High-density Single Nucleotide Polymorphism Research Articles

Genomic loci associated with grain yield under well-watered and water-stressed conditions in multiple bi-parental maize populations

Smallholder maize farming systems in sub-Saharan Africa (SSA) are vulnerable to drought-induced yield losses, which significantly impact food security and livelihoods within these communities. Mapping and characterizing genomic regions associated with water stress tolerance in tropical maize is essential for future breeding initiatives targeting this region. In this study, three biparental F3 populations composed of 753 families were evaluated in Kenya and Zimbabwe and genotyped with high-density single nucleotide polymorphism (SNP) markers. Quantitative trait loci maping was performed on these genotypes to dissect the genetic architecture for grain yield (GY), plant height (PH), ear height (EH) and anthesis-silking interval (ASI) under well-watered (WW) and water-stressed (WS) conditions. Across the studied maize populations, mean GY exhibited a range of 4.55–8.55 t/ha under WW and 1.29–5.59 t/ha under WS, reflecting a 31–59% reduction range under WS conditions. Genotypic and genotype-by-environment (G × E) variances were significant for all traits except ASI. Overall broad sense heritabilities for GY were low to high (0.25–0.60). For GY, these genetic parameters were decreased under WS conditions. Linkage mapping revealed a significant difference in the number of QTLs detected, with 93 identified under WW conditions and 41 under WS conditions. These QTLs were distributed across all maize chromosomes. For GY, eight and two major effect QTLs (>10% phenotypic variation explained) were detected under WW and WS conditions, respectively. Under WS conditions, Joint Linkage Association Mapping (JLAM) identified several QTLs with minor effects for GY and revealed genomic region overlaps in the studied populations. Across the studied water regimes, five-fold cross-validation showed moderate to high prediction accuracies (−0.15–0.90) for GY and other agronomic traits. Our findings demonstrate the polygenic nature of WS tolerance and highlights the immense potential of using genomic selection in improving genetic gain in maize breeding.

Natural selection on feralization genes contributed to the invasive spread of wild pigs throughout the United States.

Despite a long presence in the contiguous United States (US), the distribution of invasive wild pigs (Sus scrofa × domesticus) has expanded rapidly since the 1980s, suggesting a more recent evolutionary shift towards greater invasiveness. Contemporary populations of wild pigs represent exoferal hybrid descendants of domestic pigs and European wild boar, with such hybridization expected to enrich genetic diversity and increase the adaptive potential of populations. Our objective was to characterize how genetic enrichment through hybridization increases the invasiveness of populations by identifying signals of selection and the ancestral origins of selected loci. Our study focused on invasive wild pigs within Great Smoky Mountains National Park, which represents a hybrid population descendent from the admixture of established populations of feral pigs and an introduction of European wild boar to North America. Accordingly, we genotyped 881 wild pigs with multiple high-density single-nucleotide polymorphism (SNP) arrays. We found 233 markers under putative selection spread over 79 regions across 16 out of 18 autosomes, which contained genes involved in traits affecting feralization. Among these, genes were found to be related to skull formation and neurogenesis, with two genes, TYRP1 and TYR, also encoding for crucial melanogenesis enzymes. The most common haplotypes associated with regions under selection for the Great Smoky Mountains population were also common among other populations throughout the region, indicating a key role of putatively selective variants in the fitness of invasive populations. Interestingly, many of these haplotypes were absent among European wild boar reference genotypes, indicating feralization through genetic adaptation.

