High-density Single Nucleotide Polymorphism Research Articles

GWAS identifies a polyembryony locus in mango: development of KASP and PACE markers for marker-assisted breeding

Apomixis is a horticultural trait that enables clonal propagation of hybrids by producing asexual embryos from maternal cells in the ovule without meiosis. Many mango cultivars exhibit apomictic polyembryony, where one embryo develops from zygotic tissues and the rest from nucellar tissues, resulting in seedlings that are genetically identical to the mother tree. In Mangifera indica L. commercially important rootstocks are raised from apomictic seeds, which are then grafted with desired cultivars. Identifying molecular markers for polyembryony and understanding its genetics would facilitate introducing this trait in commercially important cultivars. In this report, genome-wide association studies were conducted on a diversity panel consisting of 42 polyembryonic and 42 monoembryonic M. indica cultivars using high-density single nucleotide polymorphism (SNP) markers. These studies revealed that the polyembryony locus is in a 360-kb region on linkage group 17 of the ‘Alphonso’ reference genome. This locus contains the MiRWP/MiRKD4 gene, which codes for an RWP–RK domain-containing protein previously implicated in citrus apomixis. Comparative genomic analyses revealed synteny between the citrus and the mango polyembryony loci, suggesting a common evolutionary mechanism for this trait. A total of 29 SNP markers in this locus were significantly associated with polyembryony in M. indica. Five of these markers were developed into convenient genotyping assays using competitive allele-specific PCR chemistry implemented in two different genotyping platforms – Kompetitive Allele-Specific PCR (KASP) and PCR allele competitive extension (PACE). The utility of these assays was validated and demonstrated in diverse germplasm collection and open-pollinated mango breeding populations with known pedigrees and polyembryony phenotypes. These SNP markers, especially those flanking the MiRWP/MiRKD4 gene, provide a valuable tool for mango breeders to select polyembryonic progenies at the seedling stages in mango breeding programs.

Genome-wide association study reveals the advantaged genes regulating japonica rice grain shape traits in northern China.

Rice, a staple food for over half of the global population, exhibits significant diversity in grain shape characteristics, which impact not only appearance and milling quality but also grain weight and yield. Identifying genes and loci underlying these traits is crucial for improving rice breeding programs. Previous studies have identified multiple quantitative trait loci (QTLs) and genes regulating grain length, width, and length-width ratio; however, further investigation is necessary to elucidate their regulatory pathways and their practical application in crop improvement. This study employed a genome-wide association study (GWAS) on 280 japonica rice varieties from northern China to decipher the genetic basis of grain shape traits. Phenotyping included measurements of 11 grain-related traits, such as grain length, width, and area, along with their brown and white rice counterparts. High-density single nucleotide polymorphism (SNP) markers (33,579) were utilized for genotyping, and GWAS was performed using a mixed linear model (MLM) incorporating principal component analysis (PCA) and kinship (K) matrix to account for population structure and relatedness. Our analysis detected 15 QTLs associated with the 11 grain shape traits, of which five major QTL clusters emerged as crucial. Candidate genes, including LOC_Os01g50720 (qGL1), OsMKK4 (LOC_Os02g54600, influencing qBA2, qWL2, and qWA2), GW5 (LOC_Os05g09520, controlling qGW5, qBW5, qBR5, qWW5, and qWR5), GW6a (LOC_Os06g44100, associated with qGW6, qBW6, qBR6, qWW6, and qWR6), and FZP (LOC_Os07g47330, linked to qWL7), were identified based on functional annotations and haplotype analysis. These findings offer valuable insights into the genetic mechanisms underlying rice grain shape and suggest promising targets for marker-assisted selection to enhance rice quality and yield.

Mapping genetic susceptibility to spontaneous preterm birth: Analysis of Utah pedigrees to find inherited genetic factors.

