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Abstract Hu sheep (HS), a breed of sheep carrying the FecB mutation gene, is known for its “year-round estrus and multiple births” and is an ideal model for studying the high fecundity mechanisms of livestock. Through analyzing and comparing the genomic selection features of Hu sheep and other sheep breeds, we identified a series of candidate genes that may play a role in Hu sheep’s high fecundity mechanisms. In this study, we conducted whole-genome resequencing on six breeds and screened key mutations significantly correlated with high reproductive traits in sheep. Notably, the CC2D1B gene was selected by the fixation index (F ST) and the cross-population composite likelihood ratio (XP-CLR) methods in HS and other five breeds. It was worth noting that the CC2D1B gene in HS was different from that in other sheep breeds, and seven missense mutations have been identified. Furthermore, the linkage disequilibrium (LD) analysis revealed a strong linkage disequilibrium in this specific gene region. Subsequently, by performing different grouping based on FecB genotypes in Hu sheep, genome-wide selective signal analysis screened several genes related to reproduction, such as BMPR1B and PPM1K. Besides, F ST analysis identified functional genes related to reproductive traits, including RHEB, HSPA2, PPP1CC, HVCN1, and CCDC63. Additionally, a missense mutation was found in the CCDC63 gene and the haplotype was different between the high reproduction (HR) group and low reproduction (LR) group in HS. In summary, we discovered genetic differentiation among six distinct breeding sheep breeds at the whole genome level. Additionally, we identified a set of genes which were associated with reproductive performance in Hu sheep and visualized how these genes differed in different breeds. These findings laid a theoretical foundation for understanding genetic mechanisms behind high prolific traits in sheep.

Cashmere goats are valuable genetic resources which are famous worldwide for their high-quality fiber. Runs of homozygosity (ROHs) have been identified as an efficient tool to assess inbreeding level and identify related genes under selection. However, there is limited research on ROHs in cashmere goats. Therefore, we investigated the ROH pattern, assessed genomic inbreeding levels and examined the candidate genes associated with the cashmere trait using whole-genome resequencing data from 123 goats. Herein, the Inner Mongolia cashmere goat presented the lowest inbreeding coefficient of 0.0263. In total, we identified 57,224 ROHs. Seventy-four ROH islands containing 50 genes were detected. Certain identified genes were related to meat, fiber and milk production (FGF1, PTPRM, RERE, GRID2, RARA); fertility (BIRC6, ECE2, CDH23, PAK1); disease or cold resistance and adaptability (PDCD1LG2, SVIL, PRDM16, RFX4, SH3BP2); and body size and growth (TMEM63C, SYN3, SDC1, STRBP, SMG6). 135 consensus ROHs were identified, and we found candidate genes (FGF5, DVL3, NRAS, KIT) were associated with fiber length or color. These findings enhance our comprehension of inbreeding levels in cashmere goats and the genetic foundations of traits influenced by selective breeding. This research contributes significantly to the future breeding, reservation and use of cashmere goats and other goat breeds.

Tibetan goats, Taihang goats, Jining grey goats, and Meigu goats are the representative indigenous goats in China, found in Qinghai-Tibet Plateau, Western pastoral area, Northern and Southern agricultural regions. Very few studies have conducted a comprehensive analysis of the genomic diversity and selection of these breeds. We genotyped 96 unrelated individuals, using goat 53 K Illumina BeadChip array, of the following goat breeds: Tibetan (TG), Taihang (THG), Jining grey (JGG), and Meigu (MGG). A total of 45 951 single nucleotide polymorphisms were filtered to estimate the genetic diversity and selection signatures. All breeds had a high proportion (over 95%) of polymorphic loci. The observed and excepted heterozygosity ranged from 0.338 (MGG) to 0.402 (JGG) and 0.339 (MGG) to 0.395 (JGG), respectively. Clustering analysis displayed a genetically distinct lineage for each breed, and their Fst were greater than 0.25, indicating that they had a higher genetic differentiation between groups. Furthermore, effective population size reduced in all four populations, indicating a loss of genetic diversity. In addition, runs of homozygosity were mainly distributed in 5–10 Mb. Lastly, we identified signature genes, which were closely related to high-altitude adaptation (ADIRF) and prolificity (CNTROB, SMC3, and PTEN). This study provides a valuable resource for future studies on genome-wide perspectives on the diversity and selection signatures of Chinese indigenous goats.