Genetic diversity and population structure of four Anatolian sheep revealed by genome-wide ddRADseq data

This is the first wide-scale study to reveal next-generation sequencing-based and comprehensive study to reveal genetic diversity, population structure, and phylogenetic relationships of some of Türkiye's indigenous fat-tailed sheep breeds. A total of 80 animals belonging to Akkaraman (AKR), Güney Karaman (GKR), Morkaraman (MKR), and Karakaş (KRK) sheep breeds were genotyped with genome-wide of 296.097 single nucleotide polymorphisms (SNPs) data recovered from double digest restriction site-associated DNA sequencing (ddRADseq) libraries processed by Illumina HiSeq X Ten instrument. Minor allele frequency (MAF) ranged from 0.311 (MKR) to 0.316 (AKR and GKR). Observed heterozygosity (HO) values were higher than expected values (HE) across all populations with a mean of 0.307. Negative inbreeding coefficient (FIS) values were observed in four sheep populations varying between −0.034 (AKR) to −0.060 (MKR). Cross-entropy criterion-based ADMIXTURE analysis demonstrated that four Anatolian sheep breeds were represented by two ancestral populations in which GKR and AKR were distinct, while KRK and MKR were mixed populations. Genetic distance-based tree, discriminant analysis of principal components (DAPC), and ADMIXTURE analyses confirmed that GKR, which is believed to be derived from the AKR breed, has become genetically different from other sheep populations. Moreover, no migration from and into the GKR breed was detected, while a migration edge was drawn from the KRK and MKR clade into the AKR breed by the TreeMix algorithm. This study confirmed that high-density SNP data obtained from advanced next-generation sequencing (NGS) platforms are efficient in genetically distinguishing animal breeds, even varieties. It is recommended that further NGS-based studies could be carried out to better characterize different indigenous livestock populations raised in Türkiye.

Genetic history of esophageal cancer group in southwestern China revealed by Y‐chromosome STRs and genomic evolutionary connection analysis

Genetic and environmental factors play crucial roles in the development of esophageal cancer (EC) and contribute uniquely or cooperatively to human cancer susceptibility. Sichuan is located in the interior of southwestern China, and the northern part of Sichuan is one of the regions with a high occurrence of EC. However, the factors influencing the high incidence rate of EC in the Sichuan Han Chinese population and its corresponding genetic background and origins are still poorly understood. Here, we utilized genome-wide single nucleotide polymorphisms (SNPs) and Y-chromosome short tandem repeats (Y-STRs) to characterize the genetic structure, connection, and origin of cancer groups and general populations. We generated Y-STR-based haplotype data from 214 Sichuan individuals, including the Han Chinese EC population and a control group of Han Chinese individuals. Our results, obtained from Y-STR-based population statistical methods (analysis of molecular variance (AMOVA), principal component analysis (PCA), and phylogenetic analysis), demonstrated that there was a genetic substructure difference between the EC population in the high-incidence area of northern Sichuan Province and the control population. Additionally, there was a strong genetic relationship between the EC population in the northern Sichuan high-incidence area and those at high risk in both the Fujian and Chaoshan areas. In addition, we obtained high-density SNP data from saliva samples of 60 healthy Han Chinese individuals from three high-prevalence areas of EC in China: Sichuan Nanchong, Fujian Quanzhou, and Henan Xinxiang. As inferred from the allele frequency of SNPs and sharing patterns of haplotype segments, the evolutionary history and admixture events suggested that the Han population from Nanchong in northern Sichuan Province shared a close genetic relationship with the Han populations from Xinxiang in Henan Province and Quanzhou in Fujian Province, both of which are regions with a high prevalence of EC. Our study illuminated the genetic profile and connection of the Northern Sichuan Han population and enriched the genomic resources and features of the Han Chinese populations in China, especially for the Y-STR genetic data of the Han Chinese EC population. Populations living in different regions with high incidences of EC may share similar genetic backgrounds, which offers new insights for further exploring the genetic mechanisms underlying EC.

