A compendium of genetic regulatory effects across pig tissues.

The Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.

Genome-wide association study identifies functional genomic variants associated with young stock survival in Nordic Red Dairy Cattle.

Identifying quantitative trait loci (QTL) associated with calf survival is essential for both reducing economic loss in cattle industry and understanding the genetic basis of the trait. To identify mutations and genes underlying young stock survival (YSS), we performed GWAS using de-regressed estimated breeding values of a YSS index and its component traits defined by sex and age in 3,077 Nordic Red Dairy Cattle (RDC) bulls and 2 stillbirth traits (first lactation and later lactations) in 5,141 RDC bulls. Two associated QTL regions on Bos taurus autosome (BTA) 4 and 6 were identified for the YSS index. The results of 4 YSS component traits indicate that same QTL regions were associated with bull and heifer calf mortality, but the effects were different over the growing period and suggested an additional QTL on BTA23. The GWAS on stillbirth identified 3 additional QTL regions on BTA5, 14, and 24 compared with YSS and its component traits. The conditional test of BTA6 showed at least 2 closely located QTL segregating for YSS component traits and stillbirth. We found 2 independent QTL for stillbirth on BTA23. The post-GWAS revealed LCORL, PPM1K, SSP1, MED28, and LAP3 are putative causal genes on BTA6, and a frame shift variant within LCORL, BTA6:37401770 (rs384548488) could be the putative causal variant. On BTA4, the GRB10 gene is the putative causal gene and BTA4:5296018 is the putative causal variant. In addition, NDUFA9 and FGF23 on BTA5, LYN on BTA14, and KCNK5 on BTA23 are putative causal genes for QTL for stillbirth. The gene analysis also proposed several candidate genes. Our findings shed new light on the candidate genes affecting calf survival, and the knowledge could be utilized to reduce calf mortality and thereby enhance welfare of dairy cattle.

Gene coexpression network analysis reveals perirenal adipose tissue as an important target of prenatal malnutrition in sheep.

We have previously demonstrated that pre- and early postnatal malnutrition in sheep induced depot- and sex-specific changes in adipose morphological features, metabolic outcomes, and transcriptome in adulthood, with perirenal (PER) as the major target followed by subcutaneous (SUB) adipose tissue. We aimed to identify coexpressed and hub genes in SUB and PER to identify the underlying molecular mechanisms contributing to the early nutritional programming of adipose-related phenotypic outcomes. Transcriptomes of SUB and PER of male and female adult sheep with different pre- and early postnatal nutrition histories were used to construct networks of coexpressed genes likely to be functionally associated with pre- and early postnatal nutrition histories and phenotypic traits using weighted gene coexpression network analysis. The modules from PER showed enrichment of cell cycle regulation, gene expression, transmembrane transport, and metabolic processes associated with both sexes' prenatal nutrition. In SUB (only males), a module of enriched adenosine diphosphate metabolism and development correlated with prenatal nutrition. Sex-specific module enrichments were found in PER, such as chromatin modification in the male network but histone modification and mitochondria- and oxidative phosphorylation-related functions in the female network. These sex-specific modules correlated with prenatal nutrition and adipocyte size distribution patterns. Our results point to PER as a primary target of prenatal malnutrition compared to SUB, which played only a minor role. The prenatal programming of gene expression and cell cycle, potentially through epigenetic modifications, might be underlying mechanisms responsible for observed changes in PER expandability and adipocyte-size distribution patterns in adulthood in both sexes.

On interquantile smoothness of censored quantile regression with induced smoothing.

Quantile regression has emerged as a useful and effective tool in modeling survival data, especially for cases where noises demonstrate heterogeneity. Despite recent advancements, non-smooth components involved in censored quantile regression estimators may often yield numerically unstable results, which, in turn, lead to potentially self-contradicting conclusions. We propose an estimating equation-based approach to obtain consistent estimators of the regression coefficients of interest via the induced smoothing technique to circumvent the difficulty. Our proposed estimator can be shown to be asymptotically equivalent to its original unsmoothed version, whose consistency and asymptotic normality can be readily established. Extensions to handle functional covariate data and recurrent event data are also discussed. To alleviate the heavy computational burden of bootstrap-based variance estimation, we also propose an efficient resampling procedure that reduces the computational time considerably. Our numerical studies demonstrate that our proposed estimator provides substantially smoother model parameter estimates across different quantile levels and can achieve better statistical efficiency compared to a plain estimator under various finite-sample settings. The proposed method is also illustrated via four survival datasets, including the HMO (health maintenance organizations) HIV (human immunodeficiency virus) data, the primary biliary cirrhosis (PBC) data, and so forth.

