Non-alcoholic fatty liver disease (NAFLD) affects up to a quarter of the adult population in many developed and developing countries. This spectrum of liver disease ranges from simple steatosis to nonalcoholic steatohepatitis (NASH) and cirrhosis. The incidence of NASH is projected to increase by up to 56% over the next 10 years. There is growing epidemiological evidence that NAFLD has become the fastest growing cause of hepatocellular carcinoma (HCC) in industrialized countries. The annual incidence of HCC varies between patients with NASH cirrhosis and patients with noncirrhotic NAFLD. In this review, NAFLD/NASH-associated HCC will be described, including its epidemiology, risk factors promoting hepatocarcinogenesis, and management of HCC in patients with obesity and associated metabolic comorbidities, including preventive strategies and therapeutic approaches to address this growing problem.

Background: Alfalfa, the most economically important forage legume worldwide, features modest genetic progress due to long selection cycles and large extent of non-additive genetic variance associated with its autotetraploid genome. Methods: To improve the efficiency of genomic selection in alfalfa, we explored the effects of genome parametrization (as autotetraploid and diploid dosage, plus allele ratios) and SNP marker subsetting (all available SNPs; only genic regions; only non-genic regions) on genomic regressions, together with various levels of filtering on reading depth and missing rates. We used Genotyping by Sequencing-generated data and focused on traits of different genetic complexity, i.e., dry biomass yield in moisture-favorable (FE) and drought stress (SE) environments, leaf size, and onset of flowering, assessed on 143 genotyped plants from a genetically-broad European reference population and their phenotyped half-sib progenies. Results: On average, allele ratio improved the predictive ability compared with other genome parametrizations (+7.9% vs. tetraploid dosage, +12.6% vs. diploid dosage), SNP subsetting offered an advantage compared with any tested subsettings (+3.7% vs. genic regions, +7.6% vs. non-genic regions). However, when focusing on specific traits, different combinations of genome parametrization and subsetting reached better performances. We also released Legpipe2, a SNP calling pipeline tailored for reduced representation (GBS, RAD) medium-sized genotyping experiments.

(1) Background: The goal of our study was to identify SNPs, metabolic pathways (KEGG), and gene ontology (GO) terms significantly associated with calving and workability; (2) Methods: Based on the EuroGenomics reference data set, we analyzed direct (DCE) and maternal (MCE) calving ease, direct (DSB), and maternal (MSB) stillbirth, milking speed (MSP), and temperament (TEM). We estimated SNP effects using a multi-SNP mixed-model. Further, SNP positions were mapped to genes, and GO terms/KEGG pathways of the corresponding genes were assigned. The estimation of GO term/KEGG pathway effects was based on a mixed-model using SNP effects as dependent variables; (3) Results: The number of significant SNPs comprised 59 for DCE, 25 for DSB and MSP, 17 for MCE and MSB, and 7 for TEM. Significant KEGG pathways were found for MSB (2), TEM (2), and MSP (1), while 11 GO terms were significant for MSP, 10 for DCE, 8 for DSB and TEM, 5 for MCE, and 3 for MSB.; (4) Conclusions: From the perspective of a better understanding of the genomic background of the phenotypes, traits with low heritabilities suggest that the focus should be moved from single genes to metabolic pathways or gene ontologies significant for the phenotype.

Molecular markers, including Simple Sequence Repeat (SSR), Single Nucleotide Polymorphism (SNP), and Intron Length Polymorphism (ILP), are widely utilized in crop improvement and population genetics studies. However, these marker resources remain insufficient for Musa species. In this study, we developed genome-wide SSR, SNP, and ILP markers from Musa and its sister species, creating a comprehensive molecular marker repository for the improvement of Musa species. This database contains 2115474 SSR, 63588 SNP, and 91547 ILP markers developed from thirteen Musa species and two of its relative species. We found that 77% of the SSR loci are suitable for marker development; 38% of SNP markers originated from the genic region, and transition mutations (C↔T; A↔G) were more frequent than transversion. The database is freely accessible and follows a ‘three-tier architecture,’ organizing marker information in MySQL tables. It has a user-friendly interface, written in JavaScript, PHP, and HTML code. Users can employ flexible search parameters, including marker location in the chromosome, transferability, polymorphism, and functional annotation, among others. These distinctive features distinguish the Musa Marker Database (MMdb) from existing marker databases by offering a novel approach that is tailored to the precise needs of the Musa research community. Despite being an in silico method, searching for markers based on various attributes holds promise for Musa research. These markers serve various purposes, including germplasm characterization, gene discovery, population structure analysis, and QTL mapping.

Sepsis is an inflammatory disorder caused by the host’s dysfunctional response to infection. Septic patients present diverse clinical characteristics, and in the recent years it has been the main cause of death in intensive care units (ICU). Aquaporins, membrane proteins with role in water transportation, have been reported to participate in numerous biological processes. Their role in sepsis progression has been studied extensively. This review aims to examine recent literature on aquaporin expression and regulation in clinical sepsis, as well as established experimental models of sepsis. We will present how sepsis affects aquaporin expression at the molecular and protein level. Moreover, we will delve into the importance of aquaporin regulation at the transcriptional, post-transcriptional, translational, and post-translational level in sepsis, by presenting data on aquaporin regulation by non-coding RNAs and selected chemical molecules. Finally, we will focus on the importance of aquaporin single nucleotide polymorphisms in the setting of sepsis.

Recent climatic disasters (dzudzs) and uncontrolled massive breeding endangered valuable ge-netic resources of Mongolian goats labored by five thousand years of evolution in extremes of Al-tai mountains and Gobi deserts. Meanwhile, Mongolian goats has never been characterized by genomic data. We used Illumina Goat SNP50 to investigate phylogenic relationships and genetic risks in 5 local Mongolian populations: Erchim (N=37) from geographically remote Darkhat Valley in the northern mountains, Ulgii Red (N=35) and Dorgon (N=28) from the western mountain region, Buural (N=34) from the western steppe and mountain areas and Gobi Gurvan Saikhan (N=33) from semi-arid steppe area in the South Gobi region. ROH analyses, estimated populations sizes and Fst values showed South Gobi and Darkhat Valley goats to be of a high risk of inbreed-ing that however appear to be of distinct origin (artificial selection vs geographical isolation). In-dices of genetic differentiations between Mongolian goats were relatively low compared to Euro-pean breeds. Meanwhile, we suggest direct comparison is not fully appropriate given that Mongo-lian breeds were not subjected to intense selection. Darkhat Valley goats were clearly differentiat-ed from other Mongolian breeds according to various types of analyses. Phylogenetic relationships within XXX breeds of the rest of the world plotted Mongolian goats between some Russian (Altai, Orenburg) and Chinese populations (Nanjiang and Qinggeli). Thus, present study (i) highlights demographic history Mongolian goats and (ii)provides unified SNP-data called for support deci-sions in conservational genetics. Finally, our work (iii) raises a question of how exactly these data should be compared to make objective choices.

