GENOME-WIDE ANALYSIS REVEALS THE MOLECULAR BASIS OF GENETIC VARIATION OF IMPORTANT ECONOMIC TRAITS IN CASHMERE GOATS ON QINGHAI-TIBET PLATEAU

D. Tian^1,2,3†, B. C. Zhou^4†, B. Han^1,2,3, X. Li^1,2,3, F. Tian^1,3, D. Qi⁵ and K. Zhao^1,3*

¹Key Laboratory of Adaptation and Evolution of Plateau Biota, Qinghai Provincial Key Laboratory of Animal Ecological Genomics, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, Qinghai, China

²University of Chinese Academy of Sciences, Beijing 100049, China

³Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China

⁴General Station of Animal Husbandry of Qinghai province, Xining 810001, Qinghai, China

⁵State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, 810016, Qinghai, China

^†Dehong Tian and Baicheng Zhou contributed equally to this work.

^*Corresponding author’s: zhaokai@nwipb.cas.cn;

ABSTRACT

Qaidam Cashmere goat is one of the few animals that can survive in the harsh environment of the Qinghai-Tibet Plateau and the adjacent alpine areas. It has a strong adaptability, thus shaping the genetic diversity of goat phenotype, morphology, physiology and other aspects. However, the molecular basis behind these genetic mechanisms remains unclear. Here, we conducted genome-wide studies of genetic variation in two different morphologies and geographical coordinates in indigenous Chinese goats to identify selective signaling in genomic regions. In the present study, we resequenced 10 high-altitude Chinese indigenous goat breeds and compared them with low-altitude goats.By combining θπ and Fst values, we identified 1277 overlapping selection regions that may contribute to the wool fiber traits, reproductive performance, and high-altitude adaptation of goats.Candidate genes enriched in selected regions are associated with the phenotypes in cashmere fiber traits (IGFBP3, TNF, ROCK1, WNT10B, KITLG), reproduction traits (CAMK2D, IL-18, ESR1, ANAPC13), body size (POMC), hypoxic adaptation (TH, ACER1, GNB1, HIF1A) and disease (IL-10). This study provided valuable genetic information for the basis of biological characteristics and genetic improvement of breeds.

INTRODUCTION

Goats were domesticated about 10,000 years ago (Zeder et al. 2000).The domestication of the goat was a step forward in the history of human civilization by gradually changing natural selection into the desired direction of human beings through artificial selection. Goats provided stable meat, milk, and fur materials for human beings. Domestic goats retain a unique selective signature and are an important local genetic gene pool (Yue et al. 2017). Cashmere is a kind of unmedullated hair fiber that extends from the secondary hair follicles of the skin. It is a high-grade raw material of pure natural animal fiber. However, the relevant selection signals behind the genetic and phenotypic polymorphism mechanisms exhibited by goats under the dual selection pressures of both artificial and natural environments remain unclear.

Genome-wide analysis can identify the selective signal of dominant alleles in hypoxic environments and adaptive genetic basis(Simonson et al. 2010; Scheinfeldt et al. 2012). Wang et al. (2016) identified genomic regions for phenotype and high-altitude adaptation by analyzing sequencing data from eight goat breeds. Benjelloun et al. (2015) identified some potential adaptive variants in 44 representative indigenous goat breeds. The identification of selected signals used the strategy of detecting regions of genetic variation in duck (Zhang et al. 2018), pandas (Zhao et al. 2013), pig (Anon 2012), sheep (Lv et al. 2014), dog (Liu et al. 2018), and goat (Dong et al. 2015). An extensive collection of candidate genes and possible directions for trait improvement can determine the effects of selection on the genome for use in breeding.

Qaidam cashmere goats are mainly distributed in the desert, semi-desert, and mountainous steppe areas of Qinghai-Tibet Plateau in Wulan County, Haixi Region. Goats living in these areas have adaptive solid biological characteristics and can adapt to various climatic conditions, including dry, cold, and harsh environments (Liu et al. 2015), reflecting phenotypic and genetic evolution of adaptability to local settings. However, the genetic footprint of genomic variation in Tibetan Plateau goats after domestication on multiple traits remains further studied.