Comprehensive analysis of runs of homozygosity and heterozygosity in Holstein cattle on the basis of medium and high density SNP panels and large population sample

Abstract This study reports runs of homozygosity (ROH) and heterozygosity (ROHet) distributed in a large population of Holstein cattle on the basis of two microarrays of medium (50k; 2163 animals; 54 609 SNPs) and high single nucleotide polymorphism (SNP) density (HD; 600 animals; 777 692 SNPs). To assess the inbreeding values of Holstein cattle, the ROH-based genomic inbreeding coefficient (FROH) was calculated. The comparison of SNP panels suggested that FROH values above 4 Mb should be considered for panels of medium densities as a relatively reliable measure of inbreeding. Moreover, ROH hotspots and coldspots were identified and compared between the HD and 50k SNP panels and were carefully examined for association with production and functional traits. The obtained results pinpointed genomic regions presumably under selection pressure in Holstein cattle. The regions overlapped with a large number of genes, including GHR, GBF1, SUMF1, CCL28, NIM1K, U6, BTRC and FABP1, many of which are involved in important Holstein cattle characteristics. We also found that some ROH hotspots and coldspots identified with the HD panel were not detected with the 50k panel, mainly because of insufficient SNP density in certain genomic regions. This suggests that using medium-density panels might not be the best choice when precise identification of ROH patterns is the main goal. In summary, in this work, we confirmed that a high-density SNP panel compared to a medium-density SNP panel allows for more precise identification of ROH patterns, especially in the case of short ROH that could be associated with ancestral inbreeding.

The genetic basis of dispersal in a vertebrate metapopulation.

Dispersal affects evolutionary processes by changing population size and genetic composition, influencing the viability and persistence of populations. Investigating which mechanisms underlie variation in dispersal phenotypes and whether populations harbour adaptive potential for dispersal is crucial to understanding the eco-evolutionary dynamics of this important trait. Here, we investigate the genetic architecture of dispersal among successfully recruited individuals in an insular metapopulation of house sparrows. We use an extensive long-term individual-based ecological data set and high-density single-nucleotide polymorphism (SNP) genotypes for over 2500 individuals. We conducted a genome-wide association study (GWAS), and found a relationship between dispersal probability and a SNP located near genes known to regulate circadian rhythm, glycogenesis and exercise performance, among other functions. However, this SNP only explained 3.8% of variance, suggesting that dispersal is a polygenic trait. We then used an animal model to estimate heritable genetic variation (σA 2 ), which composes 10% of the total variation in dispersal probability. Finally, we investigated differences in σA 2 across populations occupying ecologically relevant habitat types (farm vs. non-farm) using a genetic groups animal model. We found different adaptive potentials across habitats, with higher mean breeding value, σA 2 , and heritability for the habitat presenting lower dispersal rates, suggesting also different roles of environmental variation. Our results suggest a complex genetic architecture of dispersal and demonstrate that adaptive potential may be environment dependent in key eco-evolutionary traits. The eco-evolutionary implications of such environment dependence and consequent spatial variation are likely to become ever more important with the increased fragmentation and loss of suitable habitats for many natural populations.

Identification of new major histocompatibility complex-B Haplotypes in Bangladesh native chickens.

The major histocompatibility complex in chicken demonstrates a great range of variations within varities, breeds, populations and that can eventually influence their immuneresponses. The preset study was conducted to understand the major histocompatibility complex-B (MHC-B) variability in five major populations of Bangladesh native chicken: Aseel, Hilly, Junglefowl, Non-descript Deshi, and Naked Neck. These five major populations of Bangladesh native chicken were analyzed with a subset of 89 single nucleotide polymorphisms (SNPs) in the high-density MHC-B SNP panel and Kompetitive Allele-Specific polymerase chain reaction genotyping was applied. To explore haplotype diversity within these populations, the results were analyzed both manually and computationally using PHASE 2.1 program. The phylogenetic investigations were also performed using MrBayes program. A total of 136 unique haplotypes were identified within these five Bangladesh chicken populations, and only one was shared (between Hilly and Naked Neck). Phylogenetic analysis showed no distinct haplotype clustering among the five populations, although they were shared in distinct clades; notably, the first clade lacked Naked Neck haplotypes. The present study discovered a set of unique MHC-B haplotypes in Bangladesh chickens that could possibly cause varied immune reponses. However, further investigations are required to evaluate their relationships with global chicken populations.

Genome-wide detection of positive and balancing signatures of selection shared by four domesticated rainbow trout populations (Oncorhynchus mykiss).