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Early weaning and milk substitutes increase the incidence of diarrhea in young ruminants, which may modify their gut microbiota, metabolism, immunity, and health. The aim of the study was to determine if early weaning and milk substitutes affect the gut microbiota, metabolism, and immunological status of goat kids suffering from diarrhea. The 16S rRNA gene and metagenomic sequencing in feces and serum metabolomics of early-weaned and artificially reared goat kids suffering from diarrhea (DK group) and healthy goat kids reared by their mothers (HK group) were analyzed. The serum biochemistry and immunoglobulin concentration were also determined. Several probiotics, such as Streptococcus and Lactobacillus, were higher in the feces of the DK group than in feces of the HK group. Ruminococcus sp. was elevated in the feces of HKs, likely being a biomarker for goat health. Taking all the carbohydrate-active enzyme (CAZyme) families into consideration, 20 CAZyme families were different between the groups. Compared with the DK group, the relative quantity of glycoside hydrolases (GH) and glycosyltransferase (GT) families in the HK group decreased. GT70 was only identified in HK kids participating in the activity of β-glucuronosyltransferase during the carbohydrate metabolism. Overall, 24 metabolites were different between the groups, which were mainly involved in protein digestion and absorption, cyanoamino acid metabolism, and cholesterol metabolism. The concentrations of immunoglobulins G and M were significantly lower in the DK than in the HK group. In conclusion, our study characterized the fecal microbiota, metabolism, and immunological status of early-weaned and artificially reared goat kids suffering from diarrhea.

Horns, also known as headgear, are a unique structure of ruminants. As ruminants are globally distributed, the study of horn formation is critical not only for increasing our understanding of natural and sexual selection but also for the breeding of polled sheep breeds to facilitate modern sheep farming. Despite this, a significant number of the underlying genetic pathways in sheep horn remain unclear. In this study, to clarify the gene expression profile of horn buds and investigate the key genes in horn bud formation, RNA-sequencing (RNA-seq) technology was utilized to investigate differential gene expression in the horn buds and adjacent forehead skin of Altay sheep fetuses. There were only 68 differentially expressed genes (DEGs) identified, consisting of 58 up-regulated genes and 10 down-regulated genes. RXFP2 was differentially up-regulated in the horn buds and had the highest significance (p-value = 7.42 × 10−14). In addition, 32 DEGs were horn-related genes identified in previous studies, such as RXFP2, FOXL2, SFRP4, SFRP2, KRT1, KRT10, WNT7B, and WNT3. Further, Gene Ontology (GO) analysis showed that the DEGs were mainly enriched with regard to growth, development, and cell differentiation. Pathway analysis revealed that the Wnt signaling pathway may be responsible for horn development. Further, through combining the protein–protein interaction networks of the DEGs, it was found that the top five hub genes, namely, ACAN, SFRP2, SFRP4, WNT3, and WNT7B, were also associated with horn development. Our results suggest that only a few key genes, including RXFP2, are involved in bud formation. This study not only validates the expression of candidate genes identified at the transcriptome level in previous studies but also provides new possible marker genes for horn development, which may promote our understanding of the genetic mechanisms of horn formation.

Skeletal muscle satellite cells (SMSCs), which are highly multifunctional muscle-derived stem cells, play an essential role in myogenesis and regeneration. Here, the transcriptional profile of SMSCs during proliferation and differentiation were constructed using the RNA-Seq method. A total of 1954 differentially expressed genes (DEGs) and 1092 differentially alternative splicing genes (DAGs) were identified including 1288 upregulated genes as well as 666 downregulated genes. GO and KEGG analyses showed that the DEGs and DAGs were enriched in the MAPK (mitogen-activated protein kinase) signaling pathway, the PI3K-Akt (phosphatidylinositol-tris-phosphate kinase 3/protein kinase B) signaling pathway, the Wnt signaling pathway, and the Ras signaling pathway. In total, 1479 alternative splice events (AS) were also identified during SMSC proliferation and differentiation. Among them, a unique AS event was the major per-mRNA splicing type, and SE was the predominant splicing pattern. Furthermore, transcription factors with AS were scanned during SMSC differentiation such as myocyte enhancer factor-2C (MEF2C) and the nuclear receptor subfamily 4 group A member 2 (NR4A2). Our results imply that MEF2C and NR4A2 can interact, and we speculate that NR4A2 and MEF2C might regulate the myogenesis of ovine SMSCs through interaction. Together, our study provides useful information on the transcriptional regulation of SMSCs during proliferation and differentiation at the transcriptional level, and provides a valuable resource for understanding the molecular mechanism of myogenesis and muscle development.