To identify the specific genomic variation sets and superior germplasm resources of goats subjected to artificial and natural selection, we sequenced ten indigenous Chaidamu cashmere goats (altitude > 3,000 m). Our experimental data were analyzed with the genome sequences of nine Chengdu Brown goats downloaded from NCBI. The present study provides a basic understanding of the genetic variation corresponding to phenotypic changes. The results will provide theoretical basis for hypoxia adaptation and quality improvement of Chaidamu cashmere goats on Qinghai-Tibet Plateau.

MATERIALS AND METHODS

Ethic statement: This study was conducted in accordance with the Regulations on the Management of Laboratory Animals and was approved by the Animal Care and Use Committee of the Northwest Institute of Plateau Biology, Chinese Academy of Sciences (NWIPB2021311).

Animals and Genome sequencing: Ear tissue samples of ten Qaidam cashmere goats (CDMG) with specie-specific characteristics adapted to local environment were collected randomly in Haixi area of Qinghai Province (altitude > 3,000 m). The other sequencing data of 9 Chengdu Brown goats (CDBG) were downloaded from the National Center for Biotechnology Information (altitude < 1,000 m). A library with an insertion size of 500 bp was constructed after total genomic DNA was extracted (Illumina Inc., San Diego, CA, USA). Novaseq6000 (Illumina Inc., San Diego, CA, USA) NGS platform was used for sequencing (Guangzhou, China).

Variants identification and annotation: Clean reads were compared with the reference genome using the Burrows-Wheeler Aligner (BWA). Single Nucleotide Polymorphism (SNP) was detected using GATK, SNP sites were filtered, and the filtering condition was set as: MQ (RMS Mapping Quality) ≥25；QD (Variant Confidence/Quality by Depth) ≥ 2.SNPs were annotated by ANNOVAR software(Kai, Li, and Hakon 2010).BreakDancer (Max1.1.2.) was used to detect chromosome structural variations in the genome (Chen et al. 2009). Copy number variants (CNV) were classified by CNVnator (0.3.2) (Abyzov et al. 2011)

Phylogenetic and population structure analysis: Next, neighbor joining method in the PHYLIP software (version 3.69) were used to construct genetic relationships between breeds (Felsenstein 1989) and the reliability of the branches was verified (bootstrap, 1000 replications). GCTA program (Yang et al. 2011) was used for the principal component analysis. The admixture model-based software Admixture (Alexander, Novembre, and Lange 2009) K=1~10 was selected as the mixed model to estimate the population structure. Using the method of Loiselle (Loiselle et al. 1995) et al by the software of SPAGeDi (Hardy and Vekemans 2002) V1.5 calculated the kinship matrix.

Analysis of Selective Sweep Regions: A sliding window based cross approaches was used to calculate Nucleotide Diversity (Nei and Li 1979) (π) and Fst to identify genes in the selected region. The threshold was determined by top 5 % and the genes in the significant and selected regions were screened. R scripts outputs all graphics. The candidate genes can be further analyzed.

