Dataset Information

Inferring demography from runs of homozygosity in whole-genome sequence, with correction for sequence errors.

ABSTRACT: Whole-genome sequence is potentially the richest source of genetic data for inferring ancestral demography. However, full sequence also presents significant challenges to fully utilize such large data sets and to ensure that sequencing errors do not introduce bias into the inferred demography. Using whole-genome sequence data from two Holstein cattle, we demonstrate a new method to correct for bias caused by hidden errors and then infer stepwise changes in ancestral demography up to present. There was a strong upward bias in estimates of recent effective population size (Ne) if the correction method was not applied to the data, both for our method and the Li and Durbin (Inference of human population history from individual whole-genome sequences. Nature 475:493-496) pairwise sequentially Markovian coalescent method. To infer demography, we use an analytical predictor of multiloci linkage disequilibrium (LD) based on a simple coalescent model that allows for changes in Ne. The LD statistic summarizes the distribution of runs of homozygosity for any given demography. We infer a best fit demography as one that predicts a match with the observed distribution of runs of homozygosity in the corrected sequence data. We use multiloci LD because it potentially holds more information about ancestral demography than pairwise LD. The inferred demography indicates a strong reduction in the Ne around 170,000 years ago, possibly related to the divergence of African and European Bos taurus cattle. This is followed by a further reduction coinciding with the period of cattle domestication, with Ne of between 3,500 and 6,000. The most recent reduction of Ne to approximately 100 in the Holstein breed agrees well with estimates from pedigrees. Our approach can be applied to whole-genome sequence from any diploid species and can be scaled up to use sequence from multiple individuals.

SUBMITTER: MacLeod IM

PROVIDER: S-EPMC3748359 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Inferring demography from runs of homozygosity in whole-genome sequence, with correction for sequence errors.

MacLeod Iona M IM Larkin Denis M DM Lewin Harris A HA Hayes Ben J BJ Goddard Mike E ME

Molecular biology and evolution 20130710 9

Whole-genome sequence is potentially the richest source of genetic data for inferring ancestral demography. However, full sequence also presents significant challenges to fully utilize such large data sets and to ensure that sequencing errors do not introduce bias into the inferred demography. Using whole-genome sequence data from two Holstein cattle, we demonstrate a new method to correct for bias caused by hidden errors and then infer stepwise changes in ancestral demography up to present. The ...[more]

PMID: 23842528

Similar Datasets

Project description:Tunchang pigs are an indigenous pig population in China known for their high tolerance to roughage, delicious meat, and fecundity. However, the number of Tunchang pigs has been declining due to the influence of commercial breeds and African swine fever, which could potentially lead to inbreeding. To assess the inbreeding level and the genetic basis of important traits in Tunchang pigs, our research investigated the patterns in "runs of homozygosity" (ROHs) using whole genome resequencing data from 32 Tunchang pigs. The study aimed to determine the length, number, coverage, and distribution model of ROHs in Tunchang pigs, as well as genomic regions with high ROH frequencies. The results of the study revealed that a total of 20,499,374 single-nucleotide polymorphisms (SNPs) and 1953 ROH fragments were recognized in 32 individuals. The ROH fragments in Tunchang pigs were predominantly short, ranging from 0.5 to 1 megabases (Mb) in length. Furthermore, the coverage of ROHs varied across chromosomes, with chromosome 3 having the highest coverage and chromosome 11 having the lowest coverage. The genetic diversity of Tunchang pigs was found to be relatively high based on the values of HE (expected heterozygosity), HO (observed heterozygosity), pi (nucleotide diversity), Ne (effective population size), and MAF (minor allele frequency). The average inbreeding coefficients of Tunchang pigs, as determined by three different methods (FHOM, FGRM, and FROH), were 0.019, 0.0138, and 0.0304, respectively. These values indicate that the level of inbreeding in Tunchang pigs is currently low. Additionally, the study identified a total of 13 ROH islands on all chromosomes, which in total contained 38,913 SNPs and 120 genes. These ROH islands included genes associated with economically important traits, including meat quality (GYS1, PHLPP1, SLC27A5, and CRTC1), growth and development (ANKS1A, TAF11, SPDEF, LHB, and PACSIN1), and environmental adaptation (SLC26A7). The findings of this research offer valuable perspectives on the present status of Tunchang pig resources and offer a reference for breeding conservation plans and the efficient utilization of Tunchang pigs in the future. By understanding the inbreeding level and genetic basis of important traits in Tunchang pigs, conservation efforts can be targeted towards maintaining genetic diversity and promoting the sustainable development of this indigenous pig population.