Spontaneous preterm birth (SPTB) is the leading cause of neonatal morbidity and mortality. It is a final common pathway for multiple etiologies, some of which are well known while others likely remain to be identified. Despite recent advancements in identifying genetic risk factors, the mechanisms of many SPTBs remain poorly understood due to the phenotypic heterogeneity and complexity. Large family-based studies decrease heterogeneity and improve power to identify genetic causes of SPTB. To identify inherited genetic factors in SPTB etiology using large families. Using the Utah Population Database, which links a 4.5 million-person genealogy to state birth certificate and fetal death records, we identified large pedigrees containing multiple women with early SPTB (<34 weeks' gestation) and any SPTB (<37 weeks' gestation). We reviewed birth certificate data to exclude those with maternal and fetal diagnoses associated with iatrogenic preterm birth, resulting in 74 large multiplex pedigrees for early SPTB. Enrolled women with SPTB underwent comprehensive clinical phenotyping with review of primary medical records. Seven pedigrees, each containing at least 3 sampled women with SPTB, were the focus of this genetic study. High-density single-nucleotide polymorphism genotyping was conducted in maternal peripheral blood samples from women in the seven pedigrees. Shared genomic segments analysis was performed to identify genome-wide significant chromosomal regions shared in excess by women with SPTB. We identified two genome-wide significant chromosomal regions. In single-pedigree SGS analysis, a 1.75 Mega base region in chromosome 8 (8q24.23) was shared by 5 out of 6 women with SPTB in a single large pedigree (false positive rate=0.028). In duo-pedigree analysis, a 1.05 Mega base region in the same 8q24.23 locus was identified in a second pedigree (false-positive rate [duo]= 0.0019). The intersecting region at the 8q24.23 locus contains FAM135B (family with sequence similarity 135 member B) and KHDRBS3 (KH RNA binding domain containing, signal transduction associated 3) genes, which have previously been implicated in oncogenesis and ovarian cancer, respectively. Duo-pedigree SPTB analysis also identified a second genome-wide significant 67 kilo base locus in chromosome 12 (12q21.1-q21.2) that was shared by all women with SPTB in two independent pedigrees (false-positive rate [duo] =0.01). The intersecting region at the 12q21.1-q21.2 locus contains CAPS2 (calcyphosine 2) and KCNC2 (potassium voltage-gated channel subfamily C member 2) genes, both implicated in vascular-related complications of pregnancy and preterm labor. Using large SPTB families, we identified shared chromosomal regions (8q24.23 and 12q21.1-q21.2), providing evidence for inherited (segregating) risk loci in SPTB etiology. Further investigation into genes in SPTB etiology, including functional validation may provide avenues for novel therapeutic development and guide efforts for SPTB prevention to prolong pregnancy and improve outcomes.

Signatures of selection analyses reveal genomic differences among three heavy pig breeds that constitute the genetic backbone of a dry-cured ham production system

The Italian pig farming industry is unique in its focus on raising heavy pigs primarily for the production of high-quality dry-cured hams. These products require pigs to be slaughtered at a live weight of around 170 kg at 9 months of age. The primary breeds used in this system are Italian Duroc, Italian Landrace, and Italian Large White which are crossed to produce lines that meet standard requirements. Over the past four decades, selection and breeding programmes for these breeds have been subjected to distinct selective pressures to highlight the characteristics of each breed. In this study, we investigated the genome of these breeds by analysing high-density single nucleotide polymorphism data from over 9 000 pigs to scan for signatures of selection using four different methods, two within breeds and two across breeds. This allowed to identify the genomic regions that differentiate these breeds as well as any relevant genes and biological terms. On a global scale, we found that the Italian Duroc breed exhibited a higher genetic differentiation from the Italian Landrace and Italian Large White breeds, with a pairwise FST value of 0.20 compared with the 0.13 between Italian Landrace and Italian Large White. This may reflect either their different origins or the different breeding goals, which are more similar for the Italian Landrace and Italian Large White breeds. Despite these genetic differences at a global level, few signatures of selection regions reached complete fixation, possibly due to challenges in detecting selection linked to quantitative polygenic traits. The differences among the three breeds are confirmed by the low level of overlap in the regions detected. Genetic enrichment analyses of the three breeds revealed pathways and genes related to various productive traits associated with growth and fat deposition. This may indicate a common selection direction aimed at enhancing specific production traits, though different biological mechanisms are likely targeted by the same directional selection in these three breeds. Therefore, these genes may play a critical role in determining the distinctive characteristics of Italian Duroc, Italian Landrace, and Italian Large White, and potentially influence the traits in crossbred pigs derived from them. Overall, the insights gained from this study will contribute to understanding how directional selection has shaped the genome of these heavy pig breeds and to better address selection strategies aimed at enhancing the meat processing industry linked with dry-cured ham production chains.

