The mosquito Aedes aegypti is the primary vector of many human arboviruses such as dengue, yellow fever, chikungunya, and Zika, which affect millions of people worldwide. Population genetic studies on this mosquito have been important in understanding its invasion pathways and success as a vector of human disease. The Axiom aegypti1 SNP chip was developed from a sample of geographically diverse A. aegypti populations to facilitate genomic studies on this species. We evaluate the utility of the Axiom aegypti1 SNP chip for population genetics and compare it with a low-depth shotgun sequencing approach using mosquitoes from the native (Africa) and invasive ranges (outside Africa). These analyses indicate that results from the SNP chip are highly reproducible and have a higher sensitivity to capture alternative alleles than a low-coverage whole-genome sequencing approach. Although the SNP chip suffers from ascertainment bias, results from population structure, ancestry, demographic, and phylogenetic analyses using the SNP chip were congruent with those derived from low-coverage whole-genome sequencing, and consistent with previous reports on Africa and outside Africa populations using microsatellites. More importantly, we identified a subset of SNPs that can be reliably used to generate merged databases, opening the door to combined analyses. We conclude that the Axiom aegypti1 SNP chip is a convenient, more accurate, low-cost alternative to low-depth whole-genome sequencing for population genetic studies of A. aegypti that do not rely on full allelic frequency spectra. Whole-genome sequencing and SNP chip data can be easily merged, extending the usefulness of both approaches.

BACKGROUND: Although whole-genome sequencing (WGS) is the preferred genotyping method for most genomic analyses, limitations are often experienced when studying genomes characterized by a high percentage of repetitive elements, high linkage, and recombination deserts. The Asian tiger mosquito (Aedes albopictus), for example, has a genome comprising up to 72% repetitive elements, and therefore we set out to develop a single-nucleotide polymorphism (SNP) chip to be more cost-effective. Aedes albopictus is an invasive species originating from Southeast Asia that has recently spread around the world and is a vector for many human diseases. Developing an accessible genotyping platform is essential in advancing biological control methods and understanding the population dynamics of this pest species, with significant implications for public health.
METHODS: We designed a SNP chip for Ae. albopictus (Aealbo chip) based on approximately 2.7 million SNPs identified using WGS data from 819 worldwide samples. We validated the chip using laboratory single-pair crosses, comparing technical replicates, and comparing genotypes of samples genotyped by WGS and the SNP chip. We then used the chip for a population genomic analysis of 237 samples from 28 sites in the native range to evaluate its usefulness in describing patterns of genomic variation and tracing the origins of invasions.
RESULTS: Probes on the Aealbo chip targeted 175,396 SNPs in coding and non-coding regions across all three chromosomes, with a density of 102 SNPs per 1 Mb window, and at least one SNP in each of the 17,461 protein-coding genes. Overall, 70% of the probes captured the genetic variation. Segregation analysis found that 98% of the SNPs followed expectations of single-copy Mendelian genes. Comparisons with WGS indicated that sites with genotype disagreements were mostly heterozygotes at loci with WGS read depth < 20, while there was near complete agreement with WGS read depths > 20, indicating that the chip more accurately detects heterozygotes than low-coverage WGS. Sample sizes did not affect the accuracy of the SNP chip genotype calls. Ancestry analyses identified four to five genetic clusters in the native range with various levels of admixture.
CONCLUSIONS: The Aealbo chip is highly accurate, is concordant with genotypes from WGS with high sequence coverage, and may be more accurate than low-coverage WGS.

As an important genotyping platform, SNP chips are essential for implementing genomic selection. In this article, we introduced the development of a liquid SNP chip panel for dairy goats. This panel contains 54,188 SNPs based on genotyping by targeted sequencing (GBTS) technology. The source of SNPs in the panel were from the whole-genome resequencing of 110 dairy goats from three European and two Chinese indigenous dairy goat breeds. The performance of this liquid SNP chip panel was evaluated by genotyping 200 additional goats. Fifteen of them were randomly selected for whole-genome resequencing. The average capture ratio of the panel design loci was 98.41%, and the genotype concordance with resequencing reached 98.02%. We further used this chip panel to conduct genome-wide association studies (GWAS) to detect genetic loci that affect coat color in dairy goats. A single significant association signal for hair color was found on chromosome 8 at 31.52-35.02 Mb. The TYRP1 gene, which is associated with coat color in goats, was identified to be located at this genomic region (chromosome 8: 31,500,048-31,519,064). The emergence of high-precision and low-cost liquid microarrays will improve the analysis of genomics and breeding efficiency of dairy goats.

