Whole genome resequencing reveals Y-chromosome variants in yak: key insights into genetic diversity and population structure

doi:10.21203/rs.3.rs-4836920/v1

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Whole genome resequencing reveals Y-chromosome variants in yak: key insights into genetic diversity and population structure

https://doi.org/10.21203/rs.3.rs-4836920/v1

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Yak, an economically important bovine species considered as the lifeline of the Himalaya. Indeed, this gigantic bovine is neglected because of the scientific intervention for its conservation as well as research documentation for a long time. The Y chromosome is widely recognized for its role in male traits, characterized by paternal inheritance, high mutation rate, and minimal recombination rate or reverse mutation. So, we investigated the Y-chromosome-specific variants in four yak populations namely, Arunachali, Himachali, Ladakhi, and Jinchuan through whole genome resequencing, we identified nearly 274828, 243143, 283774, and 194 228 SNPs, respectively. The intergenic regions held the highest proportion of SNPs, with Jinchuan yaks showing fewer SNPs due to intense selective breeding for reproductive performance and product quality. The Ts/Tv ratios were 1.57, 1.67, 1.55, and 1.99 for Arunachali, Himachali, Ladakhi, and Jinchuan yaks, respectively. SnpEff annotation indicated that most SNPs were intergenic, followed by intronic regions. Key genes identified included ASMT, ASMTL, and SRY, with significant roles in melatonin biosynthesis and male sex determination. Interestingly, we performed Linkage disequilibrium (LD) pruning, which retained only about 20% of SNPs, underscored the complexity of genetic analyses and highlighted the importance of careful LD criteria selection to avoid losing loci under selection. This pioneering mapping of Y-chromosome SNPs in yaks provides essential insights into their genetic landscape and underscores the critical need for precise LD pruning parameters to accurately assess genetic diversity and population differentiation.

Yak

bovine

Ts/Tv

Linkage disequilibrium

genetic diversity and population differentiation

Whole-genome resequencing has emerged as a powerful tool for exploring genetic diversity and population structure across various species. Despite the advancements since the completion of the Human Genome Project, a significant portion of the Y chromosome nearly 50% remained uncharted until the recent successful decoding by the Telomere-to-Telomere (T2T) consortium. This knowledge gap stems primarily from the high density of repetitive sequences on the Y chromosome, which complicates sequencing efforts and often leads to its exclusion from comprehensive genomic studies (Hallast et al., 2023). The Y chromosome has been characterized by various evocative descriptors over the past decade, including "functional wasteland," "genetic desert," and "gene-poor chromosome," highlighting its unique and enigmatic nature (Quintana-Murci et al., 2001; Chang et al., 2013).

In phylogenetic research, particularly within bovine species, Y-chromosomal biallelic markers have proven invaluable (Li et al., 2014). In male yaks, the Y chromosome comprises 1.54% of the haploid genome and is sub-metacentric, similar to that in Bos taurus (Popescu et al., 1969). It is widely believed that yaks were domesticated in Central Asia from their wild ancestor, Bos mutus (Philips et al., 1946). Notably, the chromosomal patterns in yaks show closer resemblance to European cattle (Bos taurus) than to zebu cattle (Bos indicus), with extensive synteny up to 94% (Qiu et al., 2012). Cytogenetic studies reveal distinct morphological differences in the Y chromosomes of Chinese Yellow cattle (metacentric) and yaks (sub-metacentric) (Guo, 1983). Furthermore, research has identified limited TSPY copy numbers in yak bulls, while Chinese Yellow cattle and cattle exhibit higher amplification (Zhang et al., 2016). Differences in HSFY and ZNF280BY copy numbers between Chinese Yellow cattle and yaks further underscore the unique genomic organization in yak’s Y chromosome region (Zhang et al., 2016).Y chromosomes typically exhibit low genetic diversity within species (Hellborg and Ellegren, 2004; Brändli et al., 2005), but show considerable divergence at the interspecies level (Lawson and Hewitt, 2002; Hughes et al., 2005). This divergence is attributed to hitchhiking during positive selection on a few Y chromosomal genes (Hughes et al., 2005) or sexual selection pressures, potentially intensified by sperm competition (Roldan and Gomendio, 1999). The hemizygous state and possible genetic conflicts may also play a role (Hurst et al., 1996). Within species, selective sweeps, often facilitated by small male population sizes, can lead to the homogenization of Y chromosomal sequences (Ma et al., 2018). In recent years, molecular markers such as Y chromosome microsatellites (Y-STRs) and single nucleotide polymorphisms (Y-SNPs) have been utilized to study paternal population genetics in yak populations (Edwards et al., 2000; Han et al., 2000; Qi et al., 2002; Nguyen et al., 2005; Ma et al., 2015; Li et al., 2014).