Abstract The identification of genome-wide selection signatures can provide insights on the mechanisms of natural and/or artificial selection and uncover genes related to biological functions and/or phenotypes. Tibetan sheep are an important livestock in Tibet, providing meat and wool for Tibetans who are renown for breeding livestock that adapt well to high altitudes. Using whole-genome sequences with an effective sequencing depth of 5×, we investigated the genomic diversity and structure and, identified selection signatures of White Tibetan, Oula and Poll Dorset sheep. We obtained 30,163,679 Single Nucleotide Polymorphisms (SNPs) and 5,388,372 indels benchmarked against the ovine Oar_v4.0 genome assembly. Next, using F ST, ZHp and XP-EHH approaches, we identified selection signatures spanning a set of candidate genes, including HIF1A, CAPN3, PRKAA1, RXFP2, TRHR and HOXA10 that are associated with pathways and GO categories putatively related to hypoxia responses, meat traits and disease resistance. Candidate genes and GO terms associated with coat color were also identified. Finally, quantification of blood physiological parameters, revealed higher levels of mean corpuscular hemoglobin measurement and mean corpuscular hemoglobin concentration in Tibetan sheep compared with Poll Dorset, suggesting a greater oxygen-carrying capacity in the Tibetan sheep and thus better adaptation to high-altitude hypoxia. In conclusion, this study provides a greater understanding of genome diversity and variations associated with adaptive and production traits in sheep.

Zhongwei goat is a unique Chinese native goat breed for excellent lamb fur. The pattern of flower spikes of the lamb fur was significantly reduced due to the reduction of the bending of the hair strands with growth. In order to explore the molecular mechanism underlying hair bending with growth, we performed the comprehensive analysis of transcriptome and proteome of skins from 45-days, 108-days and 365-days goat based on TMT-based quantitative proteomics and RNA-seq methods. In the three comparison groups, 356, 592 and 282 differentially expressed proteins (DEPs) were screened, respectively. KEGG pathway analysis indicated that DEPs were significantly enriched in a set of signaling pathways related to wool growth and bending, such as ECM-receptor interaction, PI3K-Akt signaling pathway, PPAR signaling pathway, protein digestion and absorption, and metabolic pathways. In addition, 20 DEPs abundance of goat skin at three development stages were examined by PRM method, which validated the reliability of proteomic data. Among them, KRT and collagen alpha family may play an important role in the development of goat hair follicle and wool bending. COL6A1, COL6A2, CRNN, TNC and LOC102178129 were identified as candidate genes based on combined analysis of transcriptome and proteome data and PRM quantification. Our results identify the differential expressed proteins as well as pathways related to the wool bending of Zhongwei goats and provide a theoretical basis for further revealing the molecular mechanism underlying wool bending of goats.

With climate change bound to affect food and feed production, emphasis will shift to resilient and adapted indigenous livestock to sustain animal production. However, indigenous livestock comprise several varieties, strains and ecotypes whose genomes are poorly characterized. Here, we investigated genomic variation in an African thin-tailed Desert Sheep sampled in Sudan, using 600K genotype data generated from 92 individuals representing five ecotypes. We included data from 18 fat-tailed and 45 thin-tailed sheep from China, to investigate shared ancestry and perform comparative genomic analysis. We observed a clear genomic differentiation between the African thin-tailed Desert Sheep and the Chinese thin-tailed and fat-tailed sheep, suggesting a broad genetic structure between the fat-tailed and thin-tailed sheep in general, and that at least two autosomal gene pools comprise the genome profile of the thin-tailed sheep. Further analysis detected two distinct genetic clusters in both the African thin-tailed Desert Sheep and the Chinese thin-tailed sheep, suggesting a fine-scale and complex genome architecture in thin-tailed sheep. Selection signature analysis suggested differences in adaptation, production, reproduction and morphology likely underly the fine-scale genetic structure in the African thin-tailed Desert Sheep. This may need to be considered in designing breeding programs and genome-wide association studies.