Chinese Red Steppe Cattle (CRS), a composite cattle breed, is well known for its milk production, high slaughter rate, carcass traits, and meat quality. Nowadays, it is widely bred in Jilin and Hebei Province and the Inner Mongolia Autonomous region. However, the population structure and the genetic basis of prominent characteristics of CRS are still unknown. In this study, we systematically describe their population structure, genetic diversity, and selection signature based on genotyping data from 61 CRS individuals with GGP Bovine 100 K chip. The results showed that CRS cattle had low inbreeding levels and had formed a unique genetic structure feature. Using two complementary methods (including comprehensive haplotype score and complex likelihood ratio), we identified 1291 and 1285 potentially selected genes, respectively. There were 141 genes annotated in common 106 overlapping genomic regions covered 5.62 Mb, including PLAG1, PRKG2, DGAT1, PARP10, TONSL, ADCK5, and BMP3, most of which were enriched in pathways related to muscle growth and differentiation, milk production, and lipid metabolism. This study will contribute to understanding the genetic mechanism behind artificial selection and give an extensive reference for subsequent breeding.

Blue mussels from the genus Mytilus are an abundant component of the benthic community, found in the high latitude habitats. These foundation species are relevant to the aquaculture industry, with over 2 million tonnes produced globally each year. Mussels withstand a wide range of environmental conditions and species from the Mytilus edulis complex readily hybridize in regions where their distributions overlap. Significant effort has been made to investigate the consequences of environmental stress on mussel physiology, reproductive isolation, and local adaptation. Yet our understanding on the genomic mechanisms underlying such processes remains limited. In this study, we developed a multi species medium-density 60 K SNP-array including four species of the Mytilus genus. SNPs included in the platform were called from 138 mussels from 23 globally distributed mussel populations, sequenced using a whole-genome low coverage approach. The array contains polymorphic SNPs which capture the genetic diversity present in mussel populations thriving across a gradient of environmental conditions (~59 K SNPs) and a set of published and validated SNPs informative for species identification and for diagnosis of transmissible cancer (610 SNPs). The array will allow the consistent genotyping of individuals, facilitating the investigation of ecological and evolutionary processes in these taxa. The applications of this array extend to shellfish aquaculture, contributing to the optimization of this industry via genomic selection of blue mussels, parentage assignment, inbreeding assessment and traceability. Further applications such as genome wide association studies (GWAS) for key production traits and those related to environmental resilience are especially relevant to safeguard aquaculture production under climate change.

Understanding the genetic basis of native cattle populations that have adapted to the local environment is of great significance for formulating appropriate strategies and programs for genetic improvement and protection. Therefore, it is necessary to understand the genetic diversity and population structure of Altay white-headed cattle so as to meet the current production needs under various environments, carry out continuous genetic improvement, and promote rapid adaptation to changing environments and breeding objectives. A total of 46 individual samples of endangered Xinjiang Altay white-headed cattle were collected in this study, including nine bulls and 37 cows. To collect genotype data, 100 k SNP markers were used, and then studies of genetic diversity, genetic structure, inbreeding degree, and family analysis were carried out. A total of 101,220 SNP loci were detected, and the genotype detection rate for individuals was ≥90%. There were 85,993 SNP loci that passed quality control, of which 93.5% were polymorphic. The average effective allele number was 0.036, the Polymorphism Information Content was 0.304 and the minimum allele frequency was 0.309, the average observed heterozygosity was 0.413, and the average expected heterozygosity was 0.403. The average genetic distance of Idengtical By State (IBS) was 0.3090, there were 461 ROH (genome-length homozygous fragments), 76.1% of which were between 1 and 5 MB in length, and the average inbreeding coefficient was 0.016. The 46 Altay white-headed cattle were divided into their families, and the individual numbers of each family were obviously different. To sum up, the Altay white-headed cattle conservation population had low heterozygosity, a high inbreeding degree, few families, and large differences in the number of individuals in each family, which can easily cause a loss of genetic diversity. In the follow-up seed conservation process, seed selection and matching should be carried out according to the divided families to ensure the long-term protection of Altay white-headed cattle genetic resources.

Tongcheng (TC) pigs, distinguished by their superior meat quality, are a Chinese indigenous pig breed. Recently, the genetic resources of TC pigs are under tremendous threat due to the introduction of cosmopolitan pig breeds and African swine fever disease. To promote their management and conservation, the present study assessed genetic diversity and population structure of TC pigs using single nucleotide polymorphism (SNP) markers. A total of 26, 999 SNPs were screened from 51, 315 SNPs in 68 TC pigs. The multi-dimensional scaling (MDS) analysis and neighbor-joining tree revealed that all 68 pigs were from a purebred population. The effective population size decreased over time, and it was 96 prior to generation 20. Both linkage disequilibrium (LD) and neutrality test indicated a low selection of TC pigs with average LD value of 0.15 ± 0.23. Genetic diversity results exhibited a minor allele frequency (MAF) of 0.23, observed heterozygosity (HO) of 0.32, expected heterozygosity (He) of 0.31, and nucleotide diversity (Pi) of 0.31. All these parameters indicated a remarkably high genetic diversity of TC pigs. Additionally, 184 runs of homozygosity (ROH) segments were detected from the whole genome of TC pigs with an average ROH length of 23.71Mb, ranging from 11.26Mb to 69.02 Mb. The highest ROH coverage was found on chromosome 1 (10.12%), while the lowest was on chromosome 18 (1.49%). The average inbreeding coefficients based on ROH (FROH) was 0.04%. Fourteen ROH islands containing 240 genes were detected on 9 different autosomes. Some of these 240 genes were overlapped with the genes related to biological processes such as immune function, reproduction, muscular development, and fat deposition, including FFAR2, FFAR4, MAPK8, NPY5R, KISS1, and these genes might be associated with such traits as meat quality and disease resistance in TC pigs. Taken together, population structure and genetic diversity results suggested that the TC pig represented a valuable genetic resource. However, TC pig breed conservation program remains to be further optimized to ensure adequate genetic diversity and avoid inbreeding depression. Our findings provide theoretical basis for formulating management and conservation strategies for TC pigs.