Project description:Genome-wide runs of homozygosity (ROH) are suitable for understanding population history, calculating genomic inbreeding, deciphering genetic architecture of complex traits and diseases as well as identifying genes linked with agro-economic traits. Autozygosity and ROH islands, genomic regions with elevated ROH frequencies, were characterized in 112 animals of seven Indian native cattle breeds (B. indicus) using BovineHD BeadChip. In total, 4138 ROH were detected. The average number of ROH per animal was maximum in draft breed, Kangayam (63.62 ± 22.71) and minimum in dairy breed, Sahiwal (24.62 ± 11.03). The mean ROH length was maximum in Vechur (6.97 Mb) and minimum in Hariana (4.04 Mb). Kangayam revealed the highest ROH based inbreeding (FROH > 1Mb = 0.113 ± 0.059), whereas Hariana (FROH > 1Mb = 0.042 ± 0.031) and Sahiwal (FROH > 1Mb = 0.043 ± 0.048) showed the lowest. The high standard deviation observed in each breed highlights a considerable variability in autozygosity. Out of the total autozygous segments observed in each breed except Vechur, > 80% were of short length (< 8 Mb) and contributed almost 50% of the genome proportion under ROH. However, in Vechur cattle, long ROH contributed 75% of the genome proportion under ROH. ROH patterns revealed Hariana and Sahiwal breeds as less consanguineous, while recent inbreeding was apparent in Vechur. Maximum autozygosity observed in Kangayam is attributable to both recent and ancient inbreeding. The ROH islands were harbouring higher proportion of QTLs for production traits (20.68% vs. 14.64%; P≤ 0.05) but lower for reproductive traits (11.49% vs. 15.76%; P≤ 0.05) in dairy breeds compared to draft breed. In draft cattle, genes associated with resistant to diseases/higher immunity (LYZL1, SVIL, and GPX4) and stress tolerant (CCT4) were identified in ROH islands; while in dairy breeds, for milk production (PTGFR, CSN1S1, CSN2, CSN1S2, and CSN3). Significant difference in ROH islands among large and short statured breeds was observed at chromosome 3 and 5 involving genes like PTGFR and HMGA2 responsible for milk production and stature, respectively. PCA analysis on consensus ROH regions revealed distinct clustering of dairy, draft and short stature cattle breeds.

Project description:Background Alpaca (Vicugna pacos), llama (Lama glama), vicugna (Vicugna vicugna) and guanaco (Lama guanicoe), are the camelid species distributed over the Andean high-altitude grasslands, the Altiplano, and the Patagonian arid steppes. Despite the wide interest on these animals, most of the loci under selection are still unknown. Using whole-genome sequencing (WGS) data we investigated the occurrence and the distribution of Runs Of Homozygosity (ROHs) across the South American Camelids (SACs) genome to identify the genetic relationship between the four species and the potential signatures of selection. Results A total of 37 WGS samples covering the four species was included in the final analysis. The multi-dimensional scaling approach showed a clear separation between the four species; however, admixture analysis suggested a strong genetic introgression from vicugna and llama to alpaca. Conversely, very low genetic admixture of the guanaco with the other SACs was found. The four species did not show significant differences in the number, length of ROHs (100-500 kb) and genomic inbreeding values. Longer ROHs (> 500 kb) were found almost exclusively in alpaca. Seven overlapping ROHs were shared by alpacas, encompassing nine loci (FGF5, LOC107034918, PRDM8, ANTXR2, LOC102534792, BSN, LOC116284892, DAG1 and RIC8B) while nine overlapping ROHs were found in llama with twenty-five loci annotated (ERC2, FZD9, BAZ1B, BCL7B, LOC116284208, TBL2, MLXIPL, PHF20, TRNAD-AUC, LOC116284365, RBM39, ARFGEF2, DCAF5, EXD2, HSPB11, LRRC42, LDLRAD1, TMEM59, LOC107033213, TCEANC2, LOC102545169, LOC116278408, SMIM15, NDUFAF2 and RCOR1). Four overlapping ROHs, with three annotated loci (DLG1, KAT6B and PDE4D) and three overlapping ROHs, with seven annotated genes (ATP6V1E1, BCL2L13, LOC116276952, BID, KAT6B, LOC116282667 and LOC107034552), were detected for vicugna and guanaco, respectively. Conclusions The signatures of selection revealed genomic areas potentially selected for production traits as well as for natural adaptation to harsh environment. Alpaca and llama hint a selection driven by environment as well as by farming purpose while vicugna and guanaco showed selection signals for adaptation to harsh environment. Interesting, signatures of selection on KAT6B gene were identified for both vicugna and guanaco, suggesting a positive effect on wild populations fitness. Such information may be of interest to further ecological and animal production studies. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-023-09547-3.

Dataset Information

Inferring demography from runs of homozygosity in whole-genome sequence, with correction for sequence errors.

Publications

Inferring demography from runs of homozygosity in whole-genome sequence, with correction for sequence errors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets