Dissection of quantitative trait nucleotides and candidate genes associated with agronomic and yield-related traits under drought stress in rapeseed varieties: integration of genome-wide association study and transcriptomic analysis.

Introduction: An important strategy to combat yield loss challenge is the development of varieties with increased tolerance to drought to maintain production. Improvement of crop yield under drought stress is critical to global food security. Methods: In this study, we performed multiomics analysis in a collection of 119 diverse rapeseed (Brassica napus L.) varieties to dissect the genetic control of agronomic traits in two watering regimes [well-watered (WW) and drought stress (DS)] for 3 years. In the DS treatment, irrigation continued till the 50% pod development stage, whereas in the WW condition, it was performed throughout the whole growing season. Results: The results of the genome-wide association study (GWAS) using 52,157 single-nucleotide polymorphisms (SNPs) revealed 1,281 SNPs associated with traits. Six stable SNPs showed sequence variation for flowering time between the two irrigation conditions across years. Three novel SNPs on chromosome C04 for plant weight were located within drought tolerance-related gene ABCG16, and their pleiotropically effects on seed weight per plant and seed yield were characterized. We identified the C02 peak as a novel signal for flowering time, harboring 52.77% of the associated SNPs. The 288-kbps LD decay distance analysis revealed 2,232 candidate genes (CGs) associated with traits. The CGs BIG1-D, CAND1, DRG3, PUP10, and PUP21 were involved in phytohormone signaling and pollen development with significant effects on seed number, seed weight, and grain yield in drought conditions. By integrating GWAS and RNA-seq, 215 promising CGs were associated with developmental process, reproductive processes, cell wall organization, and response to stress. GWAS and differentially expressed genes (DEGs) of leaf and seed in the yield contrasting accessions identified BIG1-D, CAND1, and DRG3 genes for yield variation. Discussion: The results of our study provide insights into the genetic control of drought tolerance and the improvement of marker-assisted selection (MAS) for breeding high-yield and drought-tolerant varieties.

Distribution, frequency and molecular basis of clethodim and quizalofop resistance in brome grass (Bromus diandrus).

BACKGROUND: Brome grass (Bromus diandrus Roth) is prevalent in the southern and western cropping regions of Australia, where it causes significant economic damage. A targeted herbicide resistance survey was conducted in 2020 by collecting brome grass populations from 40 farms in Western Australia and subjecting these samples to comprehensive herbicide screening. One sample (population 172-20), from a field that had received 12 applications of clethodim over 20 years of continuous cropping, was found to be highly resistant to the acetyl-CoA carboxylase (ACCase)-inhibiting herbicides clethodim and quizalofop, and so the molecular basis of resistance was investigated. RESULTS: All 31 individuals examined from population 172-20 carried the same resistance-endowing point mutation causing an aspartate-to-glycine substitution at position 2078 in the translated ACCase protein sequence. A wild-type susceptible population and the resistant population had similar expression levels of plastidic ACCase genes. The level of resistance to quizalofop, either standalone or in mixture with clethodim, in population 172-20 was lower under cooler growing conditions. CONCLUSION: Target-site resistance to ACCase-inhibiting herbicides, conferred by one ACCase mutation, was selected in all tested brome plants infesting a field with a history of repeated clethodim use. This mutation appears to have been fixed in the infesting population. Notably, clethodim resistance in this population was not detected by the farmer, and a high future incidence of quizalofop resistance is anticipated. Herbicide resistance testing is essential for the detection of evolving weed resistance issues and to inform effective management strategies. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

DNABERT-based explainable lncRNA identification in plant genome assemblies.