Genotype imputation is the term used to describe the process of inferring unobserved genotypes in a sample of individuals. It is a key step prior to a genome-wide association study (GWAS) or genomic prediction. The imputation accuracy will directly influence the results from subsequent analyses. In this simulation-based study, we investigate the accuracy of genotype imputation in relation to some factors characterizing SNP chip or low-coverage whole-genome sequencing (LCWGS) data. The factors included the imputation reference population size, the proportion of target markers /SNP density, the genetic relationship (distance) between the target population and the reference population, and the imputation method. Simulations of genotypes were based on coalescence theory accounting for the demographic history of pigs. A population of simulated founders diverged to produce four separate but related populations of descendants. The genomic data of 20,000 individuals were simulated for a 10-Mb chromosome fragment. Our results showed that the proportion of target markers or SNP density was the most critical factor affecting imputation accuracy under all imputation situations. Compared with Minimac4, Beagle5.1 reproduced higher-accuracy imputed data in most cases, more notably when imputing from the LCWGS data. Compared with SNP chip data, LCWGS provided more accurate genotype imputation. Our findings provided a relatively comprehensive insight into the accuracy of genotype imputation in a realistic population of domestic animals.

Chlorophyll is the most important pigment for plant photosynthesis that plays an important role in crop growth and production. In this study, the chlorophyll content trait was explored to improve sugarcane yield. Two hundred and eighty-five F1 progenies from the cross YT93-159 × ROC22 with significantly different chlorophyll contents were included as test materials. The chlorophyll content of the +1 leaves during elongation phase was measured using a SPAD-502 meter through a three-crop cycle (plant cane, first ratoon, and second ratoon). Linkage analysis was conducted on a high-density genetic map constructed based on the sugarcane 100K SNP chip. In addition, Fv/Fm, plant height, stalk diameter, brix data were collected on plant cane during the elongation and maturation phases. The results showed that the +1 leaf SPAD values, which can be used as an important reference to evaluate the growth potential of sugarcane, were significantly and positively correlated with the Fv/Fm during elongation phase, as well as with plant height, stalk diameter, and brix during maturity phase (P < 0.01). The broad sense heritability (H 2) of the chlorophyll content trait was 0.66 for plant cane crop, 0.67 for first ratoon crop, and 0.73 for second ratoon crop, respectively, indicating that this trait was mainly controlled by genetic factors. Thirty-one quantitative trait loci (QTL) were detected by QTL mapping. Among them, a major QTL, qCC-R1, could account for 12.95% of phenotypic variation explained (PVE), and the other 30 minor QTLs explained 2.37-7.99% PVE. Twenty candidate genes related to chlorophyll content were identified in the QTLs plus a 200-Kb extension region within either sides, of which four were homologous genes involved in the chlorophyll synthesis process and the remaining 16 played a certain role in chlorophyll catabolic pathway, chloroplast organization, or photosynthesis. These results provide a theoretical reference for analyzing the genetic mechanism of chlorophyll synthesis and subsequent improvement of photosynthetic characteristics in sugarcane.

Brassica napus L. is a vital oil crop in China. As auxiliary tools for rapeseed breeding, transgenic technologies play a considerable role in heterosis, variety improvement, and pest resistance. Research on transgenic detection technologies is of great significance for the introduction, supervision, and development of transgenic rapeseed in China. However, the transgenic detection methods currently in use are complex and time-consuming, with low output. A single nucleotide polymorphism (SNP) chip can effectively overcome such limitations. In the present study, we collected 40 transgenic elements and designed 291 probes. The probe sequences were submitted to Illumina Company, and the Infinium chip technology was used to prepare SNP chips. In the present Brassica napus transgenic detection experiment, 84 high-quality probes of 17 transgenic elements were preliminarily screened, and genotyping effect was optimised for the probe signal value. Ultimately, a transgenic detection system for B. napus was developed. The developed system has the advantages of simple operation, minimal technical errors, and stable detection outcomes. A transgenic detection sensitivity test revealed that the probe designed could accurately detect 1% of transgenic samples and had high detection sensitivity. In addition, in repeatability tests, the CaMV35S promoter coefficient of variation was approximately 3.58%. Therefore, the SNP chip had suitable repeatability in transgene detection. The SNP chip developed could be used to construct transgenic detection systems for B. napus.
BACKGROUND: The online version contains supplementary material available at 10.1007/s13205-021-03062-6.