Evolutionary processes leave footprints along the genome over time. Highly homozygous regions may correspond to positive selection of favorable alleles, while maintenance of heterozygous regions may be due to balancing selection phenomena. We analyzed data from 176 fish from four disconnected domestic rainbow trout populations that were genotyped using a high-density Axiom Trout genotyping 665K single nucleotide polymorphism array, including 20 from the US and 156 from three French lines. Using methods based on runs of homozygosity and extended haplotype homozygosity, we detected signatures of selection in these four populations. Nine genomic regions that included 253 genes were identified as being under positive selection in all four populations Most were located on chromosome 2 but also on chromosomes 12, 15, 16, and 20. In addition, four heterozygous regions that contain 29 genes that are putatively under balancing selection were also shared by the four populations. These were located on chromosomes 10, 13, and 19. Regardless of the homozygous or heterozygous nature of the regions, in each region, we detected several genes that are highly conserved among vertebrates due to their critical roles in cellular and nuclear organization, embryonic development, or immunity. We identified new candidate genes involved in rainbow trout fitness, as well as 17 genes that were previously identified to be under positive selection, 10 of which in other fishes (auts2, atp1b3, zp4, znf135, igf-1α, brd2, col9a2, mrap2, pbx1, and emilin-3). Using material from disconnected populations of different origins allowed us to draw a genome-wide map of signatures of positive selection that are shared between these rainbow trout populations, and to identify several regions that are putatively under balancing selection. These results provide a valuable resource for future investigations of the dynamics of genetic diversity and genome evolution during domestication.

Development and evaluation of a haplotype reference panel of Zhikong scallop (Chlamys farreri) for genotype imputation

Single nucleotide polymorphisms (SNPs) across the genome are remarkably useful resources for investigating the genome architecture, studying the genetic basis of complex traits and implementation of genomic selection. However, information on high-density SNPs is unavailable for most aquaculture species owing to the high costs of whole genome sequencing. Genotype imputation is an attractive approach for obtaining large number of genomic variants at a low cost. In this study, the first haplotype reference panel was constructed for Chlamys farreri, an economically important mollusk species and a major contributor to aquaculture in China. A total of 174 scallops from six populations in the main scallop culture area were selected for whole-genome resequencing. More than 87.47 million SNPs were identified and 3,968,417 SNPs genome-wide were selected for constructing the haplotype reference panel for C. farreri. The number of SNPs per chromosome ranged from 125,000 to 279,981 with an average spacing of 242 bases. Several factors were evaluated based on the imputation performance of the reference panel. The imputation accuracies of 19 chromosomes ranged from 0.91 to 0.95, and there were no significant differences among them (p > 0.05). The imputation accuracies of populations could reach 0.95, 0.93, and 0.90 for ZY, PR, and CS respectively, which confirmed a positive relationship between the kinship within the population and the imputation accuracy. The imputation accuracies increased with sequencing depth and plateaued at 0.5×, reaching accuracies of 0.91–0.93 for artificially breeding populations. Taken together, we constructed a haplotype reference panel for C. farreri, which can provide a cost-effective way to extend the limited number of genotypes for boosting the power of downstream analyses such as genome-wide association studies and genomic selection.

Construction of a high-density genetic map and mapping of a spike length locus for rye.