The Fate of a Polygenic Phenotype Within the Genomic Landscapes of Introgression in the European Seabass Hybrid Zone.

Unraveling the evolutionary mechanisms and consequences of hybridization is a major concern in biology. Many studies have documented the interplay between recombination and selection in modulating the genomic landscape of introgression, but few have considered how associations with phenotype may affect this landscape. Here, we use the European seabass (Dicentrarchus labrax), a key species in marine aquaculture that undergoes natural hybridization, to determine how selection on phenotype modulates the introgression landscape between Atlantic and Mediterranean lineages. We use a high-density single nucleotide polymorphism array to assess individual local ancestry along the genome and improve the mapping of muscle fat content, a polygenic trait that is divergent between lineages. Taking into account variation in recombination rates, we reveal a purging of Atlantic ancestry in the admixed Mediterranean populations. While Atlantic individuals had higher muscle fat content, we observed that genomic regions associated with this trait in Mediterranean populations displayed reduced introgression of Atlantic ancestry. These results emphasize how selection against maladapted alleles shapes the genomic landscape of introgression.

Genome-wide discovery of selection signatures in four Anatolian sheep breeds revealed by ddRADseq

High-density genomic data analyzed by accurate statistical methods are of potential to enlighten past breeding practices such as selection by unraveling fixed regions. In this study, four native Turkish sheep breeds (80 samples) were genotyped via 296.097 single nucleotide polymorphisms (SNPs) detected by double-digest restriction site-associated DNA (ddRADseq) library preparation combined with the Illumina HiSeq X Ten instrument in order to identify genes under selection pressure. A total of 32, 136, 133, and 119 protein-coding genes were detected under selection pressure by runs of homozygosity (ROH), integrated haplotype score (iHS), the ratio of extended haplotype homozygosity (Rsb), and fixation index (FST) approaches, respectively. Of these, a total of 129 genes were identified by at least two statistical models which overlapped with a total of 52 quantitative trait loci (QTL)-associated SNPs, known to be related to fiber diameter, milk content, body weight, carcass traits, some blood parameters, and entropion. A total of six genes under selection pressure were validated by three statistical approaches five of which are of potential to be integrated into animal breeding since they were associated with wool fiber diameter (ZNF208B), behaviors related to neurocognitive development (CBX1 and NFE2L1), adaptation to high-altitude (SDK1), and anxiety causing internal stress (GSG1L). The sixth gene (COPZ1) turned out to play an important role in coping with different types of cancer in mammals. In particular, ROH analysis uncovered significant findings that the Güney Karaman (GKR) had experienced different selection practices than the Akkaraman (AKR) breed. Moreover, some genes specifically under selection in the GKR breed turned out to be associated with olfaction (OR6K6, OR6N1, OR6N2, and OR4C16), survival during the gestation period (PRR15L), and heat stress (CDK5RAP9). The results of this study imply that GKR may become genetically different from the AKR breed at the genome level due to most probably experiencing different adaptation processes occurring in raised climatic conditions. These differences should be conserved to face future challenges, while other native Turkish sheep breeds could be monitored via genome-wide high-density SNP data to obtain deeper knowledge about the effects of natural selection.

It’s all relative: A multi-generational study using ForenSeq™ Kintelligence

The successful application of Forensic Investigative Genetic Genealogy (FIGG) to the identification of unidentified human remains and perpetrators of serious crime has led to a growing interest in its use internationally, including Australia. Routinely, FIGG has relied on the generation of high-density single nucleotide polymorphism (SNP) profiles from forensic samples using whole genome array (WGA) (∼650,000 or more SNPs) or whole genome sequencing (WGS) (millions of SNPs) for DNA segment-based comparisons in commercially available genealogy databases. To date, this approach has required DNA of a quality and quantity that is often not compatible with forensic samples. Furthermore, it requires the management of large data sets that include SNPs of medical relevance. The ForenSeq™ Kintelligence kit, comprising of 10,230 SNPs including 9867 for kinship association, was designed to overcome these challenges using a targeted amplicon sequencing-based method developed for low DNA inputs, inhibited and/or degraded forensic samples. To assess the ability of the ForenSeq™ Kintelligence workflow to correctly predict biological relationships, a comparative study comprising of 12 individuals from a family (with varying degrees of relatedness from 1st to 6th degree relatives) was undertaken using ForenSeq™ Kintelligence and a WGA approach using the Illumina Global Screening Array-24 version 3.0 Beadchip. All expected 1st, 2nd, 3rd, 4th and 5th degree relationships were correctly predicted using ForenSeq™ Kintelligence, while the expected 6th degree relationships were not detected. Given the (often) limited availability of forensic samples, findings from this study will assist Australian Law enforcement and other agencies considering the use of FIGG, to determine if the ForenSeq™ Kintelligence is suitable for existing workflows and casework sample types considered for FIGG.