Long non-coding ribonucleic acids (lncRNAs) have been shown to play an important role in plant gene regulation, involving both epigenetic and transcript regulation. LncRNAs are transcripts longer than 200 nucleotides that are not translated into functional proteins but can be translated into small peptides. Machine learning models have predominantly used transcriptome data with manually defined features to detect lncRNAs, however, they often underrepresent the abundance of lncRNAs and can be biased in their detection. Here we present a study using Natural Language Processing (NLP) models to identify plant lncRNAs from genomic sequences rather than transcriptomic data. The NLP models were trained to predict lncRNAs for seven model and crop species (Zea mays, Arabidopsis thaliana, Brassica napus, Brassica oleracea, Brassica rapa, Glycine max and Oryza sativa) using publicly available genomic references. We demonstrated that lncRNAs can be accurately predicted from genomic sequences with the highest accuracy of 83.4% for Z. mays and the lowest accuracy of 57.9% for B. rapa, revealing that genome assembly quality might affect the accuracy of lncRNA identification. Furthermore, we demonstrated the potential of using NLP models for cross-species prediction with an average of 63.1% accuracy using target species not previously seen by the model. As more species are incorporated into the training datasets, we expect the accuracy to increase, becoming a more reliable tool for uncovering novel lncRNAs. Finally, we show that the models can be interpreted using explainable artificial intelligence to identify motifs important to lncRNA prediction and that these motifs frequently flanked the lncRNA sequence.

Genetic and molecular analysis of stem rot (Sclerotinia sclerotiorum) resistance in Brassica napus (canola type).

Identifying the molecular and genetic basis of resistance to Sclerotinia stem rot (Sclerotinia sclerotiorum) is critical for developing long-term and cost-effective management of this disease in rapeseed/canola (Brassica napus). Current cultural or chemical management options provide, at best, only partial and/or sporadic control. Towards this, a B. napus breeding population (Mystic x Rainbow), including the parents, F1, F2, BC1P1 and BC1P2, was utilized in a field study to determine the inheritance pattern of Sclerotinia stem rot resistance (based on stem lesion length, SLL). Broad sense heritability was 0.58 for SLL and 0.44 for days to flowering (DTF). There was a significant negative correlation between SLL and stem diameter (SD) (r = -0.39) and between SLL and DTF (r = -0.28), suggesting co-selection of SD and DTF traits, along with SLL, should assist in improving overall resistance. Non-additive genetic variance was evident for SLL, DTF, and SD. In a genome wide association study (GWAS), a significant quantitative trait locus (QTL) was identified for SLL. Several putative candidate marker trait associations (MTA) were located within this QTL region. Overall, this study has provided valuable new understanding of inheritance of resistance to S. sclerotiorum, and has identified QTL, MTAs and transgressive segregants with high-level resistances. Together, these will foster more rapid selection for multiple traits associated with Sclerotinia stem rot resistance, by enabling breeders to make critical choices towards selecting/developing cultivars with enhanced resistance to this devastating pathogen.

The conservation of gene models can support genome annotation.

Many genome annotations include false-positive gene models, leading to errors in phylogenetic and comparative studies. Here, we propose a method to support gene model prediction based on evolutionary conservation and use it to identify potentially erroneous annotations. Using this method, we developed a set of 15,345 representative gene models from 12 legume assemblies that can be used to support genome annotations for other legumes.

crosshap: R package for local haplotype visualization for trait association analysis.

SUMMARY: Genome-wide association studies (GWAS) excels at harnessing dense genomic variant datasets to identify candidate regions responsible for producing a given phenotype. However, GWAS and traditional fine-mapping methods do not provide insight into the complex local landscape of linkage that contains and has been shaped by the causal variant(s). Here, we present crosshap, an R package that performs robust density-based clustering of variants based on their linkage profiles to capture haplotype structures in a local genomic region of interest. Following this, crosshap is equipped with visualization tools for choosing optimal clustering parameters (ɛ) before producing an intuitive figure that provides an overview of the complex relationships between linked variants, haplotype combinations, phenotype, and metadata traits. AVAILABILITY AND IMPLEMENTATION: The crosshap package is freely available under the MIT license and can be downloaded directly from CRAN with R >4.0.0. The development version is available on GitHub alongside issue support (https://github.com/jacobimarsh/crosshap). Tutorial vignettes and documentation are available (https://jacobimarsh.github.io/crosshap/).

Genome composition in Brassica interspecific hybrids affects chromosome inheritance and viability of progeny.

Interspecific hybridization is widespread in nature and can result in the formation of new hybrid species as well as the transfer of traits between species. However, the fate of newly formed hybrid lineages is relatively understudied. We undertook pairwise crossing between multiple genotypes of three Brassica allotetraploid species Brassica juncea (2n = AABB), Brassica carinata (2n = BBCC), and Brassica napus (2n = AACC) to generate AABC, BBAC, and CCAB interspecific hybrids and investigated chromosome inheritance and fertility in these hybrids and their self-pollinated progeny. Surprisingly, despite the presence of a complete diploid genome in all hybrids, hybrid fertility was very low. AABC and BBAC first generation (F1) hybrids both averaged ~16% pollen viability compared to 3.5% in CCAB hybrids: most CCAB hybrid flowers were male-sterile. AABC and CCAB F1 hybrid plants averaged 5.5 and 0.5 seeds per plant, respectively, and BBAC F1 hybrids ~56 seeds/plant. In the second generation (S1), all confirmed self-pollinated progeny resulting from CCAB hybrids were sterile, producing no self-pollinated seeds. Three AABC S1 hybrids putatively resulting from unreduced gametes produced 3, 14, and 182 seeds each, while other AABC S1 hybrids averaged 1.5 seeds/plant (0-8). BBAC S1 hybrids averaged 44 seeds/plant (range 0-403). We also observed strong bias towards retention rather than loss of the haploid genomes, suggesting that the subgenomes in the Brassica allotetraploids are already highly interdependent, such that loss of one subgenome is detrimental to fertility and viability. Our results suggest that relationships between subgenomes determine hybridization outcomes in these species.

Comparative pangenome analyses provide insights into the evolution of Brassica rapa resistance gene analogues (RGAs).

Brassica rapa is grown worldwide as economically important vegetable and oilseed crop. However, its production is challenged by yield-limiting pathogens. The sustainable control of these pathogens mainly relies on the deployment of genetic resistance primarily driven by resistance gene analogues (RGAs). While several studies have identified RGAs in B. rapa, these were mainly based on a single genome reference and do not represent the full range of RGA diversity in B. rapa. In this study, we utilized the B. rapa pangenome, constructed from 71 lines encompassing 12 morphotypes, to describe a comprehensive repertoire of RGAs in B. rapa. We show that 309 RGAs were affected by presence-absence variation (PAV) and 223 RGAs were missing from the reference genome. The transmembrane leucine-rich repeat (TM-LRR) RGA class had more core gene types than variable genes, while the opposite was observed for nucleotide-binding site leucine-rich repeats (NLRs). Comparative analysis with the B. napus pangenome revealed significant RGA conservation (93%) between the two species. We identified 138 candidate RGAs located within known B. rapa disease resistance QTL, of which the majority were under negative selection. Using blackleg gene homologues, we demonstrated how these genes in B. napus were derived from B. rapa. This further clarifies the genetic relationship of these loci, which may be useful in narrowing-down candidate blackleg resistance genes. This study provides a novel genomic resource towards the identification of candidate genes for breeding disease resistance in B. rapa and its relatives.

Genetic Mapping, Candidate Gene Identification and Marker Validation for Host Plant Resistance to the Race 4 of Fusarium oxysporum f. sp. cubense Using Musa acuminata ssp. malaccensis.

Fusarium wilt of banana is a devastating disease that has decimated banana production worldwide. Host resistance to Fusarium oxysporum f. sp. Cubense (Foc), the causal agent of this disease, is genetically dissected in this study using two Musa acuminata ssp. Malaccensis segregating populations, segregating for Foc Tropical (TR4) and Subtropical (STR4) race 4 resistance. Marker loci and trait association using 11 SNP-based PCR markers allowed the candidate region to be delimited to a 12.9 cM genetic interval corresponding to a 959 kb region on chromosome 3 of 'DH-Pahang' reference assembly v4. Within this region, there was a cluster of pattern recognition receptors, namely leucine-rich repeat ectodomain containing receptor-like protein kinases, cysteine-rich cell-wall-associated protein kinases, and leaf rust 10 disease-resistance locus receptor-like proteins, positioned in an interspersed arrangement. Their transcript levels were rapidly upregulated in the resistant progenies but not in the susceptible F2 progenies at the onset of infection. This suggests that one or several of these genes may control resistance at this locus. To confirm the segregation of single-gene resistance, we generated an inter-cross between the resistant parent 'Ma850' and a susceptible line 'Ma848', to show that the STR4 resistance co-segregated with marker '28820' at this locus. Finally, an informative SNP marker 29730 allowed the locus-specific resistance to be assessed in a collection of diploid and polyploid banana plants. Of the 60 lines screened, 22 lines were predicted to carry resistance at this locus, including lines known to be TR4-resistant, such as 'Pahang', 'SH-3362', 'SH-3217', 'Ma-ITC0250', and 'DH-Pahang/CIRAD 930'. Additional screening in the International Institute for Tropical Agriculture's collection suggests that the dominant allele is common among the elite 'Matooke' NARITA hybrids, as well as in other triploid or tetraploid hybrids derived from East African highland bananas. Fine mapping and candidate gene identification will allow characterization of molecular mechanisms underlying the TR4 resistance. The markers developed in this study can now aid the marker-assisted selection of TR4 resistance in breeding programs around the world.

Genetic factors inherited from both diploid parents interact to affect genome stability and fertility in resynthesized allotetraploid Brassica napus.

Established allopolyploids are known to be genomically stable and fertile. However, in contrast, most newly resynthesized allopolyploids are infertile and meiotically unstable. Identifying the genetic factors responsible for genome stability in newly formed allopolyploid is key to understanding how 2 genomes come together to form a species. One hypothesis is that established allopolyploids may have inherited specific alleles from their diploid progenitors which conferred meiotic stability. Resynthesized Brassica napus lines are often unstable and infertile, unlike B. napus cultivars. We tested this hypothesis by characterizing 41 resynthesized B. napus lines produced by crosses between 8 Brassica rapa and 8 Brassica oleracea lines for copy number variation resulting from nonhomologous recombination events and fertility. We resequenced 8 B. rapa and 5 B. oleracea parent accessions and analyzed 19 resynthesized lines for allelic variation in a list of meiosis gene homologs. SNP genotyping was performed using the Illumina Infinium Brassica 60K array for 3 individuals per line. Self-pollinated seed set and genome stability (number of copy number variants) were significantly affected by the interaction between both B. rapa and B. oleracea parental genotypes. We identified 13 putative meiosis gene candidates which were significantly associated with frequency of copy number variants and which contained putatively harmful mutations in meiosis gene haplotypes for further investigation. Our results support the hypothesis that allelic variants inherited from parental genotypes affect genome stability and fertility in resynthesized rapeseed.

Diversity of fatty acid biosynthesis genes across the soybean pangenome.

Soybean (Glycine max) is a major crop that contributes more than half of global oilseed production. Much research has been directed towards improvement of the fatty acid profile of soybean seeds through marker assisted breeding. Recently published soybean pangenomes, based on thousands of soybean lines, provide an opportunity to identify new alleles that may be involved in fatty acid biosynthesis. In this study, we identify fatty acid biosynthesis genes in soybean pangenomes based on sequence identity with known genes and examine their sequence diversity across diverse soybean collections. We find three possible instances of a gene missing in wild soybean, including FAD8 and FAD2-2D, which may be involved in oleic and linoleic acid desaturation, respectively, although we recommend follow-up research to verify the absence of these genes. More than half of the 53 fatty acid biosynthesis genes identified contained missense variants, including one linked with a previously identified QTL for oil quality. These variants were present in multiple studies based on either short read mappings or alignment of reference grade genomes. Missense variants were found in previously characterized genes including FAD2-1A and FAD2-1B, both of which are involved in desaturation of oleic acid, as well as uncharacterized candidate fatty acid biosynthesis genes. We find that the frequency of missense alleles in fatty acid biosynthesis genes has been reduced significantly more than the global average frequency of missense mutations during domestication, and missense variation in some genes is near absent in modern cultivars. This could be due to the selection for fatty acid profiles in seed, though future work should be conducted towards understanding the phenotypic impacts of these variants.

Diversity of Phytosterols in Leaves of Wild Brassicaceae Species as Compared to Brassica napus Cultivars: Potential Traits for Insect Resistance and Abiotic Stress Tolerance.

Phytosterols are natural compounds found in all higher plants that have a wide variety of roles in plant growth regulation and stress tolerance. The phytosterol composition can also influence the development and reproductive rate of strict herbivorous insects and other important agronomic traits such as temperature and drought tolerance in plants. In this study, we analysed the phytosterol composition in 18 Brassica napus (Rapeseed/canola) cultivars and 20 accessions belonging to 10 related wild Brassicaceae species to explore diverse and novel phytosterol profiles. Plants were grown in a controlled phytotron environment and their phytosterols were analysed using a saponification extraction method followed by GC-MS from the leaf samples. The B. napus cultivars showed slight diversity in eight phytosterols (>0.02%) due to the genotypic effect, whereas the wild accessions showed significant variability in their phytosterol profiles. Of interest, a number of wild accessions were found with high levels of campesterol (HIN20, HIN23, HUN27, HIN30, SARS2, and UPM6563), stigmasterol (UPM6813, UPM6563, ALBA17, and ALBA2), and isofucosterol (SARS12, SAR6, and DMU2). These changes in individual phytosterols, or ratios of phytosterols, can have a significant implication in plant tolerance to abiotic stress and plant insect resistance properties, which can be used in breeding for crop improvement.

CRISPR-Based Genome Editing Tools: An Accelerator in Crop Breeding for a Changing Future.

Genome editing is an important strategy to maintain global food security and achieve sustainable agricultural development. Among all genome editing tools, CRISPR-Cas is currently the most prevalent and offers the most promise. In this review, we summarize the development of CRISPR-Cas systems, outline their classification and distinctive features, delineate their natural mechanisms in plant genome editing and exemplify the applications in plant research. Both classical and recently discovered CRISPR-Cas systems are included, detailing the class, type, structures and functions of each. We conclude by highlighting the challenges that come with CRISPR-Cas and offer suggestions on how to tackle them. We believe the gene editing toolbox will be greatly enriched, providing new avenues for a more efficient and precise breeding of climate-resilient crops.

Legume-wide comparative analysis of pod shatter locus PDH1 reveals phaseoloid specificity, high cowpea expression, and stress responsive genomic context.

Pod dehiscence is a major source of yield loss in legumes, which is exacerbated by aridity. Disruptive mutations in "Pod indehiscent 1" (PDH1), a pod sclerenchyma-specific lignin biosynthesis gene, has been linked to significant reductions in dehiscence in several legume species. We compared syntenic PDH1 regions across 12 legumes and two outgroups to uncover key historical evolutionary trends at this important locus. Our results clarified the extent to which PDH1 orthologs are present in legumes, showing the typical genomic context surrounding PDH1 has only arisen relatively recently in certain phaseoloid species (Vigna, Phaseolus, Glycine). The notable absence of PDH1 in Cajanus cajan may be a major contributor to its indehiscent phenotype compared with other phaseoloids. In addition, we identified a novel PDH1 ortholog in Vigna angularis and detected remarkable increases in PDH1 transcript abundance during Vigna unguiculata pod development. Investigation of the shared genomic context of PDH1 revealed it lies in a hotspot of transcription factors and signaling gene families that respond to abscisic acid and drought stress, which we hypothesize may be an additional factor influencing expression of PDH1 under specific environmental conditions. Our findings provide key insights into the evolutionary history of PDH1 and lay the foundation for optimizing the pod dehiscence role of PDH1 in major and understudied legume species.

Identification of candidate genes for LepR1 resistance against Leptosphaeria maculans in Brassica napus.

Utilising resistance (R) genes, such as LepR1, against Leptosphaeria maculans, the causal agent of blackleg in canola (Brassica napus), could help manage the disease in the field and increase crop yield. Here we present a genome wide association study (GWAS) in B. napus to identify LepR1 candidate genes. Disease phenotyping of 104 B. napus genotypes revealed 30 resistant and 74 susceptible lines. Whole genome re-sequencing of these cultivars yielded over 3 million high quality single nucleotide polymorphisms (SNPs). GWAS in mixed linear model (MLM) revealed a total of 2,166 significant SNPs associated with LepR1 resistance. Of these SNPs, 2108 (97%) were found on chromosome A02 of B. napus cv. Darmor bzh v9 with a delineated LepR1_mlm1 QTL at 15.11-26.08 Mb. In LepR1_mlm1, there are 30 resistance gene analogs (RGAs) (13 nucleotide-binding site-leucine rich repeats (NLRs), 12 receptor-like kinases (RLKs), and 5 transmembrane-coiled-coil (TM-CCs)). Sequence analysis of alleles in resistant and susceptible lines was undertaken to identify candidate genes. This research provides insights into blackleg resistance in B. napus and assists identification of the functional LepR1 blackleg resistance gene.

Identification of a Major QTL-Controlling Resistance to the Subtropical Race 4 of Fusarium oxysporum f. sp. cubense in Musa acuminata ssp. malaccensis.