Abstract Background Despite decades of research, the horse domestication scenario in East Asia remains poorly understood. Results The study identified 16 haplogroups with fine-scale phylogenetic resolution using mitochondrial genomes of 317 horse samples. The time to the most recent common ancestor of the 16 haplogroups ranges from [0.8–3.1] thousand years ago (KYA) to [7.9–27.1] KYA. With combined analyses of the mitochondrial control region for 35 extant Przewalski’s horses, 3544 modern and 203 ancient horses across the world, researchers provide evidence for that East Asian prevalent haplogroups Q and R were indigenously domesticated or they were involved in numerous distinct genetic components from wild horses in the southern part of East Asia. These events of haplotypes Q and R occurred during 4.7 to 16.3 KYA and 2.1 to 11.5 KYA, respectively. The diffusion of preponderant European haplogroups L from west to East Asia is consistent with the external gene input. Furthermore, genetic differences were detected between northern East Asia and southern East Asia cohorts by Principal Component Analysis, Analysis of Molecular Variance test, the χ2 test and phylogeographic analyses. Conclusions All results suggest a complex picture of horse domestication, as well as geographic pattern in East Asia. Both local origin and external input occurred in East Asia horse populations. And besides, there are at least two different domestication or hybridization centers in East Asia.

Objective An experiment was conducted to evaluate genetic diversity of 26 Chinese indigenous goats by 30 microsatellite markers, and then to define conservation priorities to set up the protection programs according to the weight given to within- and between-breed genetic diversity. Methods Twenty-six representative populations of Chinese indigenous goats, 1,351 total, were sampled from different geographic regions of China. Within-breed genetic diversity and marker polymorphism were estimated calculating the mean number of alleles, observed heterozygosities, expected heterozygosities, fixation index, effective number of alleles and allelic richness. Conservation priorities were analyzed by statistical methods. Results A relatively high level of genetic diversity was found in twenty-four population; the exceptions were in the Daiyun and Fuqing goat populations. Within-breed kinship coefficient matrices identified seven highly inbred breeds which should be of concern. Of these, six breeds receive a negative contribution to heterozygosity when the method was based on proportional contribution to heterozygosity. Based on Weitzman or Piyasatian and Kinghorn methods, the breeds distant from others i.e. Inner Mongolia Cashmere goat, Chengdu Brown goat and Leizhou goat obtain a high ranking. Evidence from Caballero and Toro and Fabuel et al method prioritized Jining Gray goat, Liaoning Cashmere goat, and Inner Mongolia Cashmere goat, which agree with results from Kinship-based methods. Conclusion Conservation priorities were determined according to multiple methods. Our results suggest Inner Mongolia Cashmere goat (most methods), Jining Gray goat and Liaoning Cashmere goat (high contribution to heterozygosity and total diversity) should be prioritized based on most methods. Furthermore, Daiyun goat and Shannan White goat also should be prioritized based on consideration of effective population size. However, if one breed can continually survive under changing conditions, the straightforward approach would be to increase its utilization and attraction for production via mining breed germplasm characteristics.

Bactrian camels (Camelus bactrianus) are highly adapted to the desert and semi-desert environments of Asia and developed unique physiological adaptations to cold, heat, drought, and nutrient-poor conditions. These animals are an ideal model for studying desert adaptation. However, the transcriptome of different Bactrian camel tissues has not been profiled. This study performed a comprehensive transcriptome analysis of nine fetal and adult tissues. A total of 20,417 coding genes were identified, and 2.4 billion reads were generated. Gene expression and functional analyses revealed that approximately 50% of the identified genes were ubiquitously expressed, and one-third were tissue-elevated genes, which were enriched in pathways related to the biological functions of the corresponding tissue. Weighted gene co-expressed network analysis (WGCNA) identified four modules—fat metabolism, water balance, immunity, and digestion—and several hub genes, including APOA1, TMEM174, CXCL12, and MYL9. The analysis of differentially expressed genes (DEGs) between fetal and adult tissues revealed that downregulated genes were enriched in tissue development, whereas upregulated genes were enriched in biological function in adult camels. DEGs in the hump were enriched in immune-related pathways, suggesting that this tissue is involved in immunity. This study is the first to generate a transcriptome atlas of major tissues in Bactrian camels and explores the genes potentially involved in the adaptation to desert environments.

The Zhongwei goat is kept primarily for its beautiful white, curly pelt that appears when the kid is approximately 1 month old; however, this representative phenotype often changes to a less curly phenotype during postnatal development in a process that may be mediated by multiple molecular signals. DNA methylation plays important roles in mammalian cellular processes and is essential for the initiation of hair follicle (HF) development. Here, we sought to investigate the effects of genome-wide DNA methylation by combining expression profiles of the underlying curly fleece dynamics. Genome-wide DNA methylation maps and transcriptomes of skin tissues collected from 45- to 108-day-old goats were used for whole-genome bisulfite sequencing (WGBS) and RNA sequencing, respectively. Between the two developmental stages, 1,250 of 3,379 differentially methylated regions (DMRs) were annotated in differentially methylated genes (DMGs), and these regions were mainly related to intercellular communication and the cytoskeleton. Integrated analysis of the methylome and transcriptome data led to the identification of 14 overlapping genes that encode crucial factors for wool fiber development through epigenetic mechanisms. Furthermore, a functional study using human hair inner root sheath cells (HHIRSCs) revealed that, one of the overlapping genes, platelet-derived growth factor C (PDGFC) had a significant effect on the messenger RNA expression of several key HF-related genes that promote cell migration and proliferation. Our study presents an unprecedented analysis that was used to explore the enigma of fleece morphological changes by combining methylome maps and transcriptional expression, and these data revealed stage-specific epigenetic changes that potentially affect fiber development. Furthermore, our functional study highlights a possible role for the overlapping gene PDGFC in HF cell growth, which may be a predictable biomarker for fur goat selection.

Abstract Background Long intergenic noncoding RNAs (lincRNAs) have been recognized in recent years as key regulators of biological processes. However, lincRNAs in goat remain poorly characterized both across various tissues and during different developmental stages in goat (Capra hircus). Results We performed the genome-wide discovery of the lincRNAs in goat by combining the RNA-seq dataset that were generated from 28 cashmere goat skin samples and the 12 datasets of goat tissues downloaded from the NCBI database. We identified a total of 5546 potential lincRNA transcripts that overlapped 3641 lincRNA genes. These lincRNAs exhibited a tissue-specific pattern. Specifically, there are 584 lincRNAs expressed exclusively in only one tissue, and 91 were highly expressed in hair follicle (HF). In addition, 2350 protein-coding genes and 492 lincRNAs were differentially expressed in the skin of goat. The majority exhibited the remarkable differential expression during the transition of the goat skin from the May–June to August–October time point, which covered the different seasons. Fundamental biological processes, such as skin development, were significantly enriched in these genes. Furthermore, we identified several lincRNAs highly expressed in the HF, which exhibited not only the co-expression pattern with the key factors to the HF development but also the activated expression in the August to October time point. Intriguingly, one of spatiotemporal lincRNAs, linc-chig1598 could be a potential regulator of distal-less homeobox 3 expression during the secondary hair follicle growth. Conclusions This study will facilitate future studies aimed at unravelling the function of lincRNAs in hair follicle development.

Chinese Zhongwei goat is a rare and precious fur breed as its lamb fur is a well-known fur product. Wool bending of lamb fur of the Zhongwei goat is its most striking feature. However, the curvature of the wool decreases gradually with growth, which significantly affects its quality and economic value. The mechanism regulating the phenotypic changes of hair bending is still unclear. In the present study, the skin tissues of Zhongwei goats at 45 days (curving wool) and 108 days (slight-curving wool) after birth were taken as the research objects, and the expression profiling of long non-coding RNAs (lncRNAs) and mRNAs were analyzed based on the Ribo Zero RNA sequencing (RNA-seq) method. In total, 46,013 mRNAs and 13,549 lncRNAs were identified, of which 352 were differentially expressed mRNAs and 60 were. lncRNAs. Functional enrichment analysis of the target genes of lncRNAs were mainly enriched in PI3K-Akt, Arachidonic acid metabolic, cAMP, Wnt, and other signaling pathways. The qRT-PCR results of eight selected lncRNAs and target genes were consistent with the sequencing result, which indicated our data were reliable. Through the analysis of the weighted gene co-expression network, 13 co-expression modules were identified. The turquoise module contained a large number of differential expressed lncRNAs, which were mainly enriched in the PI3K-Akt signaling pathway and cAMP signaling pathway. The predicted LOC102172600 and LOC102191729 might affect the development of hair follicles and the curvature of wool by regulating the target genes. Our study provides novel insights into the potential roles of lncRNAs in the regulation of wool bending. In addition, the study offers a theoretical basis for further study of goat wool growth, so as to be a guidance and reference for breeding and improvement in the future.

Abstract Compared with the commercially available single nucleotide polymorphism (SNP) chip based on the Bead Chip technology, the solution hybrid selection (SHS)-based target enrichment SNP chip is not only design-flexible, but also cost-effective for genotype sequencing. In this study, we propose to design an animal SNP chip using the SHS-based target enrichment strategy for the first time. As an update to the international collaboration on goat research, a 66 K SNP chip for cashmere goat was created from the whole-genome sequencing data of 73 individuals. Verification of this 66 K SNP chip with the whole-genome sequencing data of 436 cashmere goats showed that the SNP call rates was between 95.3% and 99.8%. The average sequencing depth for target SNPs were 40X. The capture regions were shown to be 200 bp that flank target SNPs. This chip was further tested in a genome-wide association analysis of cashmere fineness (fiber diameter). Several top hit loci were found marginally associated with signaling pathways involved in hair growth. These results demonstrate that the 66 K SNP chip is a useful tool in the genomic analyses of cashmere goats. The successful chip design shows that the SHS-based target enrichment strategy could be applied to SNP chip design in other species.

Abstract Copy number variants (CNVs) represent a form of genomic structural variation underlying phenotypic diversity. In this study, we used the Illumina Ovine SNP 600 K BeadChip array for genome-wide detection of CNVs in 48 Chinese Tan sheep. A total of 1,296 CNV regions (CNVRs), ranging from 1.2 kb to 2.3 Mb in length, were detected, representing approximately 4.7% of the entire ovine genome (Oar_v3.1). We combined our findings with five existing CNVR reports to generate a composite genome-wide dataset of 4,321 CNVRs, which revealed 556 (43%) novel CNVRs. Subsequently, ten novel CNVRs were randomly chosen for further quantitative real-time PCR (qPCR) confirmation, and eight were successfully validated. Gene functional enrichment revealed that these CNVRs cluster into Gene Ontology (GO) categories of homeobox and embryonic skeletal system morphogenesis. One CNVR overlapping with the homeobox transcription factor DLX3 and previously shown to be associated with curly hair in sheep was identified as the candidate CNV for the special curly fleece phenotype in Tan sheep. We constructed a Chinese indigenous sheep genomic CNV map based on the Illumina Ovine SNP 600 K BeadChip array, providing an important addition to published sheep CNVs, which will be helpful for future investigations of the genomic structural variations underlying traits of interest in sheep.

Land surface temperature (LST) is a critical parameter of surface energy fluxes and has become the focus of numerous studies. LST downscaling is an effective technique for supplementing the limitations of the coarse-resolution LST data. However, the relationship between LST and other land surface parameters tends to be nonlinear and spatially nonstationary, due to spatial heterogeneity. Nonlinearity and spatial nonstationarity have not been considered simultaneously in previous studies. To address this issue, we propose a multi-factor geographically weighted machine learning (MFGWML) algorithm. MFGWML utilizes three excellent machine learning (ML) algorithms, namely extreme gradient boosting (XGBoost), multivariate adaptive regression splines (MARS), and Bayesian ridge regression (BRR), as base learners to capture the nonlinear relationships. MFGWML uses geographically weighted regression (GWR), which allows for spatial nonstationarity, to fuse the three base learners’ predictions. This paper downscales the 30 m LST data retrieved from Landsat 8 images to 10 m LST data mainly based on Sentinel-2A images. The results show that MFGWML outperforms two classic algorithms, namely thermal image sharpening (TsHARP) and the high-resolution urban thermal sharpener (HUTS). We conclude that MFGWML combines the advantages of multiple regression, ML, and GWR, to capture the local heterogeneity and obtain reliable and robust downscaled LST data.

The Tibetan cashmere goat is one of the main goat breeds used by people living in the plateau. It exhibits the distinct phenotypic characteristics observed in lowland goats, allowing them to adapt to the challenging conditions at high altitudes. It provides an ideal model for understanding the genetic mechanisms underlying high-altitude adaptation and hypoxia-related diseases. Our previous exome sequencing of five Chinese cashmere breeds revealed a candidate gene, DSG3 (Desmoglein 3), responsible for the high-altitude adaptation of the Tibetan goat. However, the whole DSG3 gene (44 kbp) consisting of 16 exons in the goat genome was not entirely covered by the exome sequencing. In this study, we resequenced all the 16 exons of the DSG3 gene in ten Chinese native goat populations. Twenty-seven SNP variants were found between the lowland and highland goat populations. The genetic distance (FST) of significant SNPs between the lowland and highland populations ranged from 0.42 to 0.58. By using correlation coefficient analysis, linkage disequilibrium, and haplotype network construction, we found three non-synonymous SNPs (R597E, T595I, and G572S) in exon 5 and two synonymous SNPs in exons 8 and 16 in DSG3. These mutations significantly segregated high- and low-altitude goats in two clusters, indicating the contribution of DSG3 to the high-altitude hypoxia adaptation in the Tibetan goat.

Land use and land cover (LULC) datasets for Beijing in 1978, 1987, 1992, 2000 and 2010 were developed from Landsat images using the object-oriented classification approach. The relationships between social-economic, demographic and political factors and time-series LULC data were examined for the periods between 1978 and 2010. The results showed the effectiveness of using the object-oriented decision tree classification method for LULC classification with time series of Landsat images. Combined with anthropogenic driving forces, our research can effectively explain the detailed LULC change trajectories corresponding to different stages and give new insights for Beijing LULC change patterns. The results show a significant increase in forest and built-up areas, but a decrease in arable lands, due to urbanization and reforestation. Large ecological projects result in an increase of forest areas and population, and economic conditions result in urban expansion. The anthropogenic driving forces analysis results further prove that both population increase and economic development played important roles in the expansion of built-up areas. Both the qualitative and quantitative anthropogenic driving forces analysis methods were helpful for better understanding the mechanisms of LULC change.

Linear spectral mixture analysis (SMA) is commonly used to infer fractional vegetation cover (FVC), especially for pixel dichotomy models. However, several sources of uncertainty including normalized difference vegetation index (NDVI) saturation and selection of endmembers inhibit the effectiveness of SMA for the estimation of FVC. In this study, Moderate-resolution Imaging Spectroradiometer (MODIS) and Landsat 8/Operational Land Imager (OLI) remote sensing data for the early growing season and in situ measurement of spectral reflectance are used to determine the value of endmembers including VIsoil and VIveg, with equally weighted RVI and NDVI measures used in combination to minimize the inherent biases in pure NDVI-based FVC. Their ability to improve estimates of grassland FVC is analyzed at different resolutions. These are shown to improve FVC estimates over NDVI-based SMA models using fixed values for the endmembers. Grassland FVC changes for Inner Mongolia, China from 2000 to 2013 are then monitored using the MODIS data. The results show that changes in most grassland areas are not significant, but in parts of Hulunbeier, south Tongliao, middle Xilin Gol and Erdos, grassland FVC has increased significantly.

Leaf chlorophyll content (LCC) provides valuable information about the nutrition and photosynthesis statuses of crops. Vegetation index-based methods have been widely used in crop management studies for the non-destructive estimation of LCC using remote sensing technology. However, many published vegetation indices are sensitive to crop canopy structure, especially the leaf area index (LAI), when crop canopy spectra are used. Herein, to address this issue, we propose four new spectral indices (The red-edge-chlorophyll absorption index (RECAI), the red-edge-chlorophyll absorption index/optimized soil-adjusted vegetation index (RECAI/OSAVI), the red-edge-chlorophyll absorption index/ the triangular vegetation index (RECAI/TVI), and the red-edge-chlorophyll absorption index/the modified triangular vegetation index(RECAI/MTVI2)) and evaluate their performance for LCC retrieval by comparing their results with those of eight published spectral indices that are commonly used to estimate LCC. A total of 456 winter wheat canopy spectral data corresponding to physiological parameters in a wide range of species, growth stages, stress treatments, and growing seasons were collected. Five regression models (linear, power, exponential, polynomial, and logarithmic) were built to estimate LCC in this study. The results indicated that the newly proposed integrated RECAI/TVI exhibited the highest LCC predictive accuracy among all indices, where R2 values increased by more than 13.09% and RMSE values reduced by more than 6.22%. While this index exhibited the best association with LCC (0.708** ≤ r ≤ 0.819**) among all indices, RECAI/TVI exhibited no significant relationship with LAI (0.029 ≤ r ≤ 0.167), making it largely insensitive to LAI changes. In terms of the effects of different field management measures, the LCC predictive accuracy by RECAI/TVI can be influenced by erective winter wheat varieties, low N fertilizer application density, no water application, and early sowing dates. In general, the newly developed integrated RECAI/TVI was sensitive to winter wheat LCC with a reduction in the influence of LAI. This index has strong potential for monitoring winter wheat nitrogen status and precision nitrogen management. However, further studies are required to test this index with more diverse datasets and different crops.

High altitude environments are of particular interest in the studies of local adaptation as well as their implications in physiology and clinical medicine in human. Some Chinese pig breeds, such as Tibetan pig (TBP) that is well adapted to the high altitude and Dahe pig (DHP) that dwells at the moderate altitude, provide ideal materials to study local adaptation to altitudes. Yet, it is still short of in-depth analysis and understanding of the genetic adaptation to high altitude in the two pig populations. In this study we conducted a genomic scan for selective sweeps using FST to identify genes showing evidence of local adaptations in TBP and DHP, with Wuzhishan pig (WZSP) as the low-altitude reference. Totally, we identified 12 specific selective genes (CCBE1, F2RL1, AGGF1, ZFPM2, IL2, FGF5, PLA2G4A, ADAMTS9, NRBF2, JMJD1C, VEGFC and ADAM19) for TBP and six (OGG1, FOXM, FLT3, RTEL1, CRELD1 and RHOG) for DHP. In addition, six selective genes (VPS13A, GNA14, GDAP1, PARP8, FGF10 and ADAMTS16) were shared by the two pig breeds. Among these selective genes, three (VEGFC, FGF10 and ADAMTS9) were previously reported to be linked to the local adaptation to high altitudes in pigs, while many others were newly identified by this study. Further bioinformatics analysis demonstrated that majority of these selective signatures have some biological functions relevant to the altitude adaptation, for examples, response to hypoxia, development of blood vessels, DNA repair and several hematological involvements. These results suggest that the local adaptation to high altitude environments is sophisticated, involving numerous genes and multiple biological processes, and the shared selective signatures by the two pig breeds may provide an effective avenue to identify the common adaptive mechanisms to different altitudes.

Remote sensing provides a consistent form of observation for biodiversity monitoring across space and time. However, the regional mapping of forest species diversity is still difficult because of the complexity of species distribution and overlapping tree crowns. A new method called “spectranomics” that maps forest species richness based on leaf chemical and spectroscopic traits using imaging spectroscopy was developed by Asner and Martin. In this paper, we use this method to detect the relationships among the spectral, biochemical and taxonomic diversity of tree species, based on 20 dominant canopy species collected in a subtropical forest study site in China. Eight biochemical components (chlorophyll, carotenoid, specific leaf area, equivalent water thickness, nitrogen, phosphorus, cellulose and lignin) are quantified by spectral signatures (R2 = 0.57–0.85, p < 0.01). We also find that the simulated maximum species number based on the eight optimal biochemical components is approximately 15, which is suitable for most 30 m × 30 m forest sites within this study area. This research may support future work on regional species diversity mapping using airborne imaging spectroscopy.