The primary objective of this study was to identify the SNPs on the Y chromosomes of Indian yaks (Arunachali, Himachali, Ladakhi yak) and a Chinese yak (Jinchuan yak) using whole genome resequencing. This research represents the first exploration of Y chromosome markers in Indian yaks, which are critical for creating haplotypes and defining individual male lineages. Additionally, it aims to investigate the impact of various quality control measures, particularly linkage disequilibrium pruning, on the Y chromosome in bovine species. These findings will lay the groundwork for future studies on the population genetics of the Indian yak Y chromosome.

Sample collection and whole genome resequencing

The genomic DNA (gDNA) was collected from the DNA repository of the institute (National Bureau of Animal Genetic Resources, Karnal) and outsourced for whole genome resequencing. The initial quality assessment of gDNA was conducted to ensure high-quality samples for downstream analysis. Library preparation was performed using the NEBNext UltraII DNA library preparation kit for Illumina. The resequencing was performed on the Illumina Novaseq 6000 platform, utilizing the S4 flow cell configuration. Paired end library for each sample with a read length of 150 bp was generated. An average of around 10× coverage was achieved in the resequencing. For comparative evaluation and better understanding we included 8 samples of Chinese yak (Jinchuan yak) and these raw fastQ whole genome sequence files of these samples were retrieved from the European Nucleotide Archive (ENA). Sample accession Ids of the downloaded sequences are in Table S1 (Wang et al., 2020).

Sequence quality assessment, alignment, and variant calling

Initial quality assessment of raw reads was conducted using FastQC (v0.12.0) (Andrews, 2010) to evaluate sequence quality metrics. The quality trimming and adapter removal was done using Trimmomatic (v0.39) (Bolger et al., 2014), to ensure the generation of clean reads for subsequent analysis. Clean reads were aligned to the yak reference genome (BosGru3.1) (GenBank GCA_005887515.3) using Burrows Wheeler Aligner (BWA-MEM) (v 0.7.17-r1188) (Li and Durbin, 2009) to establish accurate genomic positions. To refine the data, sorted BAM files were marked for duplicates reads originated during library preparation using “MarkDuplicates” option in Picard (v1.114) (http://broadinstitute.github.io/picard) to identify and handle duplicate reads stemming from the library preparation process. The variant calling was done using ‘HaplotypeCaller’ in GATK pipeline (v4.3.0.0). Initially, genomic Variant Call Format (gVCF) files were generated for individual samples. These gVCF files were merged using the "CombineGVCFs" option, followed by joint genotyping utilizing "GenotypeGVCFs" to consolidate variant calls across all samples. Subsequently, a stringent variant filtering process was implemented using GATK's "VariantFiltration" tool. Variants were filtered based on multiple criteria including Quality by Depth (QD) < 2.0, Variant Confidence/Quality (QUAL) < 30.0, Strand Odds Ratio (SOR) > 3.0, FisherStrand (FS) > 60.0, Mapping Quality (MQ) < 40.0, MQRankSum < -12.5, and ReadPosRankSum < -8.0. To assess the statistics of VCF files, 'bcftools stats' (Danecek et al., 2021) was employed to generate comprehensive statistics reflecting the variants identified within the datasets. After filtration, the variants present on the Y chromosome are retained and remaining present on Autosome, X chromosome and mitochondria were removed. Analysis of any of the sex chromosome (X or Y) and autosome variants should be done separately as they may cause any potential biases arising from discrepancies in effective population size (Bahbahani et al., 2015; Sukhija et al., 2024; Kanaka et al., 2023)