Genetic maps provide the foundation for QTL mapping of important traits of crops. As a valuable food and forage crop, rye (Secale cereale L., RR) is also one of the tertiary gene sources of wheat, especially wild rye, Secale cereale subsp. segetale, possessing remarkable stress tolerance, tillering capacity and numerous valuable traits. In this study, based on the technique of specific-locus amplified fragment sequencing (SLAF-seq), a high-density single nucleotide polymorphism (SNP) linkage map of the cross-pollinated (CP) hybrid population crossed by S. cereale L (female parent) and S. cereale subsp. segetale (male parent) was successfully constructed. Following preprocessing, the number of 1035.11 M reads were collected and 2425800 SNP were obtained, of which 409134 SNP were polymorphic. According to the screening process, 9811 SNP markers suitable for constructing linkage groups (LGs) were selected. Subsequently, all of the markers with MLOD values lower than 3 were filtered out. Finally, an integrated map was constructed with 4443 markers, including 1931 female mapping markers and 3006 male mapping markers. A major quantitative trait locus (QTL) linked with spike length (SL) was discovered at 73.882 cM on LG4, which explained 25.29% of phenotypic variation. Meanwhile two candidate genes for SL, ScWN4R01G329300 and ScWN4R01G329600, were detected. This research presents the first high-quality genetic map of rye, providing a substantial number of SNP marker loci that can be applied to marker-assisted breeding. Additionally, the finding could help to use SLAF marker mapping to identify certain QTL contributing to important agronomic traits. The QTL and the candidate genes identified through the high-density genetic map above may provide diverse potential gene resources for the genetic improvement of rye.

Application of a High-Density Single Nucleotide Polymorphism Genetic Map in Mapping Quantitative Trait Loci of Early-Maturing Traits in Upland Cotton

(1) Background: Mapping QTLs for early-maturing traits is necessary for the development of early-maturing variety breeding. (2) Methods: In this research, a high-density genetic map (HDGM) was constructed using an F2 population with 100 individuals and single nucleotide polymorphism markers (SNPs) developed using the genotyping-by-sequencing (GBS) method. (3) Results: The HDGM, which covered a total distance of 3167.14 cM, harbored 5454 SNPs with an average marker interval of 0.58 cM. In total, 18 QTLs for four early-maturing characters were detected and explained 11.6–46.4% of phenotypic variation (PV). Two QTLs of the whole growing period (WGP) and height of the node of the first fruiting branch (HNFFB) were identified as stable QTLs. In total, 125 candidate genes were identified in the confidence intervals of these stable QTLs. Presumably, Gh_D03G0857 may play an important role in regulating earliness. (4) Conclusions: This research will provide new information about fine mapping of QTLs for earliness traits, molecular marker assisted selection (MAS) of earliness traits, and pyramiding breeding as well.

Genome-Wide Association Analysis of Rice Leaf Traits

Yield-related traits have always been a research hotspot in rice breeding, and functional leaves directly affect the photosynthetic efficiency and yield of rice. Therefore, it is of great significance to explore the genes related to rice leaf size and shape to improve rice leaf morphology, photosynthesis efficiency, and yield. This study detected the quantitative trait loci (QTLs) for the length, width, length–width ratio, and area of rice flag leaf and second leaf in 393 accessions from the 3000 Rice Genome Project (3KRGP) by high-density single-nucleotide polymorphism genotyping. As a result, 91 QTLs were detected, among which 5 candidate genes (LOC_Os03g29170, LOC_Os06g17285, LOC_Os04g35060, LOC_Os03g27450, and LOC_Os09g16280) were identified. In addition, the epistatic interactions affecting leaf-related traits were also investigated, resulting in the identification of 134 significant QQIs (QTL by QTL interactions) pairs. The results of this study provide an important genetic basis for mining genes associated with rice leaf shape and valuable genetic information for rice breeding.

Genomic prediction and genome-wide association studies for additive and dominance effects for body composition traits using 50 K and imputed high-density SNP genotypes in Yunong-black pigs.

Body composition traits are complex traits controlled by minor genes and, in hybrid populations, are impacted by additive and nonadditive effects. We aimed to identify candidate genes and increase the accuracy of genomic prediction of body composition traits in crossbred pigs by including dominance genetic effects. Genomic selection (GS) and genome-wide association studies were performed on seven body composition traits in 807 Yunong-black pigs using additive genomic models (AM) and additive-dominance genomic models (ADM) with an imputed high-density single nucleotide polymorphism (SNP) array and the Illumina Porcine SNP50 BeadChip. The results revealed that the additive heritabilities estimated for AM and ADM using the 50 K SNP data ranged from 0.20 to 0.34 and 0.11 to 0.30, respectively. However, the ranges of additive heritability for AM and ADM in the imputed data ranged from 0.20 to 0.36 and 0.12 to 0.30, respectively. The dominance variance accounted for 23% and 27% of the total variance for the 50 K and imputed data, respectively. The accuracy of genomic prediction improved by 5% on average for 50 K and imputed data when dominance effect were considered. Without the dominance effect, the accuracies for 50 K and imputed data were 0.35 and 0.38, respectively, and 0.41 and 0.43, respectively, upon considering it. A total of 12 significant SNP and 16 genomic regions were identified in the AM, and 14 significant SNP and 21 genomic regions were identified in the ADM for both the 50 K and imputed data. There were five overlapping SNP in the 50 K and imputed data. In the AM, a significant SNP (CNC10041568) was found in both body length and backfat thickness traits, which was in the PLAG1 gene strongly and significantly associated with body length and backfat thickness in pigs. Moreover, a significant SNP (CNC10031356) with a heterozygous dominant genotype was present in the ADM. Furthermore, several functionally related genes were associated with body composition traits, including MOS, RPS20, LYN, TGS1, TMEM68, XKR4, SEMA4D and ARNT2. These findings provide insights into molecular markers and GS breeding for the Yunong-black pigs.

Genetic insights into crossbred dairy cattle of Pakistan: exploring allele frequency, linkage disequilibrium, and effective population size at a genome-wide scale.

Linkage disequilibrium (LD) affects genomic studies accuracy. High-density genotyping platforms identify SNPs across animal genomes, increasing LD evaluation resolution for accurate analysis. This study aimed to evaluate the decay and magnitude of LD in a cohort of 81 crossbred dairy cattle using the GGP_HDv3_C Bead Chip. After quality control, 116,710 Single Nucleotide Polymorphisms (SNPs) across 2520.241Mb of autosomes were retained. LD extent was assessed between autosomal SNPs within a 10Mb range using the r2 statistics. LD value declined as inter-marker distance increased. The average r2 value was 0.24 for SNP pairs < 10kb apart, decreasing to 0.13 for 50-100kb distances. Minor allele frequency (MAF) and sample size significantly impact LD. Lower MAF thresholds result in smaller r2 values, while higher thresholds show increased r2 values. Additionally, smaller sample sizes exhibit higher average r2 values, especially for larger physical distance intervals (> 50kb) between SNP pairs. Effective population size and inbreeding coefficient were 150 and 0.028 for the present generation, indicating a decrease in genetic diversity over time. These findings imply that the utilization of high-density SNP panels and customized/breed-specific SNP panels represent a highly favorable approach for conducting genome-wide association studies (GWAS) and implementing genomic selection (GS) in the Bos indicus cattle breeds, whose genomes are still largely unexplored. Furthermore, it is imperative to devise a meticulous breeding strategy tailored to each herd, aiming to enhance desired traits while simultaneously preserving genetic diversity.

Lifting of the 1,000 wheat exome project SNPs from Triticum aestivum cv. Chinese Spring assembly RefSeq v1.0 to RefSeq v2.1

ObjectiveThe 1,000 wheat exome project captured the single nucleotide variants in the coding regions of a diverse set of 890 wheat accessions to analyse the contribution of introgression to adaptation of wheat. However, this highly useful single nucleotide polymorphism (SNP) dataset is based on RefSeq v1.0 of the International Wheat Genome Sequencing Consortium (IWGSC) assembly of the bread wheat genome of Chinese Spring. This reference sequence has recently been updated using optical maps and long-read sequencing to produce the improved RefSeq v2.1. Our objective was to develop a reliable high-density SNP dataset positioned onto RefSeq v2.1 because it is the current standard reference sequence used by wheat researchers.ResultsThe 3,039,822 SNPs originally positioned on RefSeq v1.0 were projected to v2.1 using Liftoff with four different flanking regions, and 2,946,536 SNPs were consistently lifted to the same location irrespective of the flanking region lengths. Of these, 2,799,166 were located on the ‘+’ ve strand. The distribution of the SNPs across the 21 chromosomes on RefSeq v2.1 was similar to that of RefSeq v1.0. Among the SNPs that were based on unanchored scaffolds in RefSeq v1.0, 11,938 were projected to one of the 21 pseudomolecules in the upgraded assembly. This SNP dataset constitutes a much-needed standardized resource for the wheat research community.