Genetic diversity analysis of tropical and sub-tropical maize germplasm for Striga resistance and agronomic traits with SNP markers.

Striga hermonthica (Sh) and S. asiatica (Sa) are major parasitic weeds limiting cereal crop production and productivity in sub-Saharan Africa (SSA). Under severe infestation, Striga causes yield losses of up to 100%. Breeding for Striga-resistant maize varieties is the most effective and economical approach to controlling the parasite. Well-characterized and genetically differentiated maize germplasm is vital to developing inbred lines, hybrids, and synthetic varieties with Striga resistance and desirable product profiles. The objective of this study was to determine the genetic diversity of 130 tropical and sub-tropical maize inbred lines, hybrids, and open-pollinated varieties germplasm using phenotypic traits and single nucleotide polymorphism (SNP) markers to select Striga-resistant and complementary genotypes for breeding. The test genotypes were phenotyped with Sh and Sa infestations using a 13x10 alpha lattice design with two replications. Agro-morphological traits and Striga-resistance damage parameters were recorded under a controlled environment. Further, high-density Diversity Array Technology Sequencing-derived SNP markers were used to profile the test genotypes. Significant phenotypic differences (P<0.001) were detected among the assessed genotypes for the assessed traits. The SNP markers revealed mean gene diversity and polymorphic information content of 0.34 and 0.44, respectively, supporting the phenotypic variation of the test genotypes. Higher significant variation was recorded within populations (85%) than between populations using the analysis of molecular variance. The Structure analysis allocated the test genotypes into eight major clusters (K = 8) in concordance with the principal coordinate analysis (PCoA). The following genetically distant inbred lines were selected, displaying good agronomic performance and Sa and Sh resistance: CML540, TZISTR25, TZISTR1248, CLHP0303, TZISTR1174, TZSTRI113, TZDEEI50, TZSTRI115, CML539, TZISTR1015, CZL99017, CML451, CML566, CLHP0343 and CML440. Genetically diverse and complementary lines were selected among the tropical and sub-tropical maize populations that will facilitate the breeding of maize varieties with Striga resistance and market-preferred traits.

Exotic alleles from the wild Hordeum spontaneum contribute to drought tolerance and grain quality in modern Hordeum vulgare

Conventional breeding relies on genetic variability in crop germplasm and wild species. This study evaluated 137 barley Recombinant Chromosome Substitution Lines (RCSLs), originating from crossing a drought and salinity-tolerant wild Hordeum spontaneum with the high-quality malting H. vulgare cv. Harrington. The objectives of this work were to i) improve understanding of the genetic diversity and introgression levels in RCSLs using a comprehensive set of high-density single nucleotide polymorphism (SNP) markers; ii) investigate the phenotypic variability of physiological, agronomic, and malting quality traits in RCSLs under rainfed and fully irrigated conditions; iii) unravel the relationship between these traits and the resilience of crops in drought-prone regions; and iv) identify specific SNPs associated with both drought tolerance indices and malting quality traits. Variability in physiological, agronomic, and malting quality traits was examined under rainfed and irrigated conditions, aiming to identify specific SNPs associated with both drought tolerance indices and malting quality traits. Additionally, a subset of three recombinant lines and the parent cv. Harrington was tested in growth chambers under well-watered and water-limited conditions. Agronomic traits were influenced by genotype-by-environment interaction, with notable drought tolerance lines. The grain yield was significantly correlated with yield-related traits and carbon isotope discrimination in grains. Drought stress impacted agronomic and physiological traits, with a strong reduction in leaf gas exchange and chlorophyll and protein content. The H. spontaneum genome introgression into H. vulgare cv. Harrington varied across 137 RCSLs, averaging 13.0 %. Associations between traits and genetic markers were found, particularly for the stress tolerance index in chromosome 1H and for grain quality traits (alfa-amylase, wort color, and protein) in chromosomes 1H, 4H, and 5H. These findings uncovered valuable barley RCSLs that demonstrate drought tolerance, offering promising prospects for breeding programs targeted at improving stress resilience.