Variant annotation of Y chromosome using SnpEff

Filtered SNPs and Indels were annotated using SnpEff version 5.2c (Cingolani et al., 2012) separately for each population. SnpEff is a tool for annotating genetic variations and predicting their functional impacts and we employed the SnpEff database LU_Bosgru_v3.0.99. SNPs were categorized based on impact severity (high, low, moderate, and modifier), functional classes (missense, nonsense, and silent mutations), as well as type and genomic region (downstream, exon, intergenic, intron, splice site acceptor, splice site donor, splice site region, transcript, upstream, UTR_3_prime, and UTR_5_prime) for each population separately.

Annotation of genes present on Y chromosome

Gene ontology (GO) analysis is a frequently used method for functional studies of large-scale genomic data. It facilitates the identification of significant categories related to functions of interest, thereby aiding in the understanding of regulatory mechanisms. Gene ontology and pathway analyses were then conducted with the DAVID (Database for Annotation, Visualization, and Integrated Discovery) tool (https://david.ncifcrf.gov). Genes identified on Y chromosome were imported into DAVID to determine significant genes and to identify certain important pathways.

LD pruning on Y chromosome variants

To assess the impact of Linkage disequilibrium on Y chromosome, we performed LD pruning using –indep-pairwise command in PLINK v1.9 with various r² values i.e., 0.2, 0.5 and 0.8 with fixed window size and step size of 50kb and 5kb respectively in different yak populations. Y chromosomes unlike autosomes have lower recombination rate except in the pseudoautosomal regions (PAR regions), resulting in formation of larger blocks of LDs. So, LD pruning was performed on the Y chromosome in order to assess the percentage of variants that were lost.

Variant calling

The present investigation was done to identify variants specifically on Y-chromosome, a total of 274828, 243143, 283774 and 194228 SNPs were identified in the Arunachali, Himachali, Ladakhi yak, and Jinchuan yak respectively after default GATK hard quality filtering protocol. Interesting trends were found when the distribution of these SNPs was examined across several genomic regions. The intergenic region included the greatest proportion of SNPs, with the intronic region coming in second in all of the studied population. Unlike Indian yaks, the SNPs in Jinchuan yak showed slightly increased proportion in the intergenic region (Table 1) SNPs were also found in the exonic area, however they were found there less frequently. This frequency distribution shows Y-chr specific SNPs in a variety of genomic locations, offering important information into the genomic landscape of the yak populations under study. The Ts/Tv (Transition and Transversion) ratio of the annotated SNPs were 1.57, 1.67, 1.55 and 1.99 for Arunachali, Himachali, Ladakhi and Jinchuan yak respectively. Nonetheless, the maximum SNPs were included under missense, followed by silent and nonsense, depending on the functional classes (Fig. 1).

Table 1

Region wise distribution of SNPs on Y-chromosome (Arunachali yak, Himachali yak, Ladakhi yak and Jinchuan yak)
Region	Number of SNPs
Region	Arunachali Yak	Himachali Yak	Ladakhi Yak	Jinchuan Yak
3_Prime_UTR_Variant	664	548	683	289
5_Prime_UTR_Premature_Start_Codon_Gain_Variant	38	37	51	27
5_Prime_UTR_Variant	312	324	307	242
Downstream_Gene_Variant	15,879	13,839	16,190	10,590
Initiator_Codon_Variant	5	1	1	1
Intergenic_Region	2,04,806	1,82,952	2,12,973	1,56,039
Intron_Variant	1,54,455	1,30,686	1,56,152	80,835
Missense_Variant	2,162	1,862	2,249	1,081
Non_Coding_Transcript_Exon_Variant	669	628	736	421
Splice_Acceptor_Variant	43	16	28	13
Splice_Donor_Variant	41	19	38	8
Splice_Region_Variant	343	273	325	177
Start_Lost	6	4	4	6
Stop_Gained	103	102	120	49
Stop_Lost	2	1	2	1
Synonymous_Variant	953	909	1,028	770
Upstream_Gene_Variant	15,572	14,341	15,848	10,178

Annotation of genes

Genes harboring the Y-chromosome SNPs were functionally annotated using DAVID and the significant pathways (p-value < 0.05) are presented in Table 2. A total of seven common biological pathways were observed in all the four yak populations (p < 0.005). Among all the biological pathways, mostly found genes are ASMT and ASMTL. SRY gene is present under UP_KW_MOLECULAR_FUNCTION category, under Repressor term, which is crucial for sex determination in all the species. Interestingly, the genes harboring those SNPs were found similar for all the four yak populations under study. The list of genes has been shown (Table S2).