Application of genomic big data to analyze the genetic diversity and population structure of Korean domestic chickens

Genetic diversity analysis is crucial for maintaining and managing genetic resources. Several studies have examined the genetic diversity of Korean domestic chicken (KDC) populations using microsatellite markers, but it is difficult to capture the characteristics of the whole genome in this manner. Hence, this study analyzed the genetic diversity of several KDC populations using high-density single nucleotide polymorphism (SNP) genotype data. We examined 935 birds from 21 KDC populations, including indigenous and adapted Korean native chicken (KNC), Hyunin and Jeju KDC, and Hanhyup commercial KDC populations. A total of 212,420 SNPs of 21 KDC populations were used for calculating genetic distances and fixation index, and for ADMIXTURE analysis. As a result of the analysis, the indigenous KNC groups were genetically closer and more fixed than the other groups. Furthermore, Hyunin and Jeju KDC were similar to the indigenous KNC. In comparison, adapted KNC and Hanhyup KDC populations derived from the same original species were genetically close to each other, but had different genetic structures from the others. In conclusion, this study suggests that continuous evaluation and management are required to prevent a loss of genetic diversity in each group. Basic genetic information is provided that can be used to improve breeds quickly by utilizing the various characteristics of native chickens.

Identification of QTL for kernel weight and size and analysis of the pentatricopeptide repeat (PPR) gene family in cultivated peanut (Arachis hypogaea L.)

Peanut (Arachis hypogaea L.) is an important oilseed crop worldwide. Improving its yield is crucial for sustainable peanut production to meet increasing food and industrial requirements. Deciphering the genetic control underlying peanut kernel weight and size, which are essential components of peanut yield, would facilitate high-yield breeding. A high-density single nucleotide polymorphism (SNP)-based linkage map was constructed using a recombinant inbred lines (RIL) population derived from a cross between the variety Yuanza9102 and a germplasm accession wt09-0023. Kernel weight and size quantitative trait loci (QTLs) were co-localized to a 0.16 Mb interval on Arahy07 using inclusive composite interval mapping (ICIM). Analysis of SNP, and Insertion or Deletion (INDEL) markers in the QTL interval revealed a gene encoding a pentatricopeptide repeat (PPR) superfamily protein as a candidate closely linked with kernel weight and size in cultivated peanut. Examination of the PPR gene family indicated a high degree of collinearity of PPR genes between A. hypogaea and its diploid progenitors, Arachis duranensis and Arachis ipaensis. The candidate PPR gene, Arahy.JX1V6X, displayed a constitutive expression pattern in developing seeds. These findings lay a foundation for further fine mapping of QTLs related to kernel weight and size, as well as validation of candidate genes in cultivated peanut.

Potential of low-density genotype imputation for cost-efficient genomic selection for resistance to Flavobacterium columnare in rainbow trout (Oncorhynchus mykiss)

BackgroundFlavobacterium columnare is the pathogen agent of columnaris disease, a major emerging disease that affects rainbow trout aquaculture. Selective breeding using genomic selection has potential to achieve cumulative improvement of the host resistance. However, genomic selection is expensive partly because of the cost of genotyping large numbers of animals using high-density single nucleotide polymorphism (SNP) arrays. The objective of this study was to assess the efficiency of genomic selection for resistance to F. columnare using in silico low-density (LD) panels combined with imputation. After a natural outbreak of columnaris disease, 2874 challenged fish and 469 fish from the parental generation (n = 81 parents) were genotyped with 27,907 SNPs. The efficiency of genomic prediction using LD panels was assessed for 10 panels of different densities, which were created in silico using two sampling methods, random and equally spaced. All LD panels were also imputed to the full 28K HD panel using the parental generation as the reference population, and genomic predictions were re-evaluated. The potential of prioritizing SNPs that are associated with resistance to F. columnare was also tested for the six lower-density panels.ResultsThe accuracies of both imputation and genomic predictions were similar with random and equally-spaced sampling of SNPs. Using LD panels of at least 3000 SNPs or lower-density panels (as low as 300 SNPs) combined with imputation resulted in accuracies that were comparable to those of the 28K HD panel and were 11% higher than the pedigree-based predictions.ConclusionsCompared to using the commercial HD panel, LD panels combined with imputation may provide a more affordable approach to genomic prediction of breeding values, which supports a more widespread adoption of genomic selection in aquaculture breeding programmes.