Rheumatoid arthritis (RA); is a chronic systemic autoimmune disease which causes loss of joint function and significantly reduces quality of life. Plasma metabolite concentrations of disease-modifying anti-rheumatic drugs (DMARDs) can influence treatment efficacy and toxicity. This study explored the relationship between DMARD metabolising gene variants and plasma metabolite levels in RA patients. DMARD metabolite concentrations were determined by tandem mass-spectrometry in plasma samples from 100 RA patients with actively flaring disease, collected at two intervals. Taqman-probes were used to discriminate single nucleotide polymorphism (SNP) genotypes in cohort genomic DNA: rs246240 (ABCC1), rs1476413 (MTHFR), rs2231142 (ABCG2), rs3740065 (ABCC2), rs4149081 (SLCO1B1), rs4846051 (MTHFR), rs10280623 (ABCB1), rs16853826 (ATIC), rs17421511 (MTHFR) and rs717620 (ABCC2). Mean plasma concentrations of methotrexate (MTX) and MTX-7-OH metabolites were higher (p<0.05, C.I. 95%) at baseline in rs4149081 GA genotype patients. Patients with rs1476413 SNP TT or CT alleles in the have significantly higher (p<0.001, 95% C.I) plasma poly-glutamate metabolites at both study time points and correspondingly elevated disease activity scores. Patients with the rs17421511 SNP AA allele reported significantly lower pain scores (p<0.05, 95% C.I.) at both study intervals. Genotyping strategies could help prioritise treatments to RA patients most likely to gain clinical benefit, whilst minimizing toxicity.

Type 2 diabetes mellitus (T2DM) is a polygenic metabolic disease described by hyperglycemia, which is caused by insulin resistance or reduced insulin secretion. Interaction between various genetic variants and environmental factors triggers T2DM. The main aim of this study was to find the risk associated with genetic variant (rs5210) of KCNJ11gene in the development of T2D in Indian Population. A total number of 300 cases of T2D and 100 control samples were studied to find the polymorphism in KCNJ11 through PCR-RFLP. The genotype and allele frequencies in T2DM cases were significantly different from the control population. We found a significant association of KCNJ11 (rs5210) gene polymorphism with T2DM in North Indian patients indicating the role of this variant in developing risk for T2DM.

B4GALNT2 is a vital candidate gene that affects the growth traits litter size in and growth traits of sheep, but whether it has the same function in goats remains to be further investigated. In this study, we utilized 348 Nanjiang Yellow goats as experimental subjects, conducted a whole exon, and the conserved the non-coding region SNP scanning of the B4GALNT2 gene. Our results revealed the presence of a synonymous mutation, rs672215506, within the exon of the B4GALNT2 gene in the Nanjiang Yellow goat population. This mutation was found to be associated with reduced mRNA stability of the B4GALNT2 gene. The results of SNPs detection of conserved non-coding region of B4GALNT2 gene showed that there were five potential regulatory SNPs in the Nanjiang Yellow goat population, except for rs66095343, the ~500 bp fragments of four SNPs (rs649127714, rs649573228, rs652899012 and rs639183528) could significantly increase luciferase activity both in goat skeletal muscle cells and 293T cells . Genetic diversity indexes indicated low or intermediate levels for all six SNPs analyzed, each conforming to Hardy-Weinberg equilibrium regarding genotypic frequencies. Association analysis indicated that rs660965343, rs649127714 and rs649573228 were significantly correlated with growth traits in the later stage of growth and development of Nanjiang Yellow goat. The haplotype combinations of H2H3 and H2H2 had higher body weight and greater body size; moreover, H2H2 haplotype combinations were significantly correlated with the litter size of Nanjiang Yellow goat. The results of our study demonstrate the potential utility of the B4GALNT2 gene as a functional genetic marker in breeding programs for Nanjiang Yellow goats.

Analysis of telomere length is an important component of many studies aiming to characterize the role of telomere maintenance mechanisms in cellular lifespan, disease, or in general chromosome protection and DNA replication pathways. Several powerful methods to accurately measure telomere length from Southern blots have been developed, but their utility for large-scale genomic studies has not been previously evaluated. Here we performed comparative analysis of two recently developed programs, TeloTool and WALTER, for extracting mean telomere length values from Southern blots. Using both software packages, we measured telomere length in two extensive experimental datasets for the model plant Arabidopsis thaliana, consisting of 537 natural accessions and 65 T-DNA mutant lines in the Col-0 reference background. We report that TeloTool substantially overestimates telomere length in comparison to WALTER, especially for values over 4,500 bp. Importantly, TeloTool and WALTER-calculated telomere length values correlate the most in the 2,100-3,500 bp range, suggesting that telomeres in this size interval can be estimated by both programs equally well. We further show that genome-wide association studies using datasets from both telomere length analysis tools can detect the most significant SNP candidates equally well. However, GWAS analysis with the WALTER dataset consistently detects fewer significant SNPs than analysis with the TeloTool dataset, regardless of the GWAS method used. These results imply that telomere length data generated by WALTER may represent a more stringent approach to GWAS and SNP selection for downstream molecular screening of candidate genes. Overall, our work revealed the unanticipated impact of telomere length analysis method on the outcomes of large-scale genomic screens.

Type 2 diabetes (T2D) is a chronic systemic disease with a complex etiology, characterized by insulin resistance and mitochondrial dysfunction in various cell tissues. To explore this relationship, we conducted a secondary analysis of complete mtDNA sequences from 1,261 T2D patients and 1,105 control individuals. Our findings revealed significant associations between certain single nucleotide polymorphisms (SNPs) and T2D. Notably, the variants m.1438A>G (controls: 32 [27.6%], T2D: 84 [72.4%]; OR: 2.46; 95%CI: 1.64-3.78; p<0.001), m.14766C>T (controls: 498 [36.9%], T2D: 853 [63.1%]; OR: 2.57, 95%CI: 2.18-3.04, p<0.001), and m.16519T>C (controls: 363 [43.4%], T2D: 474 [56.6%]; OR: 1.24, 95%CI: 1.05-1.47, p=0.012) were significantly associated with diabetes probability. The variant m.16189T>C Previously reported in multiple studies in different populations, it was not found to be associated with T2D in our analysis (controls: 148 [13.39] T2D: 171 [13.56%]; OR: 1.03; 95%CI: 0.815-1.31,; p=0.83). These results provide evidence suggesting a link between some mtDNA polymorphisms and T2D, probably related to association rules and topological patterns and three-dimensional confirmation associated to regions where the changes are, rather than to point mutations in the sequence.

In pig production, pigs often show more aggressive behavior after mixing, which adversely affects animal welfare and growth performance. The Jumonji and structural domain-rich AT interaction domain 2 (JARID2) gene plays an important role in neurodevelopment in mice and various psychiatric disorders in humans. The JARID2 gene may impact the aggressive behavior of pigs. By observing the behavior of 500 weaned pigs during the first 72 hours after mixing, the ear tissue samples of the 12 most aggressive and 12 least aggressive pigs were selected for DNA resequencing based on the intensity of their aggressive behavior. Large group correlation analysis indicated that the rs3262221458 site located in the 3'-UTR region of the porcine JARID2 gene has a strong relationship with aggressive behavior of weaned pigs. Pigs with the mutant TT genotype of rs3262221458 have more aggressive behavior than those pigs with the GG and GT genotypes. The dual luciferase assay indicated that the luciferase activity of the plasmids containing the G allele of rs326221458 was significantly less than plasmids conaining the T allele of rs326221458 and control groups. The binding abiltiy of miR-9828-3p to sequences containing the T allele was less than sequences containing the G allele. The overexpression of miR-9828-3p in porcine neuroglial cells (PNGCs) and PK15 cells significantly decreased the mRNA and protein levels of the JARID2 gene. In addition, miR-9828-3p inhibited the proliferation of PNGCs. After inhibiting miR-9828-3p, the mRNA and protein expression levels of JARID2 increased, and the proliferation of PNGCs showed an opposite trend to the cells that forced expression of miR-9828-3p. In addition, interference with the JARID2 gene by siRNA can effectively inhibit the proliferation of PNGCs. In summary, we found that the rs326221458 locus regulates the expression of the JARID2 gene by affecting the binding of miR-9828-3p and the JARID2 gene, thereby affecting the aggressive behavior of weaned pigs after mixing.

Growing evidence indicates the involvement of a genetic component for CaP susceptibility and clinical severity. Somatic mutations of TP53 have been associated with 50% of diverse human cancers. Studies have also reported the role of germ line mutations and single nucleotide poly-morphisms (SNPs) of TP53 as possible risk factors for cancer development. In this single De-partment of Defense institutional retrospective study, we identified common SNPs in the TP53 gene in AA and CA men and performed association analyses for functional TP53 SNPs with clinico-pathological features of CaP. The CPDR Oncoarray database on blood derived genomic DNA from 321 men treated by radical prostatectomy at WRNMMC were used to examine clini-co-pathological associations with TP53 SNPs. The SNP genotyping analysis on the final cohort of 308 patients (212 AA; 95 CA) identified 74 SNPs in the TP53 gene region with a minor allele fre-quency (MAF) of at least 1%. Two SNPs were non-synonymous in the exonic region of TP53: rs1800371 (Pro47Ser) and rs1042522 (Arg72Pro). The Pro47Ser variant, had a minor allele frequency of 0.01 in AA, however, was not detected in CA. Arg72Pro was the most common SNP with a minor allele frequency of 0.50 (0.41 in AA; 0.68 in CA). Additionally, Arg72Pro was associated with time to biochemical recurrence (BCR) after statistical adjustment for patient age at diagnosis, self-reported race, and Gleason score (p= 0.046; HR = 1.52). The present study demonstrated ancestral differences in allele frequencies of TP53 Arg72Pro and Pro47Ser SNPs in AA and CA CaP, providing a valuable framework for the interrogating CaP disparity among AA and CA men.

Uncontrolled transmission of Mycobacterium tuberculosis (M. tuberculosis, MTB) drug resistant strains is a challenge to control efforts of global tuberculosis programme. Due to increasing multi-drug resistant (MDR) cases in Arunachal Pradesh, a northeastern state of India, the tracking and tracing of these resistant MTB strains is crucial for infection control and spread of drug resistance. This study aims to correlate the phenotypic DST, genomic DST (gDST) and phylogenetic analysis of MDR-MTB strains in the region. Of total 200 suspected MDR-MTB isolates, 125(62.5%) were identified as MTB. MGIT-960 SIRE DST detected 71/125(56.8%) isolates as MDR/RR-MTB of which 22(30.9%) were detected resistant to second line drugs. Whole genome sequencing of 65 isolates and their gDST found Ser315Thr mutation in katG (35/45;77.8%) and Ser531Leu mutation in rpoB (21/41;51.2%) associated with drug resistance. SNP barcoding categorized the dataset with Lineage2 (41;63.1%) being predominant followed by Lineage3 (10;15.4%), Lineage1 (8;12.3%) and Lineage4 (6;9.2%) respectively. Phylogenetic assignment by cgMLST gave insights of two Beijing sub-lineages viz; 2.2.1 (SNP difference &lt; 19) and 2.2.1.2 (SNP difference &lt; 9) associated with recent ongoing transmission in Arunachal Pradesh. This study provides first insight in identifying the ongoing transmission of two virulent Beijing sub-lineages associated with TB drug resistance.

The most important factor that determines beef tenderness is its proteolytic activity and the balance between calpain1 protease activity and calpastatin inhibition is especially important, while contributions could arise from calpain2 and possibly calpain3. These processes are however affected by the meat aging process itself. To determine whether genotypes in the calpaincalpastatin system can enhance tenderness throughout a 20 day aging period, South African purebred beef bulls (n=166) were genotyped using the Illumina BovineHD SNP BeadChip, through genebased association analysis targeting the cast, capn3, capn2 and capn1 genes. The WarnerBratzler shear force (WBSF) and myofibril fragment length (MFL) of Longissimus thoracis et lumborum (LTL) steaks were evaluated between d 3 d 20 of aging, with protease enzyme activity in the first 20 h postmortem. Although several of the 134 SNP associated with tenderness, only seven SNP in the cast, capn2 and capn1 genes sustained genetic associations, additive to agingassociated increases in tenderness for at least three of the four aging periods. While most genomic associations were relatively stable over time, some genotypes within SNP responded differently to aging, resulting in altered genomic effects over time. The level of aging at which genomic associations are performed is an important factor that determines whether SNP affect tenderness phenotypes.

The expression microarray technique was performed to investigate the differences in gene expression between Czech Large White pigs and wild boars in the longissimus lumborum et thoracis and biceps femoris muscle tissues. The NREP gene (neuronal regeneration related protein homolog) was selected for detailed study as an expressional and functional candidate gene. NREP plays a role in the transformation of neural, muscle and fibroblast cells and in smooth muscle myogenesis. Quantitative real-time PCR results confirmed that the porcine NREP gene was expressed in both skeletal muscles and significantly overexpressed in Czech Large White pigs compared to wild boars (P &lt; 0.05). We identified 9 polymorphic sites in genomic DNA of NREP gene. Six of these polymorphisms were in complete linkage disequilibrium and therefore only 4 polymorphisms were informative. Associations of these 4 polymorphisms (HF571253:g.103G&gt;A, HF571253:g.134G&gt;A, HF571253:g.179T&gt;C and HF571253:g.402_409delT) with meat performance traits were assessed in Czech Large White pigs. New polymorphisms in NREP gene were significantly associated with parameters of daily weight gain, lean meat and backfat thickness in Czech Large White pigs. Our primary study suggested that porcine NREP may play an important role in skeletal muscle growth, fat metabolism and meat performance traits.

Brucella abortus is a facultative intracellular Gram-negative bacterium that causes chronic persistent infections in humans and livestock. In this study, conventional bio-typing, multiple-locus variable-number tandem repeat analysis (MLVA), and whole-genome sequencing-single-nucleotide polymorphism (WGS-SNP) were used to investigate the molecular epidemiology characteristics of Brucella abortus strains in China and their relationships to world lineages. A total of 100 strains were collected from 1953 to 2013, suggesting that B. abortus circulated in China in the past five decades. Moreover, most strains were mainly distributed in the northwest area. During this period, seven biovars were found, indicating that B. abortus displayed a high diversity of biovars and that the main epidemic areas are in the northern provinces. Strains have high genetic diversity, and bruce07 is the most helpful locus for genotyping of this population. Moreover, 17 MLVA-11 genotypes were found; 13 of them are of known genotypes and four are unassigned genotypes, indicating that B. abortus in this study had several geographic origins. Still, strains from unassigned genotypes may originate from China. Many shared MLVA-16 genotypes were observed in strains from the same provinces in Northern China, which confirmed a brucellosis outbreak within northern regions. WGS-SNP analysis showed that eight Chinese strains formed a ladder-like phylogram (C. Ⅶ) with strains from nine countries, including Uganda, Iraq, Russia, Georgia, Spain, Italy, Egypt, Mongolia, and China; strains were introduced to these countries from a single source. Notably, Chinese strains were closely related to strains from Russia and Mongolia; frequent animal (cattle) trade and exchanges may promote this process. We will provide new and insightful information for strength surveillance and control of B. abortus brucellosis in China.