Table 2

Biological pathways of various genes under DAVID with p < 0.05
Category	Term	Genes	Fold enrichment	P-Value
INTERPRO	ASMT_dimerisation	ASMT, ASMTL	439.4	0.0045
INTERPRO	O_MeTrfase_dom	ASMT, ASMTL	439.4	0.0045
INTERPRO	COMT-like	ASMT, ASMTL	439.4	0.0045
UP_KW_LIGAND	Chloride	ACE2, CLCN4, GLRA2	17.8	0.011
UP_KW_MOLECULAR_FUNCTION	Repressor	RBBP7, SCML2, SRY	9	0.04
UP_SEQ_FEATURE	DOMAIN:Acetylserotonin O-methyltransferase dimerisation	ASMT, ASMTL	428.4	0.0046
UP_SEQ_FEATURE	DOMAIN:O-methyltransferase	ASMT, ASMTL	428.4	0.0046

Effect of LD pruning on Y chromosome

Y chromosomes unlike autosomes have lower recombination rate resulting in formation of blocks of LDs and it is apparent by the loss of number of SNPs i.e., nearly 70–96 percent of the SNPs were removed after LD pruning across four yak populations (Fig. 2). In Arunachali, Himachali, Ladakhi and Jinchuan yak unpruned Y chromosome variants are 274828, 243143, 283774 and 194228 respectively. After LD pruning with varied r² value of 0.2, 0.5, 0.8 the variants left in Arunachali yak were 18537, 48237, 72748, respectively, in Himachali yak 15365, 42142, 64270 were retained respectively, in Ladakhi yak 19241, 53022, and 81005 respectively, whereas in Jinchuan yak 8045, 19345, and 33080 were remained. This number of variants across various yak populations on Y chromosomes using different parameters shows that around 6–28 percent of total SNPs are retained after LD pruning in Indian yaks while only 4–17 percent are retained in Chinese yak.

The mammalian Y chromosome is widely recognized for its role in male traits, characterized by paternal inheritance, high mutation rate, and minimal recombination rate or reverse mutation (Cortez et al., 2014). Over approximately 300 million years, it has evolved from ancestral autosomes to include genes vital for male reproduction and fertility (Lahn and Page 1999; Bachtrog 2013). Whole genome sequence has been characterized in cattle and, more recently, in yak (Kumar et al., 2024). However, research on the Y chromosome in yaks remains scarce, likely due to its repetitive sequences, palindromic regions, and elevated mutation rates, which pose challenges for sequencing. The Y chromosome plays a crucial role in studying paternal genetic variation, origins, and population structure in domestic animals. Earlier investigations into the yak Y chromosome have utilized PCR amplification to explore diversity (Luo et al., 2022; Li et al., 2014; Ma et al., 2018). Previous studies on the yak Y chromosome primarily utilized PCR-based methods to investigate genetic diversity (Luo et al., 2022; Li et al., 2014; Ma et al., 2018). Our study represents a pioneering effort to identify and analyze single nucleotide polymorphisms (SNPs) on the yak Y chromosome through whole genome resequencing. This is the first study to explore the impact of linkage disequilibrium (LD) pruning on Y chromosome variants in bovine species.

