, with low-quality bases (Phred quality value <5) over 50%, and with more than 10 bp aligned to the adapter were removed by using Fastp (0.19.7) to obtain clean data.

CNV and CNVR detection and annotation

The following steps were required before CNV detection: (i) the clean reads of each sample were aligned against the reference genome of Ovis aries (Oar_v4.0, http://www.ncbi.nlm.nih.gov/genome/?term=sheep) using BWA (Burrows–Wheeler Aligner) [62] and (ii) alignment files were converted to BAM files using SAMtools software [63]. (iii) SAMtools was also used to remove potential PCR duplications. If multiple read pairs have identical external coordinates, only the pair with the highest mapping quality is retained. CNVs were detected using CNVcaller with default parameters (-w: 800 bp, -l: 0.2, -u: 0.7, -g: 0.5) [64]. The individual candidate CNV windows are defined using 2 criteria: (i) The normalized read depth (RD) must be significantly higher or lower than the normalized mean RD (deletions < 1–2 * STDEV; duplications > 1 + 2 * STDEV). (ii) Considering that the normalized RD of heterozygous deletions and duplications should be approximately 0.5 and 1.5, respectively, an empirical standard for the normalized RD (deletions < 0.65; duplications > 1.35) must also be achieved. Low-frequency windows with low sequencing coverage were removed, and windows with an allele frequency ≥0.05 or at least 3 homozygous duplicated/deleted individuals were selected for further validation. If Pearson's correlation index was significant at the P = 0.05 level by Student’s t test, these 2 adjacent non-overlapping windows were merged into 1 call. To avoid putative positive CNVRs, the population-level candidate CNVRs for the three populations and TS as a whole were analyzed. CNV region definition, the distance between the 2 initial calls is less than 20% of their combined length, and the Pearson's correlation index of the 2 CNVRs is significant at the P = 0.01 level. Functional annotation of CNVs was completed by ANNOVAR[65] and classified as intronic, exonic or intergenic.

Functional enrichment analysis of CNVR-harboring genes

CNVR-harboring genes were retrieved from the NCBI database by BioMart software (http://www.biomart.org/), and completely or partially (≥50%) overlapping genes were all reserved for later analysis. GO and KEGG functional enrichment analyses were performed according to Huang et al. [66]. The P value was calculated and subjected to FDR correction. The merged CNVRs were compared with QTLs in the animal QTL database (https://www.animalgenome.org/cgi-bin/QTLdb/OA/index), to further assess the CNVRs that were correlated with economic traits in three ecotypes of Tibetan sheep.

Sweep selective analysis of the CNVR

Three ecotypes of Tibetan sheep have formed their own special characters under positive selection throughout long-term domestication and adaptation in the plateau. Therefore, the Vst was calculated similar to population differentiation index F_ST using the equation: Vst = (V_total–[V_pop1×N_pop1+V_pop2×N _pop2]/N_total)/V_total, where V_total is the total variance, V_pop is the CN variance for each respective population, N_pop is the sample size for each respective population, and N_total is the total sample size. Subsequently, the CNVRs with the top five Vst values were selected as candidate CNVRs, and functional enrichment analysis of these regions was performed.

qPCR and high depth resequencing validation

Quantitative real-time PCR was employed to validate the accuracy of CNVs detected in our study. Ten CNVs were selected that were identified by CNVcaller. The primers were designed using Primer 5 software based on NCBI reference sequences, and the DGAT1 gene was chosen as a reference gene (all primers are shown in Additional file 11: Table S9. qPCR was performed using the TB Green PCR reagent kit (Takara Bio). Three replicates per sample and blank controls were required in the PCR. The results were analyzed using the 2^−ΔΔCt method, and the copy number of the targeted genes was calculated [38-40].

Declarations

Ethics Statement

All experimental protocols and procedures were carried out in accordance with institutional guidelines and were approved by the Animal Care and Ethics Committee of Northwest Institute of Plateau Biology, Chinese Academy of Sciences (NWIPB20160302). We obtained the permission from the owner of the sheep to take samples.

Consent for publication

Not applicable.

Availability of data and materials

The raw sequencing data of 24 sheep for the identification of CNVs in this study have been deposited in the Genome Sequence Archive in BIG Data Center (https://ngdc.cncb.ac.cn/), Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, under the accession number CRA005573.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was supported in part by The Second Tibetan Plateau Scientific Expedition and Research (STEP) program (Grant No. 2019QZKK0302), Key R & D and Transformation Project of Qinghai Province (2019-NK-173), and Basic Applied Study of Qinghai Province (2014-ZJ-710).

Authors' contributions

LH, SX, XZ and CZ initiated the study and designed the project. LH, HL, TX, NZ and XH collected the samples. LH, QL, and CZ performed the bioinformatics and experimental analysis. LH, QL and CZ summarized the results. LH and CZ wrote the manuscript. All authors read and approved the final manuscript.

Acknowledgements

Not applicable.

Authors details

¹ Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810008, China

² State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China

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Tables

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