RESULTS AND DISCUSSION

Analysis of Genetic Variation: We've obtained 806.63 billion raw reads. Stringent quality filtering yielded 614.35 billion clean reads. Clean reads have a Mapping rate of over 98 % to the goat reference genome (https://www.ncbi.nlm.nih.gov/assembly/GCF_001704415.1) with a coverage of ~99.49 % (Supplementary Table S1). Compared with the reference goat genome, a total of 24.39 million variation data were generated.According to the sequencing data, most SNPs (62.59 %) were located in the intergenic region. The remaining SNPs were distributed upstream (0.55 %) and downstream (0.57 %) of open reading frames, in introns (34.51 %), and exons (0.63 %), respectively (Supplementary Table S2). We also observed 60,259 non-synonymous SNV and 84,818 synonymous SNV in the exon. We also observed that 60,259 non-synonymous SNPs and 84,818 synonymous SNPs were located within the exons, with a distinct non-synonymous/synonymous ratio of 0.71, similar to that in Mouflon sheep (Ji et al. 2016) (0.689)(Supplementary Table S2). Next, Loci with a missing rate of more than 50% were removed, Venn graph divided 28.43 million SNPs into three parts: CDMG and CDBG had 8.57 million and 1.46 million species-specific SNPs respectively, and shared 9.86 million SNPs (Fig.1). The number of SNPs in exons, introns and intergenic regions of CDBG were less than that of CDMG. Furthermore, CDMG observed higher genetic diversity (Supplementary Table S3). The observed abundance of variation was similar in other local breeds (Ai et al. 2015). Principal component analysis (PCA) explained the first principal component variation separation (10.71 %)(Fig.2b). The neighbor-joining tree further confirms the significant separation of the two groups. This genetic differentiation is consistent with the environmental characteristics and origin of the breeds. The grazing patterns have a substantial effect on the adaptation genetic changes of the plateau goats. In addition, although the goats' genomes are similar, they have diverged into two different branches, probably due to genetic variations that result from long-term adaptation to their respective environments (Fig.2a).

Structural variation analysis: Comprehensive and accurate detection of indel will become more critical for targeting genomic variation (Mullaney et al. 2010). Furthermore, Indel and SVs are important types of chromosomal structural variation and contribute significantly to candidate molecular markers (Kim et al. 2018).A total of 861,995 insertions and 1,114,290 deletions were detected. 1,129,583 InDels were observed to be shared, of which 388,539 and 741,044 were specific to CDBG and CDMG respectively.Most InDels were single nucleotide deletions ranging in length from 0 to 10 bp (Fig.3a). The detection of a large number of specific gene mutations, gene recombination, chromosome variation and so on emphasizes the importance of novel variants, and can better inform future husbandry and breeding practices to mitigate the potential for future loss of gene diversity.

A total of 31,483 structure variants were obtained. There were 4,941 insertions, 16,785 deletions, 292 inversions, 7,888 chromosomal translocations, and 1,577 tandem duplications. There were 1366 and 11915 SVs specific to CDBG and CDMG (Fig.3b), respectively, with no difference in length, and CDMG apparently retained more variation.This may have increased the breed's ability to adapt to extreme natural environments. The discovery of specific and overlapping variation of InDels is of great significance. This is because the breed specific variation preserves the inherent particularity, while the overlapping may reflect the amount of variation shared between the breeds (Stafuzza et al. 2018).

Genome-Wide selective sweep analysis: Whole-genome was scanned to detect regions with high degrees of fixation, which are indicative of selection signatures. The fixation index (Fst) values and πration were used to estimate pairwise genetic differentiation, the top 5 % of the 1277 overlapping selective regions (Supplementary Table S4and Fig.4b) were annotated as regions of variation containing 3184 candidate genes (Supplementary Table S5and Fig.4a) associated with genetic adaptation and goat traits. Combined with the analysis results of these methods, we can find that some existing mutations or new mutations can increase the adaptability of a species to a particular environment.

It is reasonable to assume that some changes in certain genes and biological signals alter the phenotype's adaptation to the environment.Gene ontology enrichment analysis was used to analyze the biological functions of candidate genes.The analysis identified 129 biological processes that significantly enriched candidate genes in the GO term, 24 molecular functions, and 22 cellular components with a 5 % FDR threshold (Supplementary Table S6). Overrepresented candidate genes were significantly enriched in any biological processes related to a neurological system process, cell surface receptor signaling pathway, signal transduction, multicellular organismal process, response to stimulus, and single-organism cellular process. The cellular components include the membrane, intrinsic component of membrane, and intermediate filament. The molecular functions were related to molecular transducer activity, signal transducer activity, and transmembrane receptor activity. These results indicate that the effect of GO terms reflects the plateau adaptation and phenotypic traits of Qaidam cashmere goats. Twelve pathways were enriched to be significantly enriched with a 5 % FDR threshold (Supplementary Table S7 and Fig.5a), which belonged to cellular processes, metabolism, organismal systems, environmental information processing four major categories (Fig 5b). Therefore, the traits associated with polymorphism of species variation may be the result of interactions between some underlying polygenes.It also highlights the complexity of adaptive mutants of important genetic information and their related biological regulatory mechanisms.