Long-Term Simulation of Microgravity Induces Changes in Gene Expression in Breast Cancer Cells.

Microgravity changes the gene expression pattern in various cell types. This study focuses on the breast cancer cell lines MCF-7 (less invasive) and MDA-MB-231 (triple-negative, highly invasive). The cells were cultured for 14 days under simulated microgravity (s-µg) conditions using a random positioning machine (RPM). We investigated cytoskeletal and extracellular matrix (ECM) factors as well as focal adhesion (FA) and the transmembrane proteins involved in different cellular signaling pathways (MAPK, PAM and VEGF). The mRNA expressions of 24 genes of interest (TUBB, ACTB, COL1A1, COL4A5, LAMA3, ITGB1, CD44, VEGF, FLK1, EGFR, SRC, FAK1, RAF1, AKT1, ERK1, MAPK14, MAP2K1, MTOR, RICTOR, VCL, PXN, CDKN1, CTNNA1 and CTNNB1) were determined by quantitative real-time PCR (qPCR) and studied using STRING interaction analysis. Histochemical staining was carried out to investigate the morphology of the adherent cells (ADs) and the multicellular spheroids (MCSs) after RPM exposure. To better understand this experimental model in the context of breast cancer patients, a weighted gene co-expression network analysis (WGCNA) was conducted to obtain the expression profiles of 35 breast cell lines from the HMS LINCS Database. The qPCR-verified genes were searched in the mammalian phenotype database and the human genome-wide association studies (GWAS) Catalog. The results demonstrated the positive association between the real metastatic microtumor environment and MCSs with respect to the extracellular matrix, cytoskeleton, morphology, different cellular signaling pathway key proteins and several other components. In summary, the microgravity-engineered three-dimensional MCS model can be utilized to study breast cancer cell behavior and to assess the therapeutic efficacies of drugs against breast cancer in the future.

Application of mixed linear models for the estimation of functional effects on bovine stature based on SNP summary statistics from a whole-genome association study.

Genome-wide association studies (GWAS) help identify polymorphic sites or genes linked to phenotypic variance, but a few identified genes and/or single nucleotide polymorphisms (SNPs) are unlikely to explain a large part of the phenotypic variability of complex traits. In this study, the focus was moved from single loci to functional units, expressed by the metabolic pathways as defined in the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database. Consequently, the aim of this study was to estimate KEGG effects on stature in three Nordic dairy cattle breeds using SNP effects from GWAS as the dependent variable. The SNPs were annotated to genes, then the genes to KEGG pathways. The effects of KEGG pathways were estimated separately for each breed using a mixed linear model incorporating the similarity between pathways expressed by common genes. The KEGG pathway D-amino acid metabolism (map00473) was estimated to be significant for stature in two of the analysed breeds and revealed a borderline significance in the third breed. Thus, we demonstrate that the approach to statistical modelling of higher order functional effects on complex traits is useful, and provides evidence of the importance of D-amino acids for growth in cattle.

Geographical contrasts of Y-chromosomal haplogroups from wild and domestic goats reveal ancient migrations and recent introgressions.

By their paternal transmission, Y-chromosomal haplotypes are sensitive markers of population history and male-mediated introgression. Previous studies identified biallelic single-nucleotide variants in the SRY, ZFY and DDX3Y genes, which in domestic goats identified four major Y-chromosomal haplotypes, Y1A, Y1B, Y2A and Y2B, with a marked geographical partitioning. Here, we extracted goat Y-chromosomal variants from whole-genome sequences of 386 domestic goats (75 breeds) and seven wild goat species, which were generated by the VarGoats goat genome project. Phylogenetic analyses indicated domestic haplogroups corresponding to Y1B, Y2A and Y2B, respectively, whereas Y1A is split into Y1AA and Y1AB. All five haplogroups were detected in 26 ancient DNA samples from southeast Europe or Asia. Haplotypes from present-day bezoars are not shared with domestic goats and are attached to deep nodes of the trees and networks. Haplogroup distributions for 186 domestic breeds indicate ancient paternal population bottlenecks and expansions during migrations into northern Europe, eastern and southern Asia, and Africa south of the Sahara. In addition, sharing of haplogroups indicates male-mediated introgressions, most notably an early gene flow from Asian goats into Madagascar and the crossbreeding that in the 19th century resulted in the popular Boer and Anglo-Nubian breeds. More recent introgressions are those from European goats into the native Korean goat population and from Boer goat into Uganda, Kenya, Tanzania, Malawi and Zimbabwe. This study illustrates the power of the Y-chromosomal variants for reconstructing the history of domestic species with a wide geographical range.