Characterization of genetic diversity, population structure and linkage disequilibrium is prerequisite for proper management of breeding programs and conservation of genetic resources. In this study, 186 chickpea genotypes including advanced “Kabuli” breeding lines and Iranian landrace “Desi” chickpea genotypes were genotyped using DArTseq-Based SNP markers. Out of 3339 SNPs, 1152 markers with known chromosomal position were selected for genome diversity analysis. The number of mapped SNP markers varied from 52 (LG8) to 378 (LG4), with an average of 144 SNPs per linkage group. The chromosome size that covered by SNPs varied from 16236.36 kbp (LG8) to 67923.99 kbp (LG5), while LG4 showed higher number of SNPs, with an average of 6.56 SNPs per Mbp. Polymorphism information content (PIC) value of SNP markers ranged from 0.05 to 0.50, with an average of 0.32, while the markers on LG4, LG6 and LG8 showed higher mean PIC value than average. Un-weighted Neighbor Joining cluster analysis and Bayesian-based model population structure grouped chickpea genotypes into four distinct clusters. Principal component analysis (PCoA) and Discriminant Analysis of Principal Component (DAPC) results were consistent with that of the cluster and population structure analysis. Linkage disequilibrium (LD) was extensive and LD decay in chickpea germplasm was relatively low. A few markers showed r²≥0.8, while 2961 pairs of markers showed complete LD (r²=1) and a huge LD block was observed on LG4. High genetic diversity and low kinship value between pairs of genotypes suggesting the presence of a high genetic diversity among studied chickpea genotypes. This study also demonstrated the efficiency of DArTseq-based SNP genotyping for large scale genome analysis in chickpea. The genotypic markers provided in this study are useful for various association mapping studies when combined with phenotypic data of different traits such as seed yield, abiotic and biotic stresses and therefore can be efficiently used in breeding programs to improve chickpea.

Potassium inwardly-rectifying channel, subfamily J, member 12 (KCNJ12) gene is one promising candidate for economic traits because of its crucial roles in myoblast development. Here, a missense mutation (Cys>Arg), was firstly detected to locate in exon 3 of KCNJ12 from three Chinese cattle breeds by DNA-pool sequencing. Then, we performed the association analysis of this SNP with stature in three Chinese cattle populations (n = 820). Significantly positive correlation was revealed by reduced animal general linear model and the genotype of CC is the most excellent genotype in three breeds. Further, we measured the expression profiling of the KCNJ12 gene in various cattle tissues and primary bovine skeletal muscle cells. Ubiquitous expression with high abundance in muscle was observed. Further, in primary bovine skeletal muscle cells, the KCNJ12 mRNA expression was gradually up-regulated in differentiation medium (DM) compared with that in growth medium (GM), suggesting that KCNJ12 gene is involved in bovine myocyte differentiation. Conclusively, KCNJ12 gene is a functional candidate gene which can be used as molecular marker for beef cattle breeding.

Genome-wide sequencing data play an important role in evaluating the genomic level differences between superior and poor-quality crop plants and improving our understanding of molecular association with desired traits. We analyzed the obtained 92,921,066 raw reads from genome-wide resequencing of Cucumis sativus var. hardwickii through in-silico approaches and mapped to the reference genome of Cucumis sativus to identify the genome-wide single nucleotide polymorphisms (SNPs) and Single nucleotide variations (SNV). Here, we report 19, 74,213 candidate SNPs including 1,33,468 insertions and 1,43,237 deletions and 75 Indels genome-wide. A total of 2228224 identified variants were classified into four classes including 0.01% sequence alteration, 5.94% insertion, 6.37% deletion and 87.66% SNV respectively. These variations can be a major source of phenotypic diversity and sequence variation within the species. During the present study these variants were also utilized to resolve orthologous relationships among the genomes of C. melo and C. sativus var. hardwickii. Overall, the discovery of SNPs and genomic variants may help predict the plant response to certain environmental factors and can be utilized to improve crop plants' economically important traits.

The Ponto-Caspian region is the main donor of invasive amphipods to freshwater ecosystems, with at least 13 species successfully established in European inland waters. Dikerogammarus spp. and Pontogammarus robustoides are among the most successful, due to their strong invasive impact on local biota. However, genomic knowledge on these invaders is scarce, while phylogeography and population genetics have been based on short fragments of mitochondrial markers or nuclear mi-crosatellites. In this study, we provide: (i) reconstruction of four mitogenomes for four invasive gammarids; (ii) comparison between the structure of the newly obtained mitogenomes and to those from literature; (iii) SNP calling rates for individual D. villosus and D. haemobaphes from different invasion sites across Europe; and (iv) the first time-calibrated full mitogenome reconstruction of several Ponto-Caspian taxa. We have sequenced, assembled and annotated four mitogenomes, each from D. villosus, D. hae-mobaphes, D. bispinosus and Pontogammarus robustoides. We found that, in comparison to other gammarids, the mitogenomes of Ponto-Caspian species show a translocation between the tRNA-E and tRNA-R positions. Phylogenetic reconstruction using the mitogenomes identified that Ponto-Caspian gammarids form a well-supported group that originated in the Miocene. Our study supports paraphyly in the family Gammaridae. These mitogenomes serve as vital genetic resources for the development of new markers for PCR-based identification methods and demographic studies.

The inter-subspecific crossing between indica and japonica subspecies in rice have been utilized to improve the yield potential of temperate rice. In this study, a comparative study of the genomic regions in the eight high-yielding varieties (HYVs) was conducted with those of the four non-HYVs. The Next-Generation Sequencing (NGS) mapping on the Nipponbare reference genome identified a total of 14 common genomic regions of japonica-originated alleles. Interestingly, the HYVs shared japonica-originated genomic regions on nine chromosomes, although they were developed through different breeding programs. A panel of 94 varieties was classified into four varietal groups with 38 single nucleotide polymorphism (SNP) markers from 38 genes residing in the japonica-originated genomic regions and 16 additional trait-specific SNPs. As expected, the japonica-originated genomic regions were only present in the japonica (JAP) and HYV groups, except for Chr4-1 and Chr4-2. The Wx gene, located within Chr6-1, was present in the HYV and JAP variety groups, while the yield-related genes were conserved as indica alleles in HYVs. The japonica-originated genomic regions and alleles shared by HYVs can be employed in molecular breeding programs to further develop the HYVs in temperate rice.

Development and deployment of wheat varieties with high yields, wide adaptability, good quality, multiple-resistance to abiotic and biotic stresses, and efficient response to fertilizers have greatly contributed to global wheat sustainable production. The genomic composition of key commercial wheat variety can help understand the genetic basis underlying the development of new variety and permit increased breeding efficiency. In this study, we report the chromosomal and genomic compositions of BN207, presently the leading wheat variety in the southern region of Huang-Huai River Valley, the most important wheat producing area in China through an integrated analysis using fluorescent in situ hybridization (FISH) and wheat 15 K SNP array. Our results showed that BN207 inherited 55.3% and 40.7% of its genome from its male parent BN64 and female parent ZM16, respectively, and generating 64 novel or recombined loci. Besides, we detected nine chromosomal variations in Bn207 and its parents and ten sister lines, and physically mapped two variations, the pericentric inversion of chromosome 6B, and large tandem repeat sequence block at the long arm of 5A, both had positive effects on agronomic traits, by integration of FISH and SNP loci recombination analyses. These results will provide a reference for breeding of high yield wheat varieties as BN207, and the application of founder parents BN64 and ZM16, which are being utilized frequently in wheat breeding programs in Henan Province and surrounding areas.