Candidates genesassociated with cashmere fiber traits: Based on the above enrichment analysis, candidate genes in selected regions were further screened. Selection footprints related to fiber traits were identified in the genomic regions by scanning selection signals, including IGFBP3 (ncbi_102174541), TNF (ncbi_100861232), ROCK1 (ncbi_102171022), WNT10B (ncbi_102169259), which are associated with cashmere traits. KITLG (ncbi_100860807) gene is associated with the phenotypic trait coat color. Insulin-like growth factor binding protein-3 (IGFBP3) expressed in the dermal papilla in the human hair, which plays a specific role in the local modulation of insulin-like growth factors action during the hair growth cycle (Batch, Mercuri, and Werther 1996). Later, IGFBP3 polymorphism was also found in goats(Lan et al. 2007) and sheep (Ali, El-Hanafy, and Salem 2009) successively, suggesting that genes may play an essential role in hair fiber growth.Liu found the B allele significantly improves their cashmere weight, fiber length, and hair length (Liu et al. 2012). Tumor necrosis factor (TNF) genes promoted the proliferation of skin fibroblasts and cashmere growth by activating NF-κB signaling (Jin et al. 2021; Jin et al. 2018). Rho-associated protein kinase1 (ROCK1) belongs to the ROCK signaling pathway, which was potentially involved with cashmere fiber traits (Zonaed Siddiki et al. 2020). Further research demonstrates that ROCK1 plays a vital role in the blockade of function, inhibits keratinocyte terminal differentiation, and increases cell proliferation (An et al. 2018).The high expression level of Wnt family member 10B (Wnt10b) (Li et al. 2013) promoted hair matrix cell proliferation and hair stem elongation (Liu et al. 2021). KIT ligand (KITLG)was related to mammalian melanogenesis and was involved in coat color-forming by down-regulating its expression (Wu et al. 2021). However, the development of cashmere hair follicles is affected by light, nutrition, grazing, and other external environmental factors. To a large extent, epigenetic regulation, so the mechanism of cashmere fiber occurrence needs further study.

Candidates genes associated with reproduction traits: Reproductive traits controlled by multiple genes are critical economic indexes in livestock breeding programs. Interestingly, oocyte meiosis pathways might be involved in regulating ovarian follicular maturation and ovulation. Calcium/calmodulin-dependent protein kinase type II delta (CAMK2D, ncbi_102175934) gene plays an essential role in the transferase activity and phylogeny of the bovine embryo development process (Adams et al. 2011).While simultaneously implanting the epithelium of the reproductive tract, Interleukin-18 (IL-18, ncbi_100861190) also maintains a level of immune protection in the uterus, cervix, and vagina against potential pathogens (Qi et al. 2012).Menck and Gloria all found that the dominance effect (d) (P < 0.05) of single-nucleotide polymorphisms in the estrogen receptors 1 (ESR1, ncbi_102189484) gene was associated with the litter size as a new genetic marker (Muñoz et al. 2007; Mencik et al. 2019). In addition, the anaphase-promoting complex subunit 13 (ANAPC13, ncbi_102170094) gene in this pathway is explicitly involved in oocyte maturation (Yin et al. 2017).

Candidate genes related body size: Small body size is a favorable phenotype to consume less energy, which may also be an essential adaptive mechanism for goats in high altitudes-environment (Yang et al. 2016). Compared with Boer goat adult male and female weight, Qaidam cashmere goat male and female weight was 60 kg and 40 kg lower, respectively. Pro-opiomelanocortin (POMC, ncbi_102182514) is thought to be a necessary prohormone that codes for many different peptides associated with economic traits, such as growth traits. Research has reported that POMC genes polymorphisms have potential effects on carcass traits and body weight (Zhang et al. 2009). POMC gene may be one of the candidate genes for linear longitudinal growth of animals.