Large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans.

BACKGROUND: Imputation from genotyping array to whole-genome sequence variants using resequencing of representative reference populations enhances our ability to map genetic factors affecting complex phenotypes in livestock species. The accumulation of knowledge about gene function in human and laboratory animals can provide substantial advantage for genomic research in livestock species. RESULTS: In this study, 201,388 pigs from three commercial Danish breeds genotyped with low to medium (8.5k to 70k) SNP arrays were imputed to whole genome sequence variants using a two-step approach. Both imputation steps achieved high accuracies, and in total this yielded 26,447,434 markers on 18 autosomes. The average estimated imputation accuracy of markers with minor allele frequency ≥ 0.05 was 0.94. To overcome the memory consumption of running genome-wide association study (GWAS) for each breed, we performed within-breed subpopulation GWAS then within-breed meta-analysis for average daily weight gain (ADG), followed by a multi-breed meta-analysis of GWAS summary statistics. We identified 15 quantitative trait loci (QTL). Our post-GWAS analysis strategy to prioritize of candidate genes including information like gene ontology, mammalian phenotype database, differential expression gene analysis of high and low feed efficiency pig and human GWAS catalog for height, obesity, and body mass index, we proposed MRAP2, LEPROT, PMAIP1, ENSSSCG00000036234, BMP2, ELFN1, LIG4 and FAM155A as the candidate genes with biological support for ADG in pigs. CONCLUSION: Our post-GWAS analysis strategy helped to identify candidate genes not just by distance to the lead SNP but also by multiple sources of biological evidence. Besides, the identified QTL overlap with genes which are known for their association with human growth-related traits. The GWAS with this large data set showed the power to map the genetic factors associated with ADG in pigs and have added to our understanding of the genetics of growth across mammalian species.

Pig genome functional annotation enhances the biological interpretation of complex traits and human disease.

The functional annotation of livestock genomes is crucial for understanding the molecular mechanisms that underpin complex traits of economic importance, adaptive evolution and comparative genomics. Here, we provide the most comprehensive catalogue to date of regulatory elements in the pig (Sus scrofa) by integrating 223 epigenomic and transcriptomic data sets, representing 14 biologically important tissues. We systematically describe the dynamic epigenetic landscape across tissues by functionally annotating 15 different chromatin states and defining their tissue-specific regulatory activities. We demonstrate that genomic variants associated with complex traits and adaptive evolution in pig are significantly enriched in active promoters and enhancers. Furthermore, we reveal distinct tissue-specific regulatory selection between Asian and European pig domestication processes. Compared with human and mouse epigenomes, we show that porcine regulatory elements are more conserved in DNA sequence, under both rapid and slow evolution, than those under neutral evolution across pig, mouse, and human. Finally, we provide biological insights on tissue-specific regulatory conservation, and by integrating 47 human genome-wide association studies, we demonstrate that, depending on the traits, mouse or pig might be more appropriate biomedical models for different complex traits and diseases.

Transcriptomics analysis of differentially expressed genes in subcutaneous and perirenal adipose tissue of sheep as affected by their pre- and early postnatal malnutrition histories.