Background: As part of the Heart Healthy Lenoir Project, we developed a practice level intervention to improve blood pressure control. The goal of this study was: i) determine if single nucleotide polymorphisms (SNPs) that associate with blood pressure variation, identified in large case-control studies, are applicable to blood pressure control in subjects from a rural population; ii) measure the association of these SNPs with subjects’ responsiveness to the hypertension intervention; and iii) identify other SNPs that may help understand patient-specific responses to an intervention. Methods and Results: We used a combination of candidate SNPs and genome-wide analyses to test associations with either baseline systolic blood pressure (SBP) or change in systolic blood pressure one year after the intervention in two genetically defined ancestral groups: African Americans (AA) or Caucasian Americans (CAU). Of the 48 candidate SNPs, 13 SNPs associated with baseline SBP in our study; however, one candidate SNP, rs592582, also associated with a change in SBP after one year. Using our study data, we identified 4 and 15 additional loci that associated with a change in SBP in the AA and CAU groups, respectively. Our analysis of gene-age interactions identified genotypes associated with SBP improvement within different age groups of our populations. Moreover, our integrative analysis identified AQP4-AS1 and PADI2 as genes whose expression levels may contribute to the pleiotropy of complex traits involved in cardiovascular health and blood pressure regulation in response to an intervention targeting hypertension. Conclusions: Identification of SNPs associated with the success of a hypertension treatment intervention suggests that genetic factors in combination with age may contribute to an individual’s success in lowering SBP. If these findings prove to be applicable to other populations, the use of this genetic variation in making patient-specific interventions may help providers with making decisions to improve patient outcomes. Further investigation is required to determine the role of this genetic variance with respect to the management of hypertension such that more precise treatment recommendations may be made in the future as part of personalized medicine.

This study investigated the influence of single nucleotide polymorphisms (SNPs) in genes asso-ciated with the interferon pathway (IFNAR2 rs2236757), antiviral response (OAS1 rs10774671, OAS3 rs10735079), and viral entry (ACE2 rs2074192) on COVID-19 severity and their association with non-alcoholic fatty liver disease (MAFLD). We did not observe a significant association between the investigated SNPs and COVID-19 severity. While the IFNAR2 rs2236757 A allele correlated with higher creatinine levels upon admission and the G allele with lower band neu-trophils upon discharge, these findings require further investigation. The distribution of OAS gene polymorphisms (rs10774671, rs10735079 did not differ between MAFLD and non-MAFLD patients. Our study population's distribution of ACE2 rs2074192 genotypes and alleles differed from the European reference population. Overall, our findings suggest that these specific SNPs may not be major contributors to COVID-19 severity in our patient population, highlighting the potential role of other genetic factors and environmental influences.

Stalk rot caused by Fusarium fungi is one of the most widespread and devastating diseases of maize, and the introduction of resistant genotypes is one of the most effective strategies for controlling the disease. Breeding genotypes with genetically determined resistance will also allow less use of crop protection products. The aim of the research was to identify molecular markers and associated candidate genes determining maize plant resistance to Fusarium stalk rot. The plant material for the study consisted of 122 maize hybrids, which were sown in plots of 10 m2, in a complete randomized block design, in three repetitions, at two locations (Smolice: 51 42’ 58.904’’ N, 17 13’ 29.13’’ E and Kobierzyce: 50 58’ 19.411’’ N, 16 55’ 47.323’’ E). The analyzed genotypes were simultaneously subjected to next-generation sequencing using the Illumina platform. The results of the observation of the degree of infection and sequencing were used for association mapping, which ultimately resulted in the selection of 10 molecular markers important at both places. Among the identified markers, two SNP markers that are located inside candidate genes play an important role. Marker 4772836 is located inside the serine/threonine-protein kinase bsk3 gene, while marker 4765764 is located inside the histidine kinase 1 gene. Both genes can be associated with plant resistance to Fusarium stalk rot, and these genes can also be used in breeding programs to select resistant varieties.

This study investigated novel quantitative traits loci (QTLs) associated with the control of grain shape and size as well as grain weight in rice. We employed a joint strategy multiple GAPIT (Genome Association and Prediction Integrated Tool) models [(Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK)), Fixed and random model Circulating Probability Uniform (FarmCPU), Settlement of MLM Under Progressive Exclusive Relationship (SUPER), and General Linear Model (GLM)]–High Density SNP Chip DNA Markers (60,461) to conduct a Genome-Wide Association Study (GWAS). GWAS was performed using genotype and grain-related phenotypes of 143 recombinant inbred lines (RILs). Data show that parental lines (Ilpum and Tung Tin Wan Hein 1, TTWH1, Oryza sativa L., ssp. japonica and indica, respectively) exhibited divergent phenotypes for all analyzed grain traits), which was reflected in their derived population. GWAS results revealed the association between seven SNP Chip makers and quantitative trait loci (QTLs) for grain length, co-detected by all GAPIT models on (Chr) 1–3, 5, 7, and 11), were qGL1-1BFSG (AX-95918134, Chr1: 3820526 bp) explains 65.2%–72.5% of the phenotypic variance explained (PVE). In addition, qGW1-1BFSG (AX-273945773, Chr1: 5623288 bp) for grain width explains 15.5%–18.9% of PVE. Furthermore, BLINK or FarmCPU identified three QTLs for grain thickness independently, and explain 74.9% (qGT1Blink, AX-279261704, Chr1: 18023142 bp) and 54.9% (qGT2-1Farm, AX-154787777, Chr2: AX-154787777 bp) of the observed PVE. For t length-to-width ratio, the qLWR2BFSG (AX-274833045, Chr2: 10000097 bp) explains nearly 15.2%–32% of PVE for LWR. Likewise, the major QTL for thousand-grain weight (TGW) was detected on Chr6 (qTGW6BFSG, AX-115737727, 28484619 bp) and explains 32.8%–54% of PVE. The qTGW6BFSG QTL coincides with qGW6-1Blink for grain width and explained 32.8%–54% of PVE. Putative Candidate genes pooled from major QTLs for each grain traits have interesting annotated functions that require functional studies to elucidate their function in the control of grain size, shape, or weight in rice. Genome selection analysis proposed makers useful for downstream marker-assisted selection based on genetic merit of RILs.

Atopic dermatitis (AD) has been extensively investigated for genetic associations utilizing both candidate gene approaches and genome-wide scans. Here, we comprehensively evaluated the available literature to determine the association of candidate genes in AD to gain additional insight in the etiopathogenesis of the disease. We systematically screened all studies that explored the association between polymorphisms and AD risks in cases of European and Asian ancestry and synthesized the available evidence through random-effects meta-analysis. We identified 97 studies that met our inclusion/exclusion criteria that examined 17 candidate loci in Europeans and 14 candidate genes in Asians. We confirmed the significant associations between FLG variants in both European and Asian populations and AD risk, while additional synthesis of available data revealed novel loci mapped to IL18 and TGFB1 genes in Europeans and IL12RB1 and MIF in Asians, that have not yet been identified by genome-wide association studies. Our findings provide comprehensive evidence for AD risk loci in cases of both European and Asian ancestries, validating previous associations as well as revealing novel loci that could imply previously unexplored biological pathways.