Candidate genes related to the high-altitude adaptation: Cashmere goats face environmental challenges from low oxygen, low temperatures, and high UV radiation. Cashmere fiber and its small size help combat heat loss and energy expenditure. tyrosine hydroxylase (TH, ncbi_102179849) genes may be necessary for regulating the appropriate physiological response to hypoxia in the newborn period(Adams et al. 2001). alkaline ceramidase 1 (ACER1, ncbi_102179093) gene, as targeted by key miRNAs, is presumed to enhance energy metabolism due to the function of RNA, allowing for adaptation to hypoxic conditions(Zhang et al. 2021). The intensity of light increases with altitude,” guanine nucleotide-binding protein beta-1 (GNB1,ncbi_102187070) involved in light transduction pathways are affected by positive selection, possibly in response to greater light intensity (Chi et al. 2017).When animals are exposed to hypoxia, they trigger a hypoxia response through a hypoxia-inducible factor (HIF) protein, cyclin-dependent kinase inhibitor Hypoxia-Inducible Factor-1 α (HIF1A, ncbi_100861391)was involved in mediating the physiological responses to oxygen availability (Moraga and Figueroa 2018).

Candidate genes related todisease: The immunoregulatory cytokine interleukin-10 (IL-10, ncbi_100860746) is an important immunosuppressive cytokine, this may represent the evolution of an immune event that reactivates the IL-10 gene under physiological or pathological conditions (Im et al. 2004). Selective signals associated with immune responses are considered to be prime targets because they are essential in biological defense against microbial invasion. Some such examples might include interleukin 1A (IL-1A), IL-1B, IL-10, IL-9, IL-4, IL-13, and IL-18 (Schmitt, Klein, and Bopp 2014; Quach et al. 2016).Genetic signatures of the human immune response have been widely adapted to regional climates, and these adaptations may lead to disease susceptibility.(Souëf, Goldblatt, and Lynch 2000).In conclusion, it can be concluded that populations using these regulatory variants will have natural selection advantages that affect the consistent activation of immune-related genes.

Conclusion: To our knowledge, Genome-wide scanning revealed the genomic footprint of candidate genes involved in phenotypic traits and hypoxic adaptation. The candidate genes identified in the selected region were associated with the phenotypes in cashmere fiber traits, reproduction traits, body size, high-altitude adaptation, and disease, indicating the genetic basis of phenotypic evolution adapted to local climatic conditions. Furthermore, these results lay a foundation for further study on genetic diversity and genomic characterization of essential traits of Qaidam cashmere goats.

Acknowledgements: We greatly appreciated our collaborators for their assistance in sample collection.

Funding: This research was supported by the Strategic Priority Research Program of Chinese Academy of Sciences, Pan-Third Pole Environment Study for a Green Silk Road (Pan-TPE) (4-1-3-3 XDA2004010303). The Second Tibetan Plateau Scientific Expedition and Research Program (STEP), Grant No.2019 QZKK0501. The Joint Research Project of Three-River- Resource National Park funded by Chinese Academy of Sciences and Qinghai Provincial People’s Government (LHZX-2020-08). K.C.Wong Education Foundation supports Dr. Zhao. Dr. Tian was endorsed by the 1,000 Talent program of Qinghai Province.

Authors^’ contributions: DQ and KZ arrange experiments and implement projects. DT analyzed the data and wrote the paper. BZ and FT participated in the data analysis. BH and XL did preliminary work of the experiment and data collation and analysis. All authors reviewed and agreed to the final manuscript.

Competing interests: No competing interests.

Availability of data and materials: The original data measured in this study were stored in NCBI SRA with the accession number SRA SUB9339333 under Bio-project PRJNA723729.

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