BACKGROUND: Early life malnutrition is known to target adipose tissue with varying impact depending on timing of the insult. This study aimed to identify differentially expressed genes in subcutaneous (SUB) and perirenal (PER) adipose tissue of 2.5-years old sheep to elucidate the biology underlying differential impacts of late gestation versus early postnatal malnutrition on functional development of adipose tissues. Adipose tissues were obtained from 37 adult sheep born as twins to dams fed either NORM (fulfilling energy and protein requirements), LOW (50% of NORM) or HIGH (110% of protein and 150% of energy requirements) diets in the last 6-weeks of gestation. From day 3 to 6 months of age, lambs were fed high-carbohydrate-high-fat (HCHF) or moderate low-fat (CONV) diets, and thereafter the same moderate low-fat diet. RESULTS: The gene expression profile of SUB in the adult sheep was not affected by the pre- or early postnatal nutrition history. In PER, 993 and 186 differentially expressed genes (DEGs) were identified in LOW versus HIGH and NORM, respectively, but no DEG was found between HIGH and NORM. DEGs identified in the mismatched pre- and postnatal nutrition groups LOW-HCHF (101) and HIGH-HCHF (192) were largely downregulated compared to NORM-CONV. Out of 831 DEGs, 595 and 236 were up- and downregulated in HCHF versus CONV, respectively. The functional enrichment analyses revealed that transmembrane (ion) transport activities, motor activities related to cytoskeletal and spermatozoa function (microtubules and the cytoskeletal motor protein, dynein), and responsiveness to the (micro) environmental extracellular conditions, including endocrine and nervous stimuli were enriched in the DEGs of LOW versus HIGH and NORM. We confirmed that mismatched pre- and postnatal feeding was associated with long-term programming of adipose tissue remodeling and immunity-related pathways. In agreement with phenotypic measurements, early postnatal HCHF feeding targeted pathways involved in kidney cell differentiation, and mismatched LOW-HCHF sheep had specific impairments in cholesterol metabolism pathways. CONCLUSIONS: Both pre- and postnatal malnutrition differentially programmed (patho-) physiological pathways with implications for adipose functional development associated with metabolic dysfunctions, and PER was a major target.

MeSCoT: the tool for quantitative trait simulation through the mechanistic modeling of genes' regulatory interactions.

This work represents a novel mechanistic approach to simulate and study genomic networks with accompanying regulatory interactions and complex mechanisms of quantitative trait formation. The approach implemented in MeSCoT software is conceptually based on the omnigenic genetic model of quantitative (complex) trait, and closely imitates the basic in vivo mechanisms of quantitative trait realization. The software provides a framework to study molecular mechanisms of gene-by-gene and gene-by-environment interactions underlying quantitative trait's realization and allows detailed mechanistic studies of impact of genetic and phenotypic variance on gene regulation. MeSCoT performs a detailed simulation of genes' regulatory interactions for variable genomic architectures and generates complete set of transcriptional and translational data together with simulated quantitative trait values. Such data provide opportunities to study, for example, verification of novel statistical methods aiming to integrate intermediate phenotypes together with final phenotype in quantitative genetic analyses or to investigate novel approaches for exploiting gene-by-gene and gene-by-environment interactions.

Inclusion of endophenotypes in a standard GWAS facilitate a detailed mechanistic understanding of genetic elements that control blood lipid levels.

Dyslipidemia is the primary cause of cardiovascular disease, which is a serious human health problem in large parts of the world. Therefore, it is important to understand the genetic and molecular mechanisms that regulate blood levels of cholesterol and other lipids. Discovery of genetic elements in the regulatory machinery is often based on genome wide associations studies (GWAS) focused on end-point phenotypes such as total cholesterol level or a disease diagnosis. In the present study, we add endophenotypes, such as serum levels of intermediate metabolites in the cholesterol synthesis pathways, to a GWAS analysis and use the pig as an animal model. We do this to increase statistical power and to facilitate biological interpretation of results. Although the study population was limited to ~ 300 individuals, we identify two genome-wide significant associations and ten suggestive associations. Furthermore, we identify 28 tentative associations to loci previously associated with blood lipids or dyslipidemia associated diseases. The associations with endophenotypes may inspire future studies that can dissect the biological mechanisms underlying these previously identified associations and add a new level of understanding to previously identified associations.

Genomic diversity revealed by whole-genome sequencing in three Danish commercial pig breeds.

Whole-genome sequencing of 217 animals from three Danish commercial pig breeds (Duroc, Landrace [LL], and Yorkshire [YY]) was performed. Twenty-six million single-nucleotide polymorphisms (SNPs) and 8 million insertions or deletions (indels) were uncovered. Among the SNPs, 493,099 variants were located in coding sequences, and 29,430 were predicted to have a high functional impact such as gain or loss of stop codon. Using the whole-genome sequence dataset as the reference, the imputation accuracy for pigs genotyped with high-density SNP chips was examined. The overall average imputation accuracy for all biallelic variants (SNP and indel) was 0.69, while it was 0.83 for variants with minor allele frequency > 0.1. This study provides whole-genome reference data to impute SNP chip-genotyped animals for further studies to fine map quantitative trait loci as well as improving the prediction accuracy in genomic selection. Signatures of selection were identified both through analyses of fixation and differentiation to reveal selective sweeps that may have had prominent roles during breed development or subsequent divergent selection. However, the fixation indices did not indicate a strong divergence among these three breeds. In LL and YY, the integrated haplotype score identified genomic regions under recent selection. These regions contained genes for olfactory receptors and oxidoreductases. Olfactory receptor genes that might have played a major role in the domestication were previously reported to have been under selection in several species including cattle and swine.