The hexaploid bread wheat Triticum aestivum L. (2n = 6x = 42) and the tetraploid durum wheat Triticum durum (2n = 4x = 28) are two commercially the most important wheat species worldwide. These two species are components of the same gene pool, which evolved under different conditions, which made it possible to acquire different adaptations to a wider range of environmental conditions. Identification and characterization of introgressed fragments of one species in the genome of another can help in the search for new loci responsible for economically valuable traits. SNP microarrays provide information on the genotypes of thousands of positions throughout the genome. This information can be used to obtain the distribution of alleles of one species in the genome of another and to determine the location of introgressed fragments. In our work, we used genotyping data from the SNP microarray to identify durum wheat chromosome fragments containing bread wheat alleles in the offspring from crossing bread and durum wheat. We have studied the distribution of the genetic material of bread wheat in 15 combinations from crosses of bread and durum wheat. Introgressed fragments of bread wheat into the durum wheat genome were identified on chromosomes 1A, 1B, 4A, 5B, 6B, and 7A. The introgressed fragments showed polymorphism in different breeding lines. A functional enrichment analysis of genes in the introgression fragments was performed, which showed the presence of statistically significant enrichment of genes responsible for various molecular functions, biological processes and cellular components. The obtained data can be used to identify new QTL of economically valuable traits for obtaining durum wheat varieties with improved agronomic traits.

The current and projected climate change that is represented by increasing temperatures, humidity levels and irregular rainfall patterns, promotes the occurrence of preharvest sprouting (PHS) in wheat. PHS results in significant economic losses, globally, which necessitates the need for high-yielding cultivars with increased PHS tolerance, hence this study was conducted. The current study evaluated two doubled-haploid (DH) wheat populations of Tugela-Dn × Elands and Elands × Flamink across six environments in the Free State Province of South Africa to select genotypes with increased PHS tolerance and further map the underlying loci. Significant effects of DH lines (194) and environments (6) were observed for PHS tolerance. The results of this study validate previous findings that PHS is only expressed when environmental conditions are conducive. Quantitative trait loci (QTL) mapping using single nucleotide polymorphism (SNP) and silicoDArT markers revealed three additive QTL with major effects on chromosomes 5B and 7B, and these QTL were detected more than once, when conditions were favourable. These QTL explained a phenotypic variation (PVE) varying between 10.08% and 20.30% (LOD = 2.73 – 3.11). About 16.50% of DH lines performed to the level of Elands (the PHS-tolerant parent) and are recommended for further selection in a pre-breeding or breeding programme. The findings of the study are expected to facilitate the on-going breeding efforts for PHS tolerance in winter wheat.

Soybean seed sugars are among the most abundant beneficial compounds for human and animal consumption in soybean seeds. Higher seed sugars such as sucrose are desirable as it contributes to taste and flavor in soy-based food. Therefore, the objectives of this study were to use ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) soybean population (n=309) to identify quantitative trait loci (QTL) and candidate genes that control seed sugar (sucrose, stachyose, and raffinose) contents in two environments (North Carolina and Illinois) over two years (2018 and 2020). A total of 26 QTL that control seed sugars contents were identified and mapped on 16 soybean chromosomes (chrs.). Interestingly, five QTL regions were identified in both locations, Illinois and North Carolina, in this study on chrs. 2, 5, 13, 17, and 20. Amongst 57 candidate genes identified in this study, 16 were located within 10 Megabase (MB) of the identified QTL. Amongst them a cluster of four genes involved in the sugars’ pathway was collocated within 6 MB with two QTL that were detected in this study on chr. 17. Further functional validation of the identified genes could be beneficial in breeding programs to produce soybean lines with high beneficial sucrose and low raffinose family oligosaccharides.

To evaluate genetic variability and seedling plant response to a dominated Warrior (-) race of yellow rust in Northern and Central European germplasm, we used a population of 229 winter wheat cultivars and breeding lines for genome-wide association study (GWAS). A wide variation in yellow rust disease severity (based on infection types 1-9) was observed in this panel. Four breeding lines TS049 (from Austria), TS111, TS185, and TS229 (from Germany) and one cultivar TS158 (KWS Talent) from Germany were found to be resistant to Warrior (-) FS 53/20 and Warrior (-) G 23/19. GWAS identified five significant SNPs associated with yellow rust on chromosomes 1B, 2A, 5B, and 7A for Warrior (-) FS 53/20, while one SNP on chromosome 5B was associated with disease for Warrior (-) G 23/19. For Warrior (-) FS 53/20, we discovered a new QTL for yellow rust resistance associated with the marker Kukri_c5357_323 on chromosome 1B. The resistant allele G at the marker locus Kukri_c5357_323 on chromosome 1B and the susceptible allele T at the marker locus Excalibur_c17489_804 on chromosome 5B showed the largest effects (1.21 and 0.81, respectively) on the severity of yellow rust detected in Warrior (-) FS 53/20 and Warrior (-) G 23/19. Among 144 putative genes within the flanking sequence of the significant SNPs detected by GWAS, the function of the best candidate genes was determined as protein kinase activity and oxidoreductase activity. Our results provide the basis for knowledge-based resistance breeding in the face of the enormous impact of the Warrior (-) race on wheat production in Europe.

The experiments described in this research article were designed to test the effect of rare variants into genomic prediction in dairy cattle. Common polymorphisms are able to explain only a small proportion of the underlying genetic variation of complex phenotypes. Variants representing functional mutations with large effects on complex phenotypes are expected to be rare due to natural (humans) or artificial (livestock) selection pressure. Therefore, it is important to check whether the use of rare variants could increase the accuracy of ranking of animals by providing the tool for more precise differentiation among the bulls with high additive genetic merit. The goal of our study was to verify whether including rare variants in a genomic selection model allows for a more accurate description of the additive genetic background of traits under selection in dairy cattle. We used the linear mixed model for comparison SNP estimates for Holstein-Friesian cattle of the two data sets – a set containing only single nucleotide polymorphisms defined by minor allele frequency ≥ 0.01, which is routinely used in the Polish genomic evaluation system (46,216 SNPs), and a set containing SNPs selected based only on the call rate (54,378 SNPs). Based on the SNP estimates we also calculated DGV and GEBV and compared them between both data sets. In all the analyses we used production, fertility, conformation and udder health traits. We also assessed the time required for the two most computationally demanding components of genomic selection: preparing genotype data, and estimation of SNP effects between those two data sets. The results of our study indicated that the analysis including rare variants resulted in changes in the individual ranking of the top 100 male and female candidates, but had no effect on the outcome of the quality of EBV prediction as expressed by the Interbull validation test.