Variant calling

The SNP calling pipeline employed in this study closely followed the methodology described by Kumar et al. (2024), but with a notable difference: we used the LU_Bosgru_v3.0.99 reference database in SnpEff. This methodological choice resulted in the identification of a total of 274,828 SNPs in Arunachali yaks, 243,143 in Himachali yaks, 283,774 in Ladakhi yaks, and 194,228 in Jinchuan yaks. These numbers differ significantly from those reported by Kumar et al. (2024), indicating potential variations in SNP detection due to differences in reference databases and analytical pipelines. Despite the similar sample sizes across the studied yak populations, Jinchuan yaks exhibited a notably lower SNP count compared to other populations. This reduction can be attributed to the intense selection practices applied to Jinchuan yaks. Jinchuan yaks are selectively bred for superior reproductive performance, achieving up to 90% reproductive success, and for their enhanced milk and meat quality (Mipam et al., 2012). Such selective breeding pressures reduce genetic diversity within this population, resulting in fewer SNPs compared to other yak populations, which have experienced less intense selection (Lachance and Tishkoff, 2013). The observed lower SNP count in Jinchuan yaks underscores the impact of selective breeding on genetic diversity. While this selective pressure enhances desirable traits, it also leads to reduced genetic variation, which is reflected in the SNP profiles of these yaks.

Variant annotation of Y chromosome using SnpEff

The SNPs identified in this study were meticulously annotated to determine their genomic context and potential functional impacts. This process utilized SnpEff (Cingolani et al., 2012), which predicts the effects of genetic variants by classifying SNPs based on their predicted impact (high, moderate, low, and modifier) and function (missense, nonsense, and silent). Our annotation results revealed that the majority of SNPs in the three yak populations were located in intergenic regions, aligning with findings from a previous ddRAD sequencing study of Indian yaks (Sivalingam et al., 2020). This was followed by SNPs in intronic regions. These annotations provide valuable insights into the distribution of genetic variants and their potential implications for gene function and regulation in yak populations.

Gene Annotation and functions

The genes ASMT (acetylserotonin O-methyltransferase) and ASMTL (acetylserotonin O-methyltransferase-like) are located in the pseudoautosomal region (PAR) of the short arm of the X and Y chromosomes. The ASMT gene plays a critical role in the biosynthesis of melatonin, a hormone involved in regulating circadian rhythms (Liu et al., 2023). Research has shown that overexpression of ASMT in dairy goats and cattle leads to elevated melatonin levels in blood and milk, resulting in better milk quality (Wu et al., 2022; Ma et al., 2017; Yao et al., 2022). This hormone is essential for maintaining the circadian rhythm, which synchronizes internal biological processes with external environmental cues (Lan et al., 2018). Another significant gene, ACE2 (angiotensin-converting enzyme 2), has been observed to increase mRNA expression and protein levels during the early stages of hypoxia, before returning to near-baseline levels later (Zhang et al., 2009). This response highlights its potential role in adaptation to low-oxygen environments. Mutations in the GLRA2 gene (glycine receptor, alpha 2 subunit) have been linked to high myopia in both humans and mice (Tian et al., 2023), illustrating the gene's importance in ocular development. Additionally, the RBBP7 gene (RB Binding Protein 7) is involved in cell differentiation and proliferation, further underscoring its significance in cellular processes.

The SRY gene (Sex-determining Region Y) is crucial for male sex development, functioning as a transcription factor that initiates the formation of Sertoli cells, which are key in the development of testes. This gene is pivotal in determining male sex differentiation based on chromosomal configuration. Interestingly, our study also identified the Vascular Endothelial Growth Factor (VEGF) gene, a known target of the hypoxia-inducible factor HIF-1α, which is crucial under hypoxic conditions (Rashid et al., 2020; Kumar et al., 2024). Previous whole-genome resequencing studies on Indian yaks revealed the VEGF gene's involvement in hypoxia response, highlighting its adaptive significance. Similarly, Li et al. (2014) identified the VEGF gene under selection in Tibetan Mastiffs, emphasizing its role in adaptation to high-altitude environments. Effect of LD pruning on Y chromosome