Integrated Karyotypes of Diploid and Tetraploid Carrizo Citrange (Citrus sinensis L. Osbeck × Poncirus trifoliata L. Raf.) as Determined by Sequential Multicolor Fluorescence in situ Hybridization With Tandemly Repeated DNA Sequences.

Carrizo citrange [Citrus sinensis (L.) Osbeck × Poncirus trifoliata (L.) Raf., CC] is one of the most widely used rootstocks in citriculture worldwide, but its cytogenetic study has been hampered by its inherent small size, morphological similarity to mitotic chromosomes, and lack of accessible cytological landmarks. In our previous study, a spontaneously occurring tetraploid CC seedling was discovered. The main goals of this study were to elucidate the chromosome constitution and construct the karyotypes of diploid CC rootstock and its corresponding spontaneously occurring tetraploid. To accomplish these, the chromosomal characteristics were investigated by sequential multicolor fluorescence in situ hybridization (FISH) with eight properly labeled repetitive DNA sequences, including a centromere-like repeat, four satellite repeats, two rDNAs, and an oligonucleotide of telomeric (TTTAGGG) n repeat. The results nicely demonstrated that these repetitive DNAs are reliable cytogenetic markers that collectively facilitate simultaneous and unequivocal identification of homologous chromosome pairs. Based on chromosome size and morphology together with FISH patterns of repetitive DNAs, an integrated karyotype of CC rootstock was constructed, consisting of 2n = 2x = 12m (1sat) + 6sm with karyotype asymmetry degree being divided into 2B category. Cytogenetically speaking, the variable and asymmetric distribution patterns of these repetitive DNAs were fully confirmed the hybrid nature of CC rootstock. In addition, comparative distribution patterns and chromosomal localizations of these repetitive DNAs convincingly showed that this tetraploid CC material arose from somatic chromosome doubling of diploid CC rootstock. This study revealed, for the first time, the integrated karyotype and chromosomal characteristics of this important citrus rootstock as well as its spontaneously occurring tetraploid plant. Furthermore, this study is a good prospective model for study species with morphologically indistinguishable small chromosomes.

Chromosome-level genome assembly of Tarim red deer, Cervus elaphus yarkandensis.

Tarim red deer (Cervus elaphus yarkandensis) is the only subspecies of red deer (of 22 subspecies) from Central Asia. This species is a desert dweller of the Tarim Basin of southern Xinjiang, China, and exhibits some unique adaptations to the dry and extreme hot climate. We report here the assembly of a Tarim red deer genome employing a 10X Genomics library, termed CEY_v1. Our genome consisted of 2.6 Gb with contig N50 and scaffold N50 of 275.5 Kb and 31.7 Mb, respectively. Around 96% of the assembled sequences were anchored onto 34 chromosomes based on the published high-quality red deer genetic linkage map. More than 94% BUSCOs complete genes (including 90.5% single and 3.6% duplicated ones) were detected in the CEY_v1 and 20,653 genes were annotated. The CEY_v1 is expected to contribute to comparative analysis of genome biology, to evolutionary studies within Cervidae, and to facilitating investigation of mechanisms underlying adaptation of this species to the extreme dry and hot climate.

Distinguishing pleiotropy from linked QTL between milk production traits and mastitis resistance in Nordic Holstein cattle.