Endometriosis is a chronic neuro-inflammatory disorder the defining feature of which is the growth of tissue (lesions) that resembles the endometrium in sites outside the uterus. Estimates of prevalence typically quote rates of ~10% of women of reproductive age, equating to ~190 million women world-wide. Three subtypes of endometriosis are usually considered when discussing the aetiology of the disorder - superficial peritoneal, ovarian (endometrioma cysts), and deep (infiltrating). Genetic, hormonal and immunological factors have all been proposed as contributing to risk factors associated with the development of lesions. Twin studies report the heritable component of endometriosis as ~50%. Genome wide association studies (GWAS) have been conducted allowing unbiased scanning of the genome for single nucleotide polymorphisms (SNPs) in many thousands of individuals. These studies have identified SNPs that appear over-represented in patients with endometriosis, particularly those with more extensive disease (stage III/IV). Amongst the larger scale GWAS there has been replication of SNPs near genes involved in oestrogen and other signalling pathways including ESR1 (oestrogen receptor alpha), GREB1, HOXA10, WNT4 and MAPK kinase signalling. The results from patients with endometriosis have also provided an opportunity to make comparisons with GWAS conducted on other patient cohorts including those with reproductive traits (age at menarche) and disorders (fibroids, endometrial and ovarian cancer) and conditions that are reported by women with endometriosis (migraine, depression). These comparative studies have highlighted some shared genetically-controlled biological mechanisms, including hormone-regulated pathways which might explain the co-occurrence of endometriosis with these disorders. In summary, unbiased genetic analysis has provided new insights into the genetic factors that may contribute to increased risk of developing endometriosis. New studies are needed to broaden the range of patients contributing to these datasets and to improve integration with non-genomic and tissue expression data before their full potential for diagnosis and improvements in patient care can be fully realised.

Personalized medicine is an aspect of the P4 medicine (predictive, preventive, personalized and participatory) based precisely on the customization of all medical characters of each subject. In personalized medicine, the development of medical treatments and drugs is tailored to the individual characteristics and needs of each subject, according to the study of diseases at different scales from genotype to phenotype scale. To make concrete the goal of personalized medicine, it is necessary to employ high-throughput methodologies such as Next Generation Sequencing (NGS), Genome-Wide Association Studies (GWAS), Mass Spectrometry or Microarrays, that are able to investigate a single disease from a broader perspective. For example, by using genotyping microarrays (e.g. collections of Single Nucleotide Polymorphism - SNP) it is possible to uncover the reasons (i.e. mutation in genes) because a treatment works properly in some patients (for example absence of mutated genes), but it does not work (presence of mutated genes) in others. A side effect of high-throughput methodologies is the massive amount of data produced for each single experiment, that poses several challenges (e.g. high execution time and required memory) to bioinformatic software. Thus a main requirement of modern bioinformatic software is the use of good software engineering methods and efficient programming techniques, able to face those challenges, that include the use of parallel programming and efficient and compact data structures. Thus, to exploit all the potential of this massive amount of data in the short possible time (before that data becomes obsolete), the necessity to develop parallel software tools for efficient data collection and analysis arise. Moreover, due to the heterogeneity of the data produced by the different kinds of experimental platforms, it is necessary to automatize in a comprehensive software pipeline, the various steps that compose a bioinformatic analysis, such as: the preprocessing of raw data to remove noise or corrupted data; the annotation of data with external knowledge (e.g. Gene Ontology), and the integration of molecular data with clinical data. It should be noted that such steps are necessary to make statistical or data mining analysis more effective. This paper presents the design and the experimentation of a comprehensive software pipeline, named microPipe, for the preprocessing, annotation and analysis of microarray-based SNP genotyping data. A case study in pharmacogenomics is presented. The main advantages of using microPipe are: the reduction of errors that may happen when trying to make data compatible among different tools; the possibility to analyze in parallel huge datasets; the easy annotation and integration of data.

New flaxseed cultivars differing in seed mucilage content (MC) with low hull content (HC) represent an attractive option to simultaneously target the food and feed markets. Here, a genome-wide association study (GWAS) was conducted for MC and HC in 200 diverse flaxseed accessions genotyped with 1.7 million SNP markers. The data obtained for MC and HC indicated a broad phenotypic variation and high (~70%) and a moderate (~49%) narrow sense heritability, respectively. MC and HC did not differ statistically between fiber and oil morphotypes, but yellow-seeded accessions had 2.7% less HC than brown-seeded ones. The genome wide linkage disequilibrium (LD) decayed to r2 = 0.1 at a physical distance of ~100 Kb. Seven and four QTL were identified for MC and HC, respectively. Promising candidate genes included Linum usitatissimum orthologs of the Arabidopsis thaliana genes TRANSPARENT TESTA 8, SUBTILISIN-LIKE SERINE PROTEASE, GALACTUROSYL TRANSFERASE-LIKE 5, MUCILAGE-MODIFIED 4, AGAMOUS-LIKE MADS-BOX PROTEIN AGL62, GLYCOSYL HYDROLASE FAMILY 17 and UDP-GLUCOSE FLAVONOL 3-O-GLUCOSYLTRANSFERASE that have been shown to play a role in mucilage synthesis and release, seed coat development and anthocyanin biosynthesis in A. thaliana were identified. The favorable alleles will be useful in flaxseed breeding towards the goal of achieving the ideal flaxseed cultivars for food and feed by genomic-based breeding.

Cervical cancer is the fourth common cancer amongst women worldwide. Environmental factors such as smoking and obesity, and recurrent infection by high-risk human papillomavirus subtypes are known to promote progression towards invasive cervical disease. Infection by high-risk HPV is necessary in most cases but not sufficient to develop invasive cervical cancer. Despite a predicted genetic heritability of between 27-36%, known genetic susceptibility loci that may be tumorigenic or influence host response to infection, only account for a small fraction of heritable risk factors so far. Various biobank-driven population based studies and meta-analyses have found corroborative evidence for several risk variants at the 6p21.3 locus (HLA), while many reports of variants outside the HLA region remain to be validated in other cohorts. Here, we review cervical cancer susceptibility variants arising from recent genome-wide association studies and meta-analysis in large cohorts and propose 2q14 (PAX8), 17q12 (GSDMB), and 5p15.33 (CLPTM1L) as consistently replicated non-HLA cervical cancer susceptibility loci. We further discuss the available evidence for these loci, knowledge gaps, future perspectives, and the potential impact of these findings on precision medicine strategies to combat cervical cancer.

Achieving high-yield potential is always the ultimate objective of any breeding program. However, various abiotic stresses like salinity, drought, cold, flood, and heat hampered rice productivity tremendously. Salinity is one of the most important abiotic stresses that adversely affect rice grain yield. The present investigation was undertaken to dissect new genetic loci, which are responsible for salt tolerance at the early seedling stage in rice. A bi-parental mapping population (F2:3) was developed from the cross between BRRI dhan28/Akundi, where BRRI dhan28 (BR28) is a salt-sensitive irrigated (boro) rice mega variety and Akundi is a highly salinity tolerant Bangladeshi origin indica rice landrace that is utilized as a donor parent. We report stable QTLs for salt tolerance from a common donor (Akundi) irrespective of two different genetic backgrounds (BRRI dhan49/Akundi and BRRI dhan28/Akundi). A robust 1k-Rice Custom Amplicon (1k-RiCA) SNP marker genotyping platform was used to genotype this bi-parental population. After eliminating markers with high segregation distortion, 886 polymorphic SNPs built a genetic linkage map covering 1526.5 cM of whole rice genome with an average SNP density of 1.72 cM for the 12 genetic linkage groups. A total of 12 QTLs for nine different salt tolerance-related traits were identified using QGene and inclusive composite interval mapping of additive and dominant QTL (ICIM-ADD) under salt stress on seven different chromosomes. All of these 12 new QTLs found unique, as no other map from the previous study has reported these QTLs in the similar chromosomal location and found them different from extensively studied Saltol, SKC1, OsSalT and salT locus. Twenty-eight significant digenic/epistatic interactions identified between chromosomal regions linked to or unlinked to QTLs. Akundi acts like a new alternate donor source of salt tolerance except for other usually known donors like Nona Bokra, Pokkali, Capsule, and Hasawi used in salt tolerance genetic analysis and breeding programs worldwide, including Bangladesh. Integration of the seven novel and stable QTLs (qSES1, qSL1, qRL1, qSUR1, qSL8, qK8, qK1) reported in this investigation will expedite the cultivar development that is highly tolerant to salt stress.