Vascular wilt caused by the ascomycete fungal pathogen Fusarium oxysporum f. sp. cubense (Foc) is a major constraint of banana production around the world. The virulent race, namely Tropical Race 4, can infect all Cavendish-type banana plants and is now widespread across the globe, causing devastating losses to global banana production. In this study, we characterized Foc Subtropical Race 4 (STR4) resistance in a wild banana relative which, through estimated genome size and ancestry analysis, was confirmed to be Musa acuminata ssp. malaccensis. Using a self-derived F2 population segregating for STR4 resistance, quantitative trait loci sequencing (QTL-seq) was performed on bulks consisting of resistant and susceptible individuals. Changes in SNP index between the bulks revealed a major QTL located on the distal end of the long arm of chromosome 3. Multiple resistance genes are present in this region. Identification of chromosome regions conferring resistance to Foc can facilitate marker assisted selection in breeding programs and paves the way towards identifying genes underpinning resistance.

Innovative Advances in Plant Genotyping.

Over the past decade, advances in plant genotyping have been critical in enabling the identification of genetic diversity, in understanding evolution, and in dissecting important traits in both crops and native plants. The widespread popularity of single-nucleotide polymorphisms (SNPs) has prompted significant improvements to SNP-based genotyping, including SNP arrays, genotyping by sequencing, and whole-genome resequencing. More recent approaches, including genotyping structural variants, utilizing pangenomes to capture species-wide genetic diversity and exploiting machine learning to analyze genotypic data sets, are pushing the boundaries of what plant genotyping can offer. In this chapter, we highlight these innovations and discuss how they will accelerate and advance future genotyping efforts.

A chromosome-level genome assembly of Plantago ovata.

Plantago ovata is cultivated for production of its seed husk (psyllium). When wet, the husk transforms into a mucilage with properties suitable for pharmaceutical industries, utilised in supplements for controlling blood cholesterol levels, and food industries for making gluten-free products. There has been limited success in improving husk quantity and quality through breeding approaches, partly due to the lack of a reference genome. Here we constructed the first chromosome-scale reference assembly of P. ovata using a combination of 5.98 million PacBio and 636.5 million Hi-C reads. We also used corrected PacBio reads to estimate genome size and transcripts to generate gene models. The final assembly covers ~ 500 Mb with 99.3% gene set completeness. A total of 97% of the sequences are anchored to four chromosomes with an N50 of ~ 128.87 Mb. The P. ovata genome contains 61.90% repeats, where 40.04% are long terminal repeats. We identified 41,820 protein-coding genes, 411 non-coding RNAs, 108 ribosomal RNAs, and 1295 transfer RNAs. This genome will provide a resource for plant breeding programs to, for example, reduce agronomic constraints such as seed shattering, increase psyllium yield and quality, and overcome crop disease susceptibility.

Key Advances in the New Era of Genomics-Assisted Disease Resistance Improvement of Brassica Species.

Disease resistance improvement remains a major focus in breeding programs as diseases continue to devastate Brassica production systems due to intensive cultivation and climate change. Genomics has paved the way to understand the complex genomes of Brassicas, which has been pivotal in the dissection of the genetic underpinnings of agronomic traits driving the development of superior cultivars. The new era of genomics-assisted disease resistance breeding has been marked by the development of high-quality genome references, accelerating the identification of disease resistance genes controlling both qualitative (major) gene and quantitative resistance. This facilitates the development of molecular markers for marker assisted selection and enables genome editing approaches for targeted gene manipulation to enhance the genetic value of disease resistance traits. This review summarizes the key advances in the development of genomic resources for Brassica species, focusing on improved genome references, based on long-read sequencing technologies and pangenome assemblies. This is further supported by the advances in pathogen genomics, which have resulted in the discovery of pathogenicity factors, complementing the mining of disease resistance genes in the host. Recognizing the co-evolutionary arms race between the host and pathogen, it is critical to identify novel resistance genes using crop wild relatives and synthetic cultivars or through genetic manipulation via genome-editing to sustain the development of superior cultivars. Integrating these key advances with new breeding techniques and improved phenotyping using advanced data analysis platforms will make disease resistance improvement in Brassica species more efficient and responsive to current and future demands.