BACKGROUND: Production and health traits are central in cattle breeding. Advances in next-generation sequencing technologies and genotype imputation have increased the resolution of gene mapping based on genome-wide association studies (GWAS). Thus, numerous candidate genes that affect milk yield, milk composition, and mastitis resistance in dairy cattle are reported in the literature. Effect-bearing variants often affect multiple traits. Because the detection of overlapping quantitative trait loci (QTL) regions from single-trait GWAS is too inaccurate and subjective, multi-trait analysis is a better approach to detect pleiotropic effects of variants in candidate genes. However, large sample sizes are required to achieve sufficient power. Multi-trait meta-analysis is one approach to deal with this problem. Thus, we performed two multi-trait meta-analyses, one for three milk production traits (milk yield, protein yield and fat yield), and one for milk yield and mastitis resistance. RESULTS: For highly correlated traits, the power to detect pleiotropy was increased by multi-trait meta-analysis compared with the subjective assessment of overlapping of single-trait QTL confidence intervals. Pleiotropic effects of lead single nucleotide polymorphisms (SNPs) that were detected from the multi-trait meta-analysis were confirmed by bivariate association analysis. The previously reported pleiotropic effects of variants within the DGAT1 and MGST1 genes on three milk production traits, and pleiotropic effects of variants in GHR on milk yield and fat yield were confirmed. Furthermore, our results suggested that variants in KCTD16, KCNK18 and ENSBTAG00000023629 had pleiotropic effects on milk production traits. For milk yield and mastitis resistance, we identified possible pleiotropic effects of variants in two genes, GC and DGAT1. CONCLUSIONS: Multi-trait meta-analysis improves our ability to detect pleiotropic interactions between milk production traits and identifies variants with pleiotropic effects on milk production traits and mastitis resistance. In particular, this should contribute to better understand the biological mechanisms that underlie the unfavorable genetic correlation between milk yield and mastitis.

Censored quantile regression model with time-varying covariates under length-biased sampling.

Quantile regression is a flexible and effective tool for modeling survival data and its relationship with important covariates, which often vary over time. Informative right censoring of data from the prevalent cohort within the population often results in length-biased observations. We propose an estimating equation-based approach to obtain consistent estimators of the regression coefficients of interest based on length-biased observations with time-dependent covariates. In addition, inspired by Zeng and Lin 2008, we also develop a more numerically stable procedure for variance estimation. Large sample properties including consistency and asymptotic normality of the proposed estimator are established. Numerical studies presented demonstrate convincing performance of the proposed estimator under various settings. The application of the proposed method is demonstrated using the Oscar dataset.

Molecular evidence for adaptive evolution of olfactory-related genes in cervids.

BACKGROUND: Cervids have evolved very successful means for survival and thriving to adapt to various climates and environments. One of these successful means might be the effective and efficient way of communication. To support this notion, cervids are well equipped with a variety of skin glands that distribute in different body regions. However, studies relevant to adaptive evolution in cervids, particularly on olfactory reception at the molecular level, have thus far not been reported. OBJECTIVE: To provide valuable insights into molecular evidence for the adaptive evolution of olfactory-related gene in cervids. METHODS: Based on recently sequenced genomes of cervids and closely-related-species, we performed comparative genomic analysis at genome level using bioinformatics tools. RESULTS: Tree topology strongly supported that Bovidae was the sister group of Moschidae and both formed a branch that was then clustered with Cervidae. Expansion of heavy chain genes of the dynein family and 51 rapidly evolving genes could be associated with adaptation of cilia that serve as sensory organelles and act as cellular antennae. Based on the branch-site model test along the deer branch spanning 7-21 mammalian species, 14 deer olfactory receptor genes were found to be undergoing positive selection pressure and 89 positive selection sites (probability > 60%) had amino acid substitutions unique to deer. CONCLUSION: This study, for the first time, provides significant molecular evidence for adaption of olfactory-related genes of cervids according to their olfactory behavior.

Evolution and Domestication Footprints Uncovered from the Genomes of Coix.

Coix lacryma-jobi, a plant species closely related to Zea and Sorghum, is an important food and medicinal crop in Asia. However, no reference genome of this species has been reported, and its exact phylogeny within the Andropogoneae remains unresolved. Here, we generated a high-quality genome assembly of coix comprising ∼1.73 Gb with 44 485 predicted protein-coding genes. We found coix to be a typical diploid plant with an overall 1-to-1 syntenic relationship with the Sorghum genome, despite its drastic genome expansion (∼2.3-fold) due mainly to the activity of transposable elements. Phylogenetic analysis revealed that coix diverged with sorghum ∼10.41 million years ago, which was ∼1.49 million years later than the divergence between sorghum and maize. Resequencing of 27 additional coix accessions revealed that they could be unambiguously separated into wild relatives and cultivars, and suggested that coix experienced a strong genetic bottleneck, resulting in the loss of about half of the genetic diversity during domestication, even though many traits have remained undomesticated. Our data not only provide novel comparative genomic and evolutionary insights into the Andropogoneae lineage, but also an important resource that will greatly benefit molecular breeding of this important crop.