Design and validation of high-density SNP array of goats and population stratification of Indian goat breeds

Goats are the supporting pillars of rural economy contributing significantly to meat and milk production in India. It is a species targeted for fulfilling the interdependent goals of poverty reduction and creation of employment for supporting the rural income. The increased demand for goat products necessitates their genetic characterization and improvement to augment the production of native breeds. Bi-allelic, genome wide, densely placed single nucleotide polymorphism (SNP) markers are most suitable for this purpose. This paper describes the design and validation of an Affymetrix Axiom-based high-density (HD) SNP chip for goats. The array was designed using a panel of 225 samples from 15 diverse goat breeds of India. In total, more than 38 million high quality SNPs were subjected to stringent filtering and 626,975 SNPs were finally tiled on the array. The average coverage of SNPs in our chip is one SNP per four kilobase (kb), providing a denser coverage of the goat genome than previously available arrays. The HD chip (Axiom_Cahi) was validated by genotyping 443 samples from 26 indigenous goat breeds/populations. The results revealed 95.83% markers to be highly informative and polymorphic in Indian goats. Multivariate analysis indicated population structuring, as 15 breeds could be segregated using the designed array. Phylogenetic analysis suggested stratification of breeds by geographic proximity. This HD SNP chip for goats is a valuable resource for genomic selection, genome wide association as well as population genetic studies in goats.

A multi-omics analysis identifies molecular features associated with fertility in heifers (Bos taurus)

Infertility or subfertility is a critical barrier to sustainable cattle production, including in heifers. The development of heifers that do not produce a calf within an optimum window of time is a critical factor for the profitability and sustainability of the cattle industry. In parallel, heifers are an excellent biomedical model for understanding the underlying etiology of infertility because well-nourished heifers can still be infertile, mostly because of inherent physiological and genetic causes. Using a high-density single nucleotide polymorphism (SNP) chip, we collected genotypic data, which were analyzed using an association analysis in PLINK with Fisher’s exact test. We also produced quantitative transcriptome data and proteome data. Transcriptome data were analyzed using the quasi-likelihood test followed by the Wald’s test, and the likelihood test and proteome data were analyzed using a generalized mixed model and Student’s t-test. We identified two SNPs significantly associated with heifer fertility (rs110918927, chr12: 85648422, P = 6.7 × 10−7; and rs109366560, chr11:37666527, P = 2.6 × 10−5). We identified two genes with differential transcript abundance (eFDR ≤ 0.002) between the two groups (Fertile and Sub-Fertile): Adipocyte Plasma Membrane Associated Protein (APMAP, 1.16 greater abundance in the Fertile group) and Dynein Axonemal Intermediate Chain 7 (DNAI7, 1.23 greater abundance in the Sub-Fertile group). Our analysis revealed that the protein Alpha-ketoglutarate-dependent dioxygenase FTO was more abundant in the plasma collected from Fertile heifers relative to their Sub-Fertile counterparts (FDR < 0.05). Lastly, an integrative analysis of the three datasets identified a series of molecular features (SNPs, gene transcripts, and proteins) that discriminated 21 out of 22 heifers correctly based on their fertility category. Our multi-omics analyses confirm the complex nature of female fertility. Very importantly, our results also highlight differences in the molecular profile of heifers associated with fertility that transcend the constraints of breed-specific genetic background.