Linkage disequilibrium (LD) describes the non-random association of alleles at different loci. In cases where the frequency of a haplotype matches the product of the individual allele frequencies, the alleles are in linkage equilibrium and are independent. Deviations from this equilibrium indicate LD, influenced by factors such as genetic drift, mutations, and recombination. Typically, alleles at loci close to each other exhibit high LD due to the infrequency of recombination events, while alleles at distant loci or on separate chromosomes show lower LD levels. Biological mechanisms, including selection, inbreeding, and population structure, further shape LD patterns (Slatkin et al., 2008). LD pruning, the process of removing SNPs based on their LD, can be complex. Traditional methods often prune SNPs with high correlations, which can lead to the removal of SNPs with significant allele frequency differences among subpopulations. This issue, known as the two-locus Wahlund effect (Nei, 1973), can obscure true genetic differentiation between populations and bias metrics like F_ST, which measure genetic divergence (Li et al., 2019).In our study, we applied various LD pruning parameters to the Y chromosome data from different yak populations. We observed that 70–96% of SNPs were pruned under different r² values. Specifically, using an r² threshold of 0.2 with a fixed window size of 50kb and a step size of 5kb, we removed 256,291, 227,778, 264,533, and 186,183 SNPs in Arunachali, Himachali, Ladakhi, and Jinchuan yaks, respectively. A similar approach in goats removed 30,139 SNPs, leaving around 15,000 SNPs (Visser et al., 2016). Increasing the r² threshold to 0.5 further reduced the number of SNPs to 226,591, 201,001, 230,752, and 174,883 in these yak populations, consistent with previous findings in bovine species (Li et al., 2022). At an r² value of 0.8, the SNP count dropped to 202,080, 178,873, 202,769, and 161,148, respectively. The extensive SNP pruning, removing between 72% and 96% of variants, highlights the potential pitfalls of stringent LD criteria, especially in sex chromosomes or allosomes. Such pruning may inadvertently eliminate loci under selection, distorting the analysis of genetic diversity and population structure (Falconer, 1996; Laird and Lange, 2011; Abramovs et al., 2020; Kanaka et al., 2023). Therefore, careful consideration is required when applying LD pruning, particularly in genetic studies involving multiple populations or sex chromosomes.

In this study, we performed a comprehensive whole genome resequencing to identify single nucleotide polymorphisms (SNPs) on the yak Y chromosome, marking a pioneering effort in this domain. Our findings demonstrated notable differences in SNP counts across various yak populations, which can be attributed to selective breeding practices. Our analysis also highlighted the significant impact of linkage disequilibrium (LD) pruning, which resulted in a substantial loss of SNPs, ranging from 70–96% depending on the parameters used. This underscores the complexity and potential pitfalls associated with LD pruning in genetic studies. To accurately assess the effects of selective breeding and ensure precise genetic differentiation, it is crucial to carefully select LD pruning parameters. This approach will help mitigate biases and enhance the reliability of genetic insights, particularly in studies involving sex chromosomes or diverse populations.

Ethics approval:

All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.

Consent for publication:

The manuscript has consent of all the authors for its publication in current format.

Conflict of interest:

The authors declare that there is no conflict of interest.

Funding:

This study was not supported by any external grants.

Author Contribution

MSD and AK executed the study; SKN and SA provided yak DNA for WGS; and MSD and AK generated the WGS data; KM, RCG, AG, GRG, RSK, and MSD analyzed the WGS data and drafted the manuscript; KJ, MC, RA and RKP revised the manuscript with inputs from all authors.

Acknowledgement

The authors thank the Director, ICAR-National Bureau of Animal Genetic Resources, Karnal, India for providing necessary facilities and support to carry out the work.

Data Availability

The raw data and .vcf file have been submitted to Sequence Read Archive (PRJNA803425) and European Variant Archive (PRJEB50815), respectively.

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Whole genome resequencing reveals Y-chromosome variants in yak: key insights into genetic diversity and population structure

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Abstract

Figures

Introduction

Material methods

Sample collection and whole genome resequencing

Sequence quality assessment, alignment, and variant calling

Variant annotation of Y chromosome using SnpEff

Annotation of genes present on Y chromosome

LD pruning on Y chromosome variants

Results

Variant calling

Annotation of genes

Effect of LD pruning on Y chromosome

Discussion

Variant calling

Variant annotation of Y chromosome using SnpEff

Gene Annotation and functions

Conclusion

Declarations

Ethics approval:

Consent for publication:

Conflict of interest:

Funding:

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

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Version 1