In this work we looked for a stable and accurate procedure to perform feature selection in datasets with a much higher number of predictors than individuals, as in Genome-Wide Association Studies. Due to the instability in feature selection when many potential predictors are measured, a variable selection procedure is proposed that combines several replications of shrinkage regression models. A weighted formulation is used to define the final predictors. The procedure is applied to investigate Single Nucleotide Polymorphisms (SNPs) predictors associated to Alzheimer’s disease in the Alzheimer’s disease Neuroimaging Initiative (ADNI) dataset. Two data scenarios are investigated: one considering only the set of SNPs and another with the covariates age, sex, educational level and APOE4 genotype. The SNP rs2075650 and the APOE4 genotype are given as risk factors for AD, which is in line with the literature, and other four new SNPs are pointed, opening new hypotheses for in vivo analyses. These experiments demonstrate the potential of the new method for stable feature selection.

Recurrent pregnancy loss (RPL) affects around 2 % of women of reproductive age. Primary RPL is defined by ≥2 pregnancy losses and no normal birth delivery. In secondary RPL, the losses are after a normal pregnancy and delivery. Most cases have no clear aetiology, although primary cases are the most complex. Several gene polymorphisms have been associated with RPL. Some polymorphisms are increased in women of Asian or Caucasian race. In admixed RPL populations, the information on possible genetic links is scarce and contradictory. The study aimed to assess the frequency of two SNP in different enzymes involved in medical conditions observed during pregnancy. Microsomal epoxy hydrolase (mEPH) is involved in detoxifying xenobiotics. It is present in ovaries, and it is hormonally regulated. The endothelial nitric oxide synthase forms nitric oxide from arginine and is involved in vascular tone. Two SNPs, rs1051740 and rs1799983, were assessed. The study included 26 controls and 63 primary RPL patients. Significant differences were observed in the frequencies of both SNP (p<0.05). The frequency of mutated alleles was higher in patients. Double mutated homozygotes were encountered only in RLP patients (p<0.05). Genetic polymorphisms rs1051740 and rs1799983 may be involved in primary RPL in the Venezuelan admix population. Genetic studies could provide crucial information on the aetiology of primary RPL.

Analysis of complex DNA mixtures is limited by the selected genetic markers characterized and assay technology. Small panels of short tandem repeats (STRs) are the current standards in most countries. Extension of STRs with hundreds of single nucleotide polymorphisms (SNPs) is now commercially available. The current set of extension SNPs focus on phenotypic and biogeographic ancestry informative SNPs. Larger panels with thousands of SNPs have been developed that can identify up to 10 contributors to forensic DNA samples. Herein, multiple sets of SNPs were selected with the focus of increasing the upper limit of detectable contributors. Larger SNP panel sets with lower minor allele frequency (MAF) alleles can detect large numbers of contributors to in silico mixtures of randomly selected profiles from the 1,000 Genomes project. These results provide a path to enable characterization of complex DNA mixtures that are currently impossible to analyse.

The extracellular matrix (ECM) is earning an increasingly relevant role in many disease states and the process of aging. Analyzing these disease states is possible with GWAS and PheWAS methodology, and through our analysis, we aimed to explore the relationships between polymorphisms in the compendium of ECM genes (i.e., matrisome genes) in various disease states. A significant contribution on the part of the ECM polymorphisms is evident in many varying types of diseases, particularly those in the core matrisome genes. Our results confirm previous links to connective tissue disorders, but also unearth new and underexplored relationships with neurological, psychiatric, and age-related disease states. Upon analysis of drug indications for gene-disease relationships, we identified numerous targets that may be repurposed for age-related pathology. The identification of ECM polymorphisms and their contribution to disease plays an integral role in future therapeutic developments, drug repurposing, precision medicine, and personalized care.

Quantitative trait loci (QTL) are genomic regions associated with phenotype variation of quantitative traits in a population. To date, a total of 267 QTL for 29 quantitative traits have been reported in 13 studies on flax. Of these, 200 QTL from 12 studies were identified based on genetic maps, scaffold sequences, or pre-released chromosome-scale pseudomolecules. Molecular markers for QTL identification differed across studies but were mainly based on simple sequence repeat (SSR) or single nucleotide polymorphism (SNP) markers. This article provides methods with software tools and database files to uniquely map SSR and SNP markers from different references onto the recently released chromosome-scale pseudomolecules. Using these methods, 195 QTL were successfully sorted onto the 15 flax chromosomes and grouped into 133 co-located QTL clusters. Mapping of QTL from different studies to the same reference enables comparisons and facilitates genome-wide QTL analysis, candidate gene scanning, and breeding applications.

Hubei, Hunan and Henan Provinces are located in Central China, a region with extensive transport networks and trade. Bursaphelenchus xylophilus, the causative agent of pine wilt disease, is spreads mainly through human activities. In order to further understand the genetic structure of PWN in Central China, we studied the genetic information of PWN populations in this region and compared the genetic relationship with strains from Guangdong and Jiangsu provinces. We found that the HB (Hubei) 15, HEN (Henan) 20, HN (Hunan) 07, HN08 and HN10 had significantly more SNPs and homozygotes than other strains from Central China, and their most frequent mutant genotypes also differed from other strains. The clustering results indicated that HB15, HEN 20, HN07, HN08 and HN10 were genetically distinct from other strains and closely related to Guangdong strains. We also observed significant genetic variation among strains in Henan province, suggesting that some of them might have different transmission sources than those from Hubei and Hunan provinces. The results provide a basis for tracing the origin and spread of PWD in China.

A genome-wide association study (GWAS) was performed on a set of 260 lines which belong to three different bi-parental flax mapping populations. These lines were sequenced to an averaged genome coverage of 19× using the Illumina Hi-Seq platform. Phenotypic data for 11 seed yield and oil quality traits were collected in eight year/location environments. A total of 17,288 single nucleotide polymorphisms were identified, which explained more than 80% of the phenotypic variation for days to maturity (DTM), iodine value (IOD), palmitic (PAL), stearic, linoleic (LIO) and linolenic (LIN) acid contents. Twenty-three unique genomic regions associated with 33 QTL for the studied traits were detected, thereby validating four genomic regions previously identified. The 33 QTL explained 48-73% of the phenotypic variation for oil content, IOD, PAL, LIO and LIN but only 8-14% for plant height, DTM and seed yield. A genome-wide selective sweep scan for selection signatures detected 114 genomic regions that accounted for 7.82% of the flax pseudomolecule and overlapped with the 11 GWAS-detected genomic regions associated with 18 QTL for 11 traits. The results demonstrate the utility of GWAS combined with selection signatures for dissection of the genetic structure of traits and for pinpointing genomic regions for breeding improvement.