Genetic analysis of yield components in buckwheat using high-throughput sequencing analysis and wild resource populations.

Fagopyrum tataricum, an important medicinal and edible crop, possesses significant agricultural and economic value. However, the development of buckwheat varieties and yields has been hindered by the delayed breeding progress despite the abundant material resources in China. Current research indicates that quantitative trait loci (QTLs) play a crucial role in controlling plant seed type and yield. To address these limitations, this study constructed recombinant inbred lines (RILs) utilizing both cultivated species and wild buckwheat as raw materials. In total, 84,521 Single Nucleotide Polymorphism (SNP) markers were identified through Genotyping-by-Sequencing (GBS) technology, and high-resolution and high-density SNP genetic maps were developed, which had significant value for QTL mapping, gene cloning and comparative mapping of buckwheat. In this study, we successfully identified 5 QTLs related to thousand grain weight (TGW), 9 for grain length (GL), and 1 for grain width (GW) by combining seed type and TGW data from 202 RIL populations in four different environments, within which one co-located QTL for TGW were discovered on the first chromosome. Transcriptome analysis during different grain development stages revealed 59 significant expression differences between the two materials, which can serve as candidate genes for further investigation into the regulation of grain weight and yield enhancement. The mapped major loci controlling TGW, GL and GW will be valuable for gene cloning and reveal the mechanism underlying grain development and marker-assisted selection in Tartary buckwheat.

Fine mapping of QYrsv.swust-1BL for resistance to stripe rust in durum wheat Svevo.

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a serious disease that affects wheat worldwide. There is a great need to develop cultivars with combinations of all-stage resistance (ASR) and adult-plant resistance (APR) genes for sustainable control of the disease. QYrsv.swust-1BL in the Italian durum wheat (Triticum turgidum ssp. durum) cultivar Svevo is effective against Pst races in China and Israel, and the gene has been previously mapped to the long arm of chromosome 1B. The gene is flanked by SNP (single nucleotide polymorphism) markers IWB5732 and IWB4839 (0.75 cM). In the present study, we used high-density 660K SNP array genotyping and the phenotypes of 137 recombinant inbred lines (RILs) to fine map the QYrsv.swust-1BL locus within a 1.066 Mb region in durum wheat Svevo (RefSeq Rel. 1.0) on chromosome arm 1BL. The identified 1.066 Mb region overlaps with a previously described map of Yr29/QYr.ucw-1BL, a stripe rust APR gene. Twenty-five candidate genes for QYrsv.swut-1BL were identified through comparing polymorphic genes within the 1.066 Mb region in the resistant cultivar. SNP markers were selected and converted to Kompetitive allele-specific polymerase chain reaction (KASP) markers. Five KASP markers based on SNP were validated in a F2 and F2:3 breeding population, providing further compelling evidence for the significant effects of QYrsv.swut-1BL. These markers should be useful in marker-assisted selection for incorporating Yr29/QYrsv.swust-1BL into new durum and common wheat cultivars for resistance to stripe rust.

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 (&amp;gt;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.

SABO-ILSTSVR: a genomic prediction method based on improved least squares twin support vector regression.

In modern breeding practices, genomic prediction (GP) uses high-density single nucleotide polymorphisms (SNPs) markers to predict genomic estimated breeding values (GEBVs) for crucial phenotypes, thereby speeding up selection breeding process and shortening generation intervals. However, due to the characteristic of genotype data typically having far fewer sample numbers than SNPs markers, overfitting commonly arise during model training. To address this, the present study builds upon the Least Squares Twin Support Vector Regression (LSTSVR) model by incorporating a Lasso regularization term named ILSTSVR. Because of the complexity of parameter tuning for different datasets, subtraction average based optimizer (SABO) is further introduced to optimize ILSTSVR, and then obtain the GP model named SABO-ILSTSVR. Experiments conducted on four different crop datasets demonstrate that SABO-ILSTSVR outperforms or is equivalent in efficiency to widely-used genomic prediction methods. Source codes and data are available at: https://github.com/MLBreeding/SABO